Internet DRAFT - draft-zhang-icnrg-icniot
draft-zhang-icnrg-icniot
ICN Research Group Y. Zhang
Internet-Draft D. Raychadhuri
Intended status: Informational WINLAB, Rutgers University
Expires: December 28, 2017 L. Grieco
Politecnico di Bari (DEI)
E. Baccelli
INRIA
J. Burke
UCLA REMAP
R. Ravindran
G. Wang
Huawei Technologies
A. Lindgren
B. Ahlgren
RISE SICS
O. Schelen
Lulea University of Technology
June 26, 2017
Design Considerations for Applying ICN to IoT
draft-zhang-icnrg-icniot-01
Abstract
The Internet of Things (IoT) promises to connect billions of objects
to the Internet. After deploying many stand-alone IoT systems in
different domains, the current trend is to develop a common, "thin
waist" of protocols over a horizontal unified, defragmented IoT
architecture. Such an architecture will make objects accessible to
applications across organizations and domains. Towards this goal,
quite a few proposals have been made to build an application-layer
based unified IoT platform on top of today's host-centric Internet.
However, there is a fundamental mismatch between the host-centric
nature of todays Internet and mostly information-centric nature of
the IoT system. To address this mismatch, an information-centric
network (ICN) architecture can provide a common set of protocols and
services, called 'ICN-IoT', which can be used to build IoT platforms.
ICN-IoT leverages the salient features of ICN, and thus provides
naming, security, mobility support,scalability, and efficient content
and service delivery.
This draft summarizes general IoT demands, and covers the challenges
and design considerations ICN faces to realize a ICN-IoT framework
based on ICN architecture.
Zhang, et al. Expires December 28, 2017 [Page 1]
Internet-Draft ICN based Architecture for IoT June 2017
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on December 28, 2017.
Copyright Notice
Copyright (c) 2017 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. IoT Motivation . . . . . . . . . . . . . . . . . . . . . . . 3
2. Motivating ICN for IoT . . . . . . . . . . . . . . . . . . . 4
3. IoT Architectural Requirements . . . . . . . . . . . . . . . 9
3.1. Naming . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2. Security and Privacy . . . . . . . . . . . . . . . . . . 10
3.3. Scalability . . . . . . . . . . . . . . . . . . . . . . . 10
3.4. Resource Constraints . . . . . . . . . . . . . . . . . . 10
3.5. Traffic Characteristics . . . . . . . . . . . . . . . . . 11
3.6. Contextual Communication . . . . . . . . . . . . . . . . 12
3.7. Handling Mobility . . . . . . . . . . . . . . . . . . . . 12
3.8. Storage and Caching . . . . . . . . . . . . . . . . . . . 13
3.9. Communication Reliability . . . . . . . . . . . . . . . . 13
3.10. Self-Organization . . . . . . . . . . . . . . . . . . . . 14
3.11. Ad hoc and Infrastructure Mode . . . . . . . . . . . . . 14
Zhang, et al. Expires December 28, 2017 [Page 2]
Internet-Draft ICN based Architecture for IoT June 2017
3.12. IoT Platform Management . . . . . . . . . . . . . . . . . 15
4. State of the Art . . . . . . . . . . . . . . . . . . . . . . 15
4.1. Silo IoT Architecture . . . . . . . . . . . . . . . . . . 15
4.2. Application-Layer Unified IoT Solutions . . . . . . . . . 16
4.2.1. Weaknesses of the Application-Layer Approach . . . . 17
4.2.2. Suitability of Delay Tolerant Networking(DTN) . . . . 19
5. Advantages of using ICN for IoT . . . . . . . . . . . . . . . 19
6. ICN Design Considerations for IoT . . . . . . . . . . . . . . 21
6.1. Naming Devices, Data, and Services . . . . . . . . . . . 21
6.2. Name Resolution . . . . . . . . . . . . . . . . . . . . . 25
6.3. Security and Privacy . . . . . . . . . . . . . . . . . . 26
6.4. Caching . . . . . . . . . . . . . . . . . . . . . . . . . 28
6.5. Storage . . . . . . . . . . . . . . . . . . . . . . . . . 30
6.6. Routing and Forwarding . . . . . . . . . . . . . . . . . 31
6.7. Mobility Management . . . . . . . . . . . . . . . . . . . 32
6.8. Contextual Communication . . . . . . . . . . . . . . . . 33
6.9. In-network Computing . . . . . . . . . . . . . . . . . . 33
6.10. Self-Orgnization . . . . . . . . . . . . . . . . . . . . 34
6.11. Communications Reliability . . . . . . . . . . . . . . . 35
6.12. Resource Constraints and Heterogeneity . . . . . . . . . 35
7. Differences from T2TRG . . . . . . . . . . . . . . . . . . . 36
8. Security Considerations . . . . . . . . . . . . . . . . . . . 36
9. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 36
10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 36
11. Informative References . . . . . . . . . . . . . . . . . . . 37
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 48
1. IoT Motivation
During the past decade, many Internet of Things (IoT) systems have
been developed and deployed in different domains. The recent trend,
however, is to evolve towards a more unified IoT architecture, in
which a large number of objects connect to the Internet, available
for interactions among themselves, as well as interactions with many
different applications across boundaries of administration and
domains. General IoT applications involve sensing, processing, and
secure content distribution occurring at various timescales and at
multiple levels of hierarchy depending on the application
requirements. This requires the system to adopt a unified
architecture providing pull, push and publish/subscribe mechanisms
using application abstractions, common naming, payload, encryption
and signature schemes. This requires open APIs to be generic enough
to support commonly used interactions between consumers, content
producer, and IoT services, as opposed to proprietary APIs that are
common in today's systems. Building a unified IoT architecture,
however, poses great challenges on the underlying network and
systems. To name a few, it needs to support 50-100 Billion networked
objects [1], many of which are mobile. The objects will have
Zhang, et al. Expires December 28, 2017 [Page 3]
Internet-Draft ICN based Architecture for IoT June 2017
extremely heterogeneous means of connecting to the Internet, often
with severe resource constraints. Interactions between the
applications and objects are often real-time and dynamic, requiring
strong security and privacy protections. In addition, many IoT
applications are inherently information centric (e.g., data consumers
usually need data sensed from the environment without any reference
to the sub-set of sensors that will provide the asked information).
Taking a general IoT perspective, we first motivate the discussion of
ICN for IoT using well known scenarios. Then we discuss the IoT
requirements generally applicable to many well known IoT scenarios.
We then discuss how the current application-layer unified IoT
architectures fail to meet these requirements. We follow this by key
ICN features that makes it a better candidate to realize an unified
IoT framework. We then discuss IoT design challenges from an ICN
perspective and requirements posed towards its design.
2. Motivating ICN for IoT
ICN offers many features including name-based networking, content
object security, caching, computing and storage, mobility, context-
aware networking (see Section 3.6) and support for ad hoc networking
features, all of which have to be realized in an application-specific
means in the context of IP-IoT. These compelling features enable a
distributed and intelligent data distribution platform to support
heterogeneous IoT services with features like device bootstrapping
with minimal configuration, simpler protocols to aid self-organizing
among the IoT elements, natural support for compute and caching logic
at strategic points in the network. We discuss these features
through the following scenarios that are difficult to realize over IP
today, and whose characteristics we argue match the features offered
by ICN.
o Smart Mobility: Smarter end-user devices and Machine-to-Machine
(M2M) connection are undergoing a significant growth. By 2021,
there will be more than 10 billion mobile devices and connection,
including smartphones, tablets, wearables, vehicles [1]. Involved
fields range from medical and healthcare, fitness, clothing, to
environmental monitoring [40]. In particular, one of the most
affected domain is transportation and the so-called Intelligent
Transport Systems (ITS) [42]. It aims at providing multi-modal
transportation, embracing public and private municipal, regional,
national, trans-national vehicles and fleets. This extremely
heterogeneous eco-system of means of transportation is made
available to users and citizens through advanced services. These
services are able to fulfill usability requirements while pursuing
system level objectives, thus including: (i) the reduction of the
CO2 footprint, (ii) the real-time delivery of specific goods,
Zhang, et al. Expires December 28, 2017 [Page 4]
Internet-Draft ICN based Architecture for IoT June 2017
(iii) the reduction of traffic within urban areas, (iv) the
provisioning of pleasant journeys to tourists, and (v) the general
commitment of satisfactory travel time and experience [117]. In
this context, IoT technologies can play a pivotal, in particular,
Traffic Management Systems (TMS) aided by IoT technologies are
creating novel approaches to traffic modeling [47]. Moreover,
such features enable advanced design paradigms (e.g., Mobility as
a Service (MaaS) [39]) with huge implications in systems
architectures [48]. As a consequence, smart mobility support can
be a significant use case of ICN-IoT. The important ICN features
that corroborate mobility support are:
* The location independence of content allows one to manage
consumer mobility in a simpler way than IP. Different from
Mobile IP, that needs 'triangular routing' to locate moving
hosts, ICN envisions that the consumers just needs to re-issue
content requests after changing the attachment point [43];
* Since content is not bound to a specific location, it can be
cached anywhere in the network. This caching mechanism adds
redundancy to the system. Therefore, if the producer loses
connectivity while it is moving, a content request can be
resolved to an intermediate node en-route or routed towards a
caching node [43];
* The content request-response communication paradigm decouples
publications and subscriptions in time and space. Therefore,
entities involved are not aware of each other and do not need
to be connected at the same time [44];
* The use of in-network Name Resolution Service design allows to
identify content name's current location in the network, thanks
to its network function of updating named entity location
information [56].
From a technological perspective, open challenges are: (i)
interoperability across different IoT technologies; (ii) namespace
design able to harmonize ITS standards; (iii) scalable data-
sharing model across real-time (and non real-time) traffic
sources; (iv) definition of travel-centric services based on ICN-
IoT; (v) seamless support to mobility; (vi) content authentication
and cryptography.
o Smart Building: Buildings are gaining smart capabilities that
allow to enhance comfort, provide safety and security, manage
efficiently energy [101]. In particular, smart buildings are no
longer simple energy consumer, but can also be prosumers with on-
site energy generation systems. These systems can improve
Zhang, et al. Expires December 28, 2017 [Page 5]
Internet-Draft ICN based Architecture for IoT June 2017
building's usability towards: (i) Smart heating, ventilation, and
air conditioning (HVAC), (ii) Smart lightings, (iii) Plug loads,
(iv) Smart windows. The main requirements of those sub-systems
are [101]: (i) context awareness; (ii) resource-constrained
devices; (iii) interoperability across heterogeneous technologies;
(iv) security and privacy protection. The ICN paradigm could ease
the fulfillment of those requirements because, usually, smart
building services are information centric by design: this means
that every time an autonomic management loop is established within
the smart building to control some physical variables of interest,
the information exchanged between users, sensors, actuators, and
controllers do not immediately translate to specific nodes within
the building but could be provided by multiple sensors / gateways.
The relevance of ICN in Smart Building is recognized in literature
with reference to the several frameworks deployed in various
environments. For instance, in [61], nodes are distributed in
different rooms, floors, and buildings of a campus university and
their energy consumption and individual behavior are monitored.
Smart home application is investigated in [103], by evaluating
data retrieval delay and data packet loss. Moreover, [104]
designed and tested lighting control over NDN in a theater. In
this context, specific ICN challenges are: (i) design of a
scalable namespace for uniquely identifying the information of
interest, (ii) data-sharing model across heterogeneous systems,
(iii) self-organizing functionalities for improving network
connections between end-nodes, utilities and the control center,
(iv) authentication procedures to grant data confidentiality and
integrity.
o Smart Grid: Smart Grids are increasingly transforming into cyber-
physical systems [18] with the goal of maximum automation towards
efficiency and minimal human intervention. The system is very
complex comprising of power distribution grids, end user
applications (e.g. EV charging systems, appliances etc), smart
monitoring systems (spanning end user and the power grids),
heterogeneous energy producing sources (including prosumers), and
load distribution and balancing systems. Current smart grid
systems are managed using Supservisory Control and Data
Acquisition (SCADA) frameworks that are centralized and highly
restrictive unidirectional communication support [19]. Hence the
requirement is towards : 1) greater flexibility to distribute the
energy from the feeder through real-time reconfiguration of
multiple monitoring devices (e.g. phasor measurement units
(PMUs)), and management operations which require efficient data
delivery infrastructure; 2) large scale data delivery
infrastructure, which also include latency sensitive applications,
inter-connecting heterogeneous smart grid producing, monitoring
and consuming end user devices; 3) Resiliency,which is critical to
Zhang, et al. Expires December 28, 2017 [Page 6]
Internet-Draft ICN based Architecture for IoT June 2017
the operation and protection of the grid; 4)Security, to protect
mission critical grid applications from network intrusions ; 5)
understanding machine-to-machine traffic patterns for optimal
placement of storage and computing for maximum efficiency. Smart
grids can benefit from ICN in the following ways [20] :
* Smart grid will benefit from naming content than hosts, as it
is more likely that data generated by one subsystem will be
useful for multiple entities. Further, naming content allows
to enable many-to-many model of communication, which is very
in-efficient in host-centric architectures.
* ICN features of in-network computing, storage and caching will
enable better use of network resources and benefit diverse
application needs varying from applications that has low
bitrate and is latency tolerant (e.g. smart grid and energy
pricing) to higher data rate ones with stringent delay/
disruption requirements (e.g. synchrophasor measurements).
Also it is typical in smart grid systems to have applications
consuming the same data at different rates in which case in-
network caching and computing could help.
* Host-centric networking exposes a mission critical
infrastructure like smart grid infrastructure to intrusion and
DOS attacks, this is directly related to exposing the IP
addresses of critical applications and subsystems. Naming
content, service or device de-couples it from the location,
reducing the exposure to target a specific smart grid subsystem
based on a geographical context.
* ICN's name based networking offers the potential for self-
configuration both during bootstrapping and during the regular
operation of the grid allowing scalable operation and self-
recovery during faults or maintenance tasks in the system.
o Smart Industrial Automation : In a smart and connected industry
environment, there is a multitude of equipment with sensors that
generate large volumes of data during normal operation. This
range from highly time-critical data for real-time control of
production processes, to less time-critical data that is collected
to central cloud environment for control room monitoring, to pure
log data without latency requirements that is mainly kept for a
posteriori analysis. Industrial wireless networks are harsh
environments with lots of potential interference at the same time
as hard reliability and real-time requirements are placed by many
applications. This means that available network capacity is not
always high, so congestion is likely to be experienced by traffic
with less stringent timing requirements. One such example is when
Zhang, et al. Expires December 28, 2017 [Page 7]
Internet-Draft ICN based Architecture for IoT June 2017
errors occur in the production process, a mobile workforce will
need to investigate the problem on-site and will need high
resolution data from the faulty machine as well as other process
data from other parts of the plant. The mobile workforce will
locally perform diagnostics or maintenance and they rely on the
information from the production system both for safety and to
solve any issues in the plant. They rely on both historical data
in order to pinpoint the root cause of the problems, as well as
the current data flows in order to assess the present state of the
equipment under control. High resolution measurements are
generated close to the mobile workforce while the historic data
has to be retrieved from the historian servers. Multiple workers
involved in the process will access the same data, possibly with a
slight time-shift. The network thus need to support a mobile
users to get access to data flows in a way suitable for their
physical location and task requirements. Introducing ICN
functionality into the system can introduce several benefits that
will enhance the working experience and productivity for the
mobile workforce.
* When using ICN, naming of data can be done in a way that
corresponds well to the current names often used in industrial
scenarios as the hierarchical names defined by OPC Foundation
[10] maps well to the CCN/NDN name space.
* ICN provides the possibility to get newest data without knowing
the location of the caches or whether a particular piece of
data is available locally or in a central repository. Also
gives the possibility to get either local high-resolution data
or remote low-resolution data (no need to store all data
centrally, which is maybe not even possible due to large data
volumes). May require known naming conventions or routing
policies that can route interests to the right location.
* Reduces network usage as unnecessary data is not transmitted,
and data accessed by multiple workers is only sent once.
* Workforce mobility between different access points in the
factory is inherently supported without the need to maintain
connection state.
* Removing tedious configurations in clients since that is
provided by the infrastructure.
* Allow sharing of large data volumes between users that are in
physical proximity without introducing additional traffic on
the backbone.
Zhang, et al. Expires December 28, 2017 [Page 8]
Internet-Draft ICN based Architecture for IoT June 2017
* Caching of data means avoiding database accesses to a
distributed redundant database in the central infrastructure
with consistency requirements.
3. IoT Architectural Requirements
A unified IoT platform has to support interactions among a large
number of mobile devices across the boundaries of organizations and
domains. As a result, it naturally poses stringent requirements in
every aspect of the system design. Below, we outline a few important
requirements that a unified IoT platform has to address.
3.1. Naming
An important step towards realizing a unified IoT architecture is the
ability to assign names that are unique to each device, data items
generated by these devices, or a group of devices towards a common
objective. Naming has the following requirements. Firstly, names
need to be persistent against dynamic features that are common in IoT
systems, such as lifetime, mobility or migration. Secondly, names
that are derived from the keys need to be self-certifying, for both
device-centric communication and content-centric communication. For
device-centric communication, the binding between device names and
the device must be secure. For content-centric communication, the
binding between the names and the content has to be secure. Thirdly,
names usually serve multiple purposes: routing, security (self-
certifying) or human-readability. For IoT applications, the choice
of flat versus human readable names needs to be made considering
application and network requirements such as privacy and network
level scalability, and the name space explosion that may occur
because of complex relationship between name hierarchies [120] which
might confound application logic. In order to ensure the
trustworthiness of the names, a name certificate service (NCS) needs
to be considered. Such a service acts as a certificate authority in
assigning names, which are themselves public keys or appropriately
bound to the name for verification at the consumer's end. In short,
the NCS must provide services analogous to those provided by a Public
Key Infrastructure (PKI). In ICN, users may either generate their
own public keys and submit them to the NCS for registration, or may
contact the NCS to acquire public keys. Consequently, the NCS
publishes approved cryptographic suites, object categories and object
description formats, as well as allows users to self-certify
themselves.
Zhang, et al. Expires December 28, 2017 [Page 9]
Internet-Draft ICN based Architecture for IoT June 2017
3.2. Security and Privacy
A variety of security and privacy concerns exist in IoT. For example
the unified IoT architecture makes physical objects accessible to
applications across organizations and domains. Further, it often
integrates with critical infrastructure and industrial systems with
life safety implications, bringing with it significant security
challenges and regulatory requirements [13], as will be discussed in
Section 6.3. Security and privacy thus become a serious concern, as
does the flexibility and usability of the design approaches. Beyond
the overarching trust management challenge, security includes data
integrity, authentication, and access control at different layers of
the IoT architecture. Privacy includes several aspects: (1) privacy
of data producer/consumer that is directly related to each individual
vertical domain such as heath, electricity, etc., (2) privacy of data
content, and (3) privacy of contextual information such as time and
location of data transmission [65].
3.3. Scalability
Cisco predicts there will be around 50 Billion IoT devices such as
sensors, RFID tags, and actuators, on the Internet by 2020 [1]. As
mentioned above, a unified IoT platform needs to name every entity
such as data, device, service etc. Scalability has to be addressed
at multiple levels of the IoT architecture including naming,
security, name resolution, routing and forwarding level. Mobility
adds further challenge in terms of scalability. Particularly with
respect to name resolution the system should be able to
register/update/resolve a name within a short latency. In addition
scalability is also affected because of IoT system specific features
such as IoT resource object count, state and rate of information
updates generated by the sensing devices.
3.4. Resource Constraints
IoT devices can be broadly classified as type 1, type 2, and type 3
devices, with type 1 the most resource-constrained and type 3 the
most resource-rich [45]. In general, there are the following types
of resources: power, computing, storage, bandwidth, and user
interface.
Power constraints of IoT devices limit how much data these devices
can communicate, as it has been shown that communications consume
more power than other activities for embedded devices [46]. Flexible
techniques to collect the relevant information are required, and
uploading every single produced data to a central server is
undesirable. Computing constraints limit the type and amount of
processing these devices can perform. As a result, more complex
Zhang, et al. Expires December 28, 2017 [Page 10]
Internet-Draft ICN based Architecture for IoT June 2017
processing needs to be conducted in cloud servers or at opportunistic
points, example at the network edge, hence it is important to balance
local computation versus communication cost.
Storage constraints of the IoT devices limit the amount of data that
can be stored on the devices. This constraint means that unused
sensor data may need to be discarded or stored in aggregated compact
form time to time. Bandwidth constraints of the IoT devices limit
the amount of communication. Such devices will have the same
implication on the system architecture as with the power constraints;
namely, we cannot afford to collect single sensor data generated by
the device and/or use complex signaling protocols. It is also worth
mentioning that idle chatter in the background is strongly
discouraged to maintain connectivity or other volatile state.
User interface constraints refer to whether the device is itself
capable of directly interacting with a user should the need arise
(e.g., via a display and keypad or LED indicators) or requires the
network connectivity, either global or local, to interact with
humans.
The above discussed device constraints also affect application
performance with respect to latency.
3.5. Traffic Characteristics
IoT traffic can be broadly classified into local area traffic and
wide area traffic. Local area traffic is among nearby devices. For
example, neighboring cars may work together to detect potential
hazards on the highway, sensors deployed in the same room may
collaborate to determine how to adjust the heating level in the room.
These local area communications often involve data aggregation and
filtering, have real time constraints, and require fast device/data/
service discovery and association. At the same time, the IoT
platform has to also support wide area communications. For example,
in Intelligent Transportation Systems, re-routing operations may
require a broad knowledge of the status of the system, traffic load,
availability of freights, whether forecasts and so on. Wide area
communications require efficient data/service discovery and
resolution services.
While traffic characteristics for different IoT systems are expected
to be different, certain IoT systems have been analyzed and shown to
have comparable uplink and downlink traffic volume in some
applications such as [2], which means that we have to optimize the
bandwidth/energy consumption in both directions. Further, IoT
traffic demonstrates certain periodicity and burstiness [2]. As a
Zhang, et al. Expires December 28, 2017 [Page 11]
Internet-Draft ICN based Architecture for IoT June 2017
result, when provisioning the system, the shape of the traffic volume
has to be properly accounted for.
3.6. Contextual Communication
Many IoT applications rely on dynamic contexts in the IoT system to
initiate, maintain and terminate communication among IoT devices.
Here, we refer to a context as attributes applicable to a group of
devices that share some common features, such as their owners may
have a certain social relationship or belong to the same
administrative group, or the devices may be present in the same
location. There are two types of contexts: long-term quasi static
contexts and short-term dynamic contexts. In this draft, we focus on
the latter, which are more challenging to support, requiring fast
formation, update, lookup and association For example, cars traveling
on the highway may form a "cluster" based upon their temporal
physical proximity as well as the detection of the same event. These
temporary groups are referred to as contexts. IoT applications need
to support interactions among the members of a context, as well as
interactions across contexts.
Temporal context can be broadly categorized into two classes, long-
term contexts such as those that are based upon social contacts as
well as stationary physical locations (e.g., sensors in a car/
building), and short-term contexts such as those that are based upon
temporary proximity (e.g., all taxicabs within half a mile of the
Time Square at noon on Oct 1, 2013). Between these two classes,
short-term contexts are more challenging to support, requiring fast
formation, update, lookup and association.
3.7. Handling Mobility
There are several degrees of mobility in a unified IoT architecture,
ranging from static as in fixed assets to highly dynamic in vehicle-
to-vehicle environments.
Mobility in the IoT architecture can mean 1) the data producer
mobility (i.e., location change), 2) the data consumer mobility, 3)
IoT Network mobility (e.g., a body-area network in motion as a person
is walking); and 4) disconnection between the data source and
destination pair (e.g., due to unreliable wireless links). The
requirement on mobility support is to be able to deliver IoT data
below an application's acceptable delay constraint in all of the
above cases, and if necessary to negotiate different connectivity or
security constraints specific to each mobile context. More detailed
discussions are presented in Section 6.7.
Zhang, et al. Expires December 28, 2017 [Page 12]
Internet-Draft ICN based Architecture for IoT June 2017
3.8. Storage and Caching
Storage and caching plays a very significant role depending on the
type of IoT ecosystem, also a function subjected to privacy and
security guidelines. Caching is usually done for increasing data
availability in the network and reliability purposes, especially in
wireless scenarios in the network access. Storage is more important
for IoT, storing data for long term analysis. Data is stored in
strategic locations in the network to reduce control and computation
overhead. In a unified IoT architecture, depending on application
requirements, content caching will be strictly driven by application
level policies considering privacy requirements. If for certain kind
of IoT data pervasive caching is allowed, intermediate nodes don't
need to always forward a content request to its original creator;
rather, receiving a cached copy is sufficient for IoT applications.
This optimization may greatly reduce the content access latencies.
Furthermore considering hierarchical nature of IoT systems, ICN
architectures enable flexible heterogeneous and potentially fault-
tolerant approach to storage providing persistence at multiple
levels.
Hence in the context of IoT while ICN allows resolution to replicated
stored copies, it should also strive for the balance between content
security/privacy and regulations considering application
requirements.
3.9. Communication Reliability
IoT applications can be broadly categorized into mission critical and
non-mission critical. For mission critical applications, reliable
communication is one of the most important features as these
applications have strong QoS requirements such as low latency and
probability of error during information transfer. To summarize,
reliable communication desires the following capabilities for the
underlying system: (1) seamless mobility support under normal
operating conditions, (2) efficient routing in the presence of
intermittent disconnection, (3) QoS aware routing, (4) support for
redundancy at all levels of a system (device, service, network,
storage etc.), and (5) support for rich and diverse communication
patterns, both within an IoT domain consisting of multiple IoT nodes
and one or more gateway nodes to the Internet and across multiple
such domains.
Zhang, et al. Expires December 28, 2017 [Page 13]
Internet-Draft ICN based Architecture for IoT June 2017
3.10. Self-Organization
The unified IoT architecture should be able to self-organize to meet
various application requirements, especially the capability to
quickly discover heterogeneous and relevant (local or global)
devices/data/services based on the context. This discovery can be
achieved through an efficient publish-subscribe service, or through
private community grouping/clustering based upon trust and other
security requirements. In the former case, the publish-subscribe
service must be efficiently implemented, able to support seamless
mobility, in- network caching, name-based routing, etc. In the
latter case, the IoT architecture needs to discover the private
community groups/clusters efficiently.
Another aspect of self-organization is decoupling the sensing
Infrastructure from applications. In a unified IoT architecture,
various applications run on top of a vast number of IoT devices.
Upgrading the firmware of the IoT devices is a difficult work. It is
also not practical to reprogram the IoT devices to accommodate every
change of the applications. The infrastructure and the application
specific logics need to be decoupled. A common interface is required
to dynamically configure the interactions between the IoT devices and
easily modify the application logics on top of the sensing/actuating
infrastructure [30] [31].
3.11. Ad hoc and Infrastructure Mode
Depending upon whether there is communication infrastructure, an IoT
system can operate either in ad-hoc or infrastructure mode.
For example, a vehicle may determine to report its location and
status information to a server periodically through cellular
connection, or, a group of vehicles may form an ad-hoc network that
collectively detect road conditions around them. In the cases where
infrastructure is unavailable, one of the participating nodes may
choose to become the temporary gateway.
The unified IoT architecture needs to design a common protocol that
serves both modes. Such a protocol should address the challenges
that arise in these two modes: (1) scalability and low latency for
the infrastructure mode and (2) efficient neighbor discovery and ad-
hoc communication for the ad-hoc mode. Finally we note that hybrid
modes are very common in realistic IoT systems.
Zhang, et al. Expires December 28, 2017 [Page 14]
Internet-Draft ICN based Architecture for IoT June 2017
3.12. IoT Platform Management
An IoT platforms' service, control and data plane will be governed by
its own management infrastructure which includes distributed and
centralized middleware, discovery, naming, self-configuring, analytic
functions, and information dissemination to achieve specific IoT
system objectives [25][26][27]. Towards this, new IoT management
mechanisms and service metrics need to be developed to measure the
success of an IoTdeployment. Considering an IoT systems' defining
characteristics such as, its potential large number of IoT devices,
objective to save power, mobility, and ad hoc communication,
autonomic self-management mechanisms become very critical. Further
considering its hierarchical information processing deployment model,
the platform needs to orchestrate computational tasks according to
the involved sensors and the available computation resources which
may change over time. An efficient computation resource discovery
and management protocol is required to facilitate this process. The
trade-off between information transmission and processing is another
challenge.
4. State of the Art
Over the years, many stand-alone IoT systems have been deployed in
various domains. These systems usually adopt a vertical silo
architecture and support a small set of pre-designated applications.
A recent trend, however, is to move away from this approach, towards
a unified IoT architecture in which the existing silo IoT systems, as
well as new systems that are rapidly deployed. By unified, we mean
all the application and network components that use common APIs to
interact with each other. This will make their data and services
accessible to general Internet applications (as in ETSI- M2M and
oneM2M standards). In such a unified architecture, resources can be
accessed over Internet and shared across the physical boundaries of
the enterprise. However, current approaches to achieve this
objective are mostly based upon service overlays over the Internet,
whose inherent inefficiencies due to IP protocol [56] hinders the
architecture from satisfying the IoT requirements outlined earlier,
particularly in terms of scalability, security, mobility, and self-
organization, discussed more in Section 4.2.
4.1. Silo IoT Architecture
Zhang, et al. Expires December 28, 2017 [Page 15]
Internet-Draft ICN based Architecture for IoT June 2017
[IoT Server]
|
|
______|_______
_______ { }
{ } { }
{IoT Dev}\ { Internet }---[IoT Application]
{_______} [IoTGW]---{ }
{ }
{______________}
Figure 1:Silo architecture of standalone IoT systems
A typical standalone IoT system is illustrated in Figure 1, which
includes devices, a gateway, a server and applications. Many IoT
devices have limited power and computing resources, unable to
directly run normal IP access network (Ethernet, WIFI, 3G/LTE etc.)
protocols. Therefore they use the IoT gateway to the server.
Through the IoT server, applications can subscribe to data collected
by devices, or interact with devices.
There have been quite a few popular protocols for standalone IoT
systems, such as DF-1, MelsecNet, Honeywell SDS, BACnet, etc.
However, these protocols are operating at the device-level
abstraction, instead of information driven, which may sometimes lead
to a fragmented protocol space that requires a higher-level solution
for better interoperability.
4.2. Application-Layer Unified IoT Solutions
The current approach to a unified IoT architecture is to make IoT
gateways and servers adopt standard APIs. IoT devices connect to the
Internet through the standard APIs and IoT applications subscribe and
receive data through standard control and data APIs. Building on top
of today's Internet this application-layer unified IoT architecture
is the most practical approach towards a unified IoT platform.
Towards this, there are ongoing standardization efforts including
ETSI[3], oneM2M[4]. Network operators can use frameworks to build
common IOT gateways and servers for their customers. In addition,
IETF's CORE working group [5] is developing a set of protocols like
CoAP (Constrained Application Protocol) [78], that is a lightweight
protocol modeled after HTTP [79] and adapted specifically for the
Internet of Things (IoT). CoAP adopts the Representational State
Transfer (REST) architecture with Client-Server interactions. It
uses UDP as the underlying transport protocol with reliability and
multicast support. Both CoAP and HTTP are considered as the suitable
Zhang, et al. Expires December 28, 2017 [Page 16]
Internet-Draft ICN based Architecture for IoT June 2017
application level protocols for Machine-to-Machine communications, as
well as IoT. For example, oneM2M (which is one of leading standards
for unified M2M architecture) has both the protocol bindings to HTTP
and CoAP for its primitives. Figure 2 shows the architecture adopted
in this approach.
Publishing----[IoT Server]----Subscribing--
| / | \ |
| / | \ |
| /______|_______ \ |
___________ | /{ } publishing |
{ } | | { } | |
{Smart Homes}\ | | { Internet }---------[IoT Application]
{___________} [IoTGW]---{ }\ | ________________
| { } \ | { }
| {______________} [IoTGW]-{Smart Healthcare}
| | {________________}
Publishing [IoTGW]
| ____|_____
| { }
---{Smart Grid}
{__________}
Figure 2: Implementing an open IoT architecture through standardized APIs
on the IoT gateways and the server
4.2.1. Weaknesses of the Application-Layer Approach
The above application-layer approach can work with many different
protocols, but the system is built upon today's IP network, which has
inherent weaknesses towards supporting a unified IoT system. As a
result, it cannot satisfy some of the requirements we outlined in
Section 3:
o Naming. In current application-layer IoT systems the naming
scheme is host centric, i.e., the name of a given resource/service
is linked to the device that can provide it. In turn, device
names are coupled to IP addresses, which are not persistent in
mobile scenarios. On the other side, in IoT systems the same
service/ resource could be offered by different devices.
o Security and Trust. In IP, the security and trust model is based
on session established between two hosts. Session-based protocols
rely on the exchange of several messages before a secure session
is established. Use of such protocols in constrained IoT devices
Zhang, et al. Expires December 28, 2017 [Page 17]
Internet-Draft ICN based Architecture for IoT June 2017
can have serious consequences in terms of energy efficiency
because transmission and reception of messages is often more
costly than the cryptographic operations. The problem may be
amplified with the number of nodes the constrained device has to
interact with because of both the computation cost and per session
key state required to be managed by the constrained device. Also
the trust management schemes are still relatively weak, focusing
on securing communication channels rather than managing the data
that needs to be secured directly. Though key management in ICN
is no less complex than in host based interactions, the benefits
is associated with the security credentials in the content instead
of the host. Trust is via keys that are bound to names through
certificates whose private keys are held by the principals of the
system, with IP focusing on the channel model of security while
ICN focusing on the object model.
o Mobility. The application-layer approach uses IP addresses as
names at the network layer, which hinders the support for device/
service mobility or flexible name resolution. Further the Layer
2/3 management, and application-layer addressing and forwarding
required to deploy current IoT solutions limit the scalability and
management of these systems.
o Resource constraints. The application-layer approach requires
every device to send data to an aggregator, gateway or to the IoT
server. Resource constraints of the IoT devices, especially in
power and bandwidth, could seriously limit the performance of this
approach. On the other hand, ICN supports in-network
computing/caching/storage, which can alleviate this problem.
o Traffic Characteristics. In this approach, applications are
written in a host-centric manner suitable for point-to-point
communication. IoT requires multicast support that is challenging
the application-layer based IoT systems today, which has only
limited deployment in current Internet.
o Contextual Communications. This application-layer based IoT
approach may not react to dynamic contextual changes in a timely
fashion. The main reason is that context lists are usually kept
at the IoT server in this approach, and they cannot help
efficiently route requests information at the network layer.
o Storage and Caching. The application-layer approach supports
application-centric storage and caching but not what ICN envisions
at the network layer, or flexible storage enabled via name-based
routing or name-based lookup.
Zhang, et al. Expires December 28, 2017 [Page 18]
Internet-Draft ICN based Architecture for IoT June 2017
o Self-Organization. The application-layer approach is topology-
based as it is bound to IP semantics, and thus does not
sufficiently satisfy the self-organization requirement. In
addition to topological self-organization, IoT also requires data-
and service-level self-organization [97], which is not supported
by this approach.
o Ad-hoc and infrastructure mode. As mentioned above, the overlay-
based approach lacks self-organization, and thus does not provide
efficient support for the ad-hoc mode of communication.
4.2.2. Suitability of Delay Tolerant Networking(DTN)
In [21][22], delay-tolerant networking (DTN) has been considered to
support future IoT architecture. DTN was created to support
information delivery in the presence of network disruptions and
disconnections, which has been extended to support heterogeneous
networks and name-based routing. The DTN Bundle Protocol is able to
achieve some of these same advantages and could be beneficially used
in an IoT network to, for example, decouple sender and receiver. The
DTN architecture is however centered around named endpoints (endpoint
IDs), which usually correspond to a host or a service, and is mainly
a way to transport data, while ICN provides a different paradigm
centered around named data that addresses additional issues for IoT
applications [23] through features such as information naming,
information discovery, information request and dissemination. Also,
the endpoint IDs could be used to also identify named content,
enabling the use of the bundle protocol as a transport mechanism for
an information-centric system. Such a use of the bundle protocol as
transport would however still require other components from an ICN
architecture such as naming conventions, so since the exact transport
is not a major focus of the issues in this draft, most of of the
discussions are applicable to a generic ICN architecture in general.
5. Advantages of using ICN for IoT
A key concept of ICN is the ability to name data independently from
the current location at which it is stored, which simplifies caching
and enables decoupling of sender and receiver. Using ICN to design
an architecture for IoT data potentially provides many such
advantages compared to using traditional host-centric networks and
other new architectures. This section highlights general benefits
that ICN could provide to IoT networks.
o Naming of Devices, Data and Services. The heterogeneity of both
network equipment deployed and services offered by IoT networks
leads to a large variety of data, services and devices. While
using a traditional host-centric architecture, only devices or
Zhang, et al. Expires December 28, 2017 [Page 19]
Internet-Draft ICN based Architecture for IoT June 2017
their network interfaces are named at the network level, leaving
to the application layer the task to name data and services. This
causes different applications to use different naming schemes, and
no consistent mapping from application layer names to network
names exist. In many common applications of IoT networks, data
and services are the main goal, and ICN provides an intuitive way
to name those in a way that can be utilized on the network layer
as well. Communication with a specific device is often secondary,
but when needed, the same ICN naming mechanisms can be used. The
network distributes content and provides a service, instead of
only sending data between two named devices. In this context,
data content and services can be provided by several devices, or
group of devices, hence naming data and services is often more
important than naming the devices. This naming mechanism also
enables self-configuration of the IoT system.
o Security and privacy. ICN advocates the model of object security
to secure data in the network. This concept is based on the idea
of securing information objects unlike session-based security
mechanisms which secure the communication channel between a pair
of nodes. ICN provides data integrity through Name-Data
Integrity, i.e., the guarantee that the given data corresponds to
the name with which it was addressed. Signature-based schemes can
additionally provide data authenticity, meaning establishing the
origin, or provenance, of the data, for example, by
cryptographically linking a data object to the identity of a
publisher. Confidentiality can be handled on a per object basis
based on keys established at the application level. All of this
means that the actual transmission of data does not have to be
secured as the same security mechanisms protect the data after
generation until consumed by a client, regardless of whether it is
in transit over a communication channel or stored in an
intermediate cache. In an ICN network, each individual object
within a stream of immutable objects could potentially be
retrieved from a cache in a different location. Having a trust
relationship with each of these different caches is not realistic.
Through Name-Data Integrity, ICN automatically guarantees data
integrity to the requester regardless of the location from where
it is delivered. The Object Security model also ensures that the
content is readily available in a secure state in the device
constraints are severe enough that it is not able to perform the
required cryptographic operations for Object Security, it may be
possible to offload this operation to a trusted gateway to which
only a single secure channel needs to be established. ICN can
also derive a name from a public key; cryptographic hash of a
public key also enables them to be self-certifying, i.e.,
authenticating the resource object does not require an external
authority [25][26].
Zhang, et al. Expires December 28, 2017 [Page 20]
Internet-Draft ICN based Architecture for IoT June 2017
o Distributed Caching and Processing. While caching mechanisms are
already used by other types of overlay networks, IoT networks can
potentially benefit even more from caching and in-network
processing systems, because of their resource constraints.
Wireless bandwidth and power supply can be limited for multiple
devices sharing a communication channel, and for small mobile
devices powered by batteries. In this case, avoiding unnecessary
transmissions with IoT devices to retrieve and distribute IoT data
to multiple places is important, hence processing and storing such
content in the network can save wireless bandwidth and battery
power. Moreover, as for other types of networks, applications for
IoT networks requiring shorter delays can benefit from local
caches and services to reduce delays between content request and
delivery.
o Decoupling between Sender and Receiver. IoT devices may be mobile
and face intermittent network connectivity. When specific data is
requested, such data can often be delivered by ICN without any
consistent direct connectivity between devices. Apart from using
structured caching systems as described previously, information
can also be spread by forwarding data opportunistically.
6. ICN Design Considerations for IoT
This section outlines some of the ICN specific design considerations
and challenges that must be considered when adopting an ICN design
for IoT applications and systems, and describes some of the trade
offs that will be involved in order to support large scale IoT
deployment with diverse application requirements.
Though ICN integrates content/service/host abstraction, name-based
routing, compute, caching/storage as part of the network
infrastructure, IoT requires special considerations given
heterogeneity of devices and interfaces such as for constrained
networking [61][119][121], data processing, and content distribution
models to meet specific application requirements which we identify as
challenges in this section.
6.1. Naming Devices, Data, and Services
The ICN approach of named data and services (i.e., device independent
naming) is typically desirable when retrieving IoT data. However,
data centric naming may also pose challenges.
o Naming of devices: Naming devices can be useful in an IoT system.
For example, actuators require clients to act on a specific node
of the deployed network, e.g. to switch it on or off; or it could
be necessary to access to a particular device for administrator
Zhang, et al. Expires December 28, 2017 [Page 21]
Internet-Draft ICN based Architecture for IoT June 2017
purposes. This can be achieved through the specific name that
uniquely identify the network entity of interest. Moreover, a
persistent name allows a device to change attachment point without
loosing its identity. A friendly way to address devices is using
contextual hierarchical names, where the same types of names as
for data objects can be used. To ensure that the device is always
reached, it is important that it is possible to disable caching
and request aggregation, if used, for such names.
o Size of data/service name: Content name can have variable length.
Since each name has to uniquely identify the content and can also
include self-certifying properties (e.g., the hash of the content
is bound to the name), its length can reach high values. In
particular, according to the specific application, content name
size can exceed Data size. This can be the case of IoT sensed
values that usually consist in few bytes: data could be as small
as a short integer in case of temperature values, or one-byte in
case of control messages of an actuator state (on/off). Moreover,
a too long name would probably incur in fragmentation at the link
layer, and related problems such as, several transmissions, delay
and security issues. Viable solutions to handle ICN packets
fragmentation and reassembly have been investigated in literature.
For instance, the work in [105] proposes to perform the operations
hop-by-hop: each hop fragments the packet that has to be forwarded
and reassembles the packet received for further processing. This
mechanism allows to efficiently handle the recovery of lost or
corrupted fragments locally, thus reducing packet delivery
failures that require application-level retransmissions.
o Hash-based content name: Hash algorithms are commonly used to name
content in order to verify that the content is the one requested.
This is only possible in contexts where the requested object is
already existing, and where there is a directory service to look
up names or learned through a manifest service. This approach is
suitable for systems with large data objects where it is important
to verify the content.
o Hierarchical names: The use of hierarchical names, such as in the
CCN and NDN architectures make it easier to create names a priori
and also provides a convenient way to use the same naming scheme
for node names. Since the names are not self-certifying, this
will require other mechanisms for verification of object
integrity. If routing is also done on the hierarchical names, the
system will loose some of its location independence and caching
will mostly only be done on the path to the publisher.
o Semantic and Metadata based content name: A semantic-based naming
approach can allow a successful name retrieving through keywords
Zhang, et al. Expires December 28, 2017 [Page 22]
Internet-Draft ICN based Architecture for IoT June 2017
(for example, 'noise level at position X'), even if a perfect
matching of name is not available [62]. Moreover, enriching
contents with metadata allows to better describe them and to
establish association between similar ones. However this
mechanism require more advanced functionality for matching of such
metadata in data objects to the semantics of the name (such as
comparing the position information of an object with the position
information of the requested name). The need for such potentially
computationally heavy tasks in intermediate nodes in the network
may be considered understanding the trade-offs in terms of
application and network performance.
o Naming of services: Similar to naming of devices or data, services
can be referred to with a unique identifier, provided by a
specific device or by someone assigned by a central authority as
the service provider. It can however also be a service provided
by anyone meeting some certain metadata conditions. Example of
services include content retrieval, that takes a content name/
description as input and returns the value of that content, and
actuation, that takes an actuation command as input and possibly
returns a status code afterwards.
o Trust: Names can be used to verify the authenticity and integrity
of the data. To provide security functionalities through names,
it is possible to use different approaches. On one hand,
hierarchical, schematized, Web-of-Trust models allow the public
key verification. On the other hand, self-certifying names allow
in-network integrity check of the name-key or name-content binding
without the need of a Public Key Infrastructure (PKI) or other
third party to establish whether the key is trustworthy or not.
This can be realized (i) directly: the hash of the content is
bound to the name; or (ii) indirectly: first, the hash of the
content is signed with the secret key of the publisher, then the
public key of the publisher and the signed hash are bound to the
name [44]. The hash algorithm can be applied to already existing
contents and where there is a directory service or manifests to
look up names. In case of contents not yet published, but
generated on demand, the hash cannot be known a priori. Thus,
different trust mechanisms should be investigated. Moreover,
self-certified names approach can hide content semantics, thus
making names less human friendly. Since trends show that users
prefer to find contents through search engine using keywords, non-
human-friendly names could be a barrier unless the content is
enriched with keywords. But, this problem does not concern M2M
applications. In fact, human-readable names may not be useful in
a context of just communicating machines.
Zhang, et al. Expires December 28, 2017 [Page 23]
Internet-Draft ICN based Architecture for IoT June 2017
o Flexibility: Further challenges arise for hierarchical naming
schema: referring to requirements on "constructible names" and
"on-demand publishing" [35][36]. TThe former entails that each
user is able to construct the name of a desired data item through
specific algorithms and that it is possible to retrieve
information also using partially specified names. The latter
refers the possibility to request a content that has not yet been
published in the past, thus triggering its creation.
o Scoping : From an application's point of view, scopes are used to
gather related data. From the network's perspective, instead,
scopes are used to mark where the content is available[65]. For
instance, nodes involved in caching coordination can vary
according to scope[66]. As a consequence, scoping allows to limit
packet request propagation, improving bandwidth and energy
resources usage, and control content dissemination thanks to
access control rules, different for each scope[64]. However,
relying on scoping for security/privacy has been shown to not work
all that well for IP, and is unlikely to work well for ICN either.
However, scoping may be useful to limit interest propagation,
provide a simple means to attain context-sensitive communication,
etc. Finally, perimeter- and channel-based access control is
often violated in current networks to enable over-the-wire updates
and cloud-based services, so scoping is unlikely to replace a need
for data-centric security in ICN.
o Confidentiality: As names can reveal information about the nature
of the communication or more importantly violate privacy,
mechanisms for name confidentiality should be available in the
ICN-IoT architecture. To grant confidentiality protection, some
approaches have been proposed in order to handle access control in
ICN naming scheme such as Attribute-Based Encryption [63] and
access control delegation scheme [64]. In the first solution, a
Trusted Third Party assigns a set of attributes to each network
entity. Then, a publisher (i) encrypts the data with a random
key; (II) generates the metadata for the decryption phase; (iii)
creates an access policy used to encrypt the random key; (iv)
appended the encrypted key to the content name. When the consumer
receives the packet, if its attributes satisfy the hidden policy
in the name, it can get the random key protected in the name and
decrypt the data. The second solution introduces a new trusted
network entity (i.e., Access Control Provide). In this case, when
a publisher generates a content, it also creates an access control
policy and send it to an Access Control Provider. This network
entity stores the access control policy, to which it associates a
Uniform Resource Identifier (URI). This URI is sent to the
publisher and included in the advertisements of the content.
Then, when a subscriber tries to access a protected content, it
Zhang, et al. Expires December 28, 2017 [Page 24]
Internet-Draft ICN based Architecture for IoT June 2017
can authenticate himself and request authorization for the
particular policy to the Access Control Provider through the URI.
6.2. Name Resolution
Inter-connecting numerous IoT entities, as well as establishing
reachability to them, requires a scalable name resolution system
considering several dynamic factors like mobility of end points,
service replication, in-network caching, failure or migration [57]
[69] [70] [91]. The objective is to achieve scalable name resolution
handling static and dynamic ICN entities with low complexity and
control overhead. In particular, the main requirements/challenges of
a name space (and the corresponding Name Resolution System where
necessary) are [50] [52]:
o Scalability: The first challenge faced by ICN-IoT name resolution
system is its scalability. Firstly, the approach has to support
billions of objects and devices that are connected to the
Internet, many of which are crossing administrative domain
boundaries. Second of all, in addition to objects/devices, the
name resolution system is also responsible for mapping IoT
services to their network addresses. Many of these services are
based upon contexts, hence dynamically changing, as pointed out in
[57]. As a result, the name resolution should be able to scale
gracefully to cover a large number of names/services with wide
variations (e.g., hierarchical names, flat names, names with
limited scope, etc.). Notice that, if hierarchical names are
used, scalability can be also supported by leveraging the inherent
aggregation capabilities of the hierarchy. Advanced techniques
such as hyperbolic routing [86] may offer further scalability and
efficiency.
o Deployability and inter-operability: Graceful deployability and
interoperability with existing platforms is a must to ensure a
naming schema to gain success on the market [7]. As a matter of
fact, besides the need to ensure coexistence between IP-centric
and ICN-IoT systems, it is required to make different ICN-IoT
realms, each one based on a different ICN architecture, to inter-
operate.
o Latency: For real-time or delay sensitive M2M application, the
name resolution should not affect the overall QoS. With reference
to this issue it becomes important to circumvent too centralized
resolution schema (whatever the naming style, i.e, hierarchical or
flat) by enforcing in-network cooperation among the different
entities of the ICN-IoT system, when possible [95]. In addition,
fast name lookup are necessary to ensure soft/hard real time
services [106][107][108]. This challenge is especially important
Zhang, et al. Expires December 28, 2017 [Page 25]
Internet-Draft ICN based Architecture for IoT June 2017
for applications with stringent latency requirements, such as
health monitoring, emergency handling and smart transportation
[109].
o Locality and network efficiency: During name resolution the named
entities closer to the consumer should be easily accessible
(subject to the application requirements). This requirement is
true in general because, whatever the network, if the edges are
able to satisfy the requests of their consumers, the load of the
core and content seek time decrease, and the overall system
scalability is improved. This facet gains further relevance in
those domains where an actuation on the environment has to be
executed, based on the feedbacks of the ICN-IoT system, such as in
robotics applications, smart grids, and industrial plants [97].
o Agility: Some data items could disappear while some other ones are
created so that the name resolution system should be able to
effectively take care of these dynamic conditions. In particular,
this challenge applies to very dynamic scenarios (e.g., VANETs) in
which data items can be tightly coupled to nodes that can appear
and disappear very frequently.
6.3. Security and Privacy
Security and privacy is crucial to all the IoT applications
applications including the use cases discussed in Section 2 and
subjected to the information context. To exemplify this, in one
recent demonstration,it was shown that passive tire pressure sensors
in cars could be hacked adversely affecting the automotive system
[74], while at the same time the information can be used by a public
traffic management system to improve road safety. The ICN paradigm
is information-centric as opposed to state-of-the-art host-centric
Internet. Besides aspects like naming, content retrieval and caching
this also has security implications. ICN advocates the model of
trust in content rather than a direct trust in network host mode.
This brings in the concept of Object Security which is contrary to
session-based security mechanisms such as TLS/DTLS prevalent in the
current host-centric Internet. Object Security is based on the idea
of securing information objects unlike session-based security
mechanisms which secure the communication channel between a pair of
nodes for unicast, (or among a set of nodes for multicast/broadcast).
This reinforces an inherent characteristic of ICN networks i.e. to
decouple senders and receivers. Even session based trust association
can be realized in ICN [83], that offers host-independence allowing
authentication and authorization to be separated from session
encryption, allowing multiple end points to meet specific service
objectives. In the context of IoT, the Object Security model has
several concrete advantages. Many IoT applications have data and
Zhang, et al. Expires December 28, 2017 [Page 26]
Internet-Draft ICN based Architecture for IoT June 2017
services are the main goal and specific communication between two
devices is secondary. Therefore, it makes more sense to secure IoT
objects instead of securing the session between communicating
endpoints. Though ICN includes data-centric security features the
mechanisms have to be generic enough to satisfy multiplicity of
policy requirements for different applications. Furthermore security
and privacy concerns have to be dealt in a scenario-specific manner
with respect to network function perspective spanning naming, name-
resolution, routing, caching, and ICN-APIs. The work by the JOSE WG
[80] provides solution approaches to address some of these concerns
for object security for constrained devices and should be considered
to see what can be applied to an ICN architecture. In general, we
feel that security and privacy protection in IoT systems should
mainly focus on the following aspects: confidentiality, integrity,
authentication and non-repudiation, and availability. Even though,
implementing security and privacy methods in IOT systems faces
different challenges than in other systems, like IP. Specifically,
below we discuss the challenges in the constrained and infrastructure
part of the network.
o In the resource-constrained nodes, energy limitation is the
biggest challenge. Moreover, it has to deliver its data over a
wireless link for a reasonable period of time on a coin cell
battery. As a result, traditional security/privacy measures are
impractical to be implemented in the constrained part. In this
case, one possible solution might be utilizing the physical
wireless signals as security measures [75] [55].
o In the infrastructure part, we have several new threats introduced
by ICN-IoT [85] particularly in architectures employing name
resolution service [119]. Below we list several possible attacks
to a name resolution service that is critical to ICN-IoT :
1. Each IoT device is given an ICN name. The name spoofing
attack is a masquerading threat, where a malicious user A
claims another user B's name and attempts to associate it with
A's own network address NA-A, by announcing the mapping (ID-B,
NA-A). The consequence of this attack is a denial of service
as it can cause traffic directed for B to be directed to A's
network address.
2. The stale mapping attack is a message manipulation attack
involving a malicious name resolution server. In this attack,
if a device moves and issues an update, the malicious name
resolution server can purposely ignore the update and claim it
still has the most recent mapping. Perhaps worse, a name
resolution server can selectively choose which (possibly
Zhang, et al. Expires December 28, 2017 [Page 27]
Internet-Draft ICN based Architecture for IoT June 2017
stale) mapping to give out during queries. The result is a
denial of service.
3. The third potential attack, false announcement attack, is an
information modification attack that results in illegitimate
resource consumption. User A, which is in network NA1, claims
its ID-A binds to a different network address, (ID-A, NA2).
Thus A can direct its traffic to network NA2, which causes
NA2's network resources to be consumed.
4. The collusion attack is an example of an information
modification attack in which a malicious user, its network and
the location where the mapping is stored collude with each
other. The objective behind the malicious collusion is to
allow for a fake mapping involving a false network address to
pass the verification and become stored in the storage place.
5. An intruder may insert fake/false sensor data into the
network. The consequence might be an increase in delay and
performance degradation for network services and applications.
o As far as the IoT application server is concerned, data privacy is
one of the biggest concerns. IoT data is collected and stored on
such servers, which usually run learning algorithms to extract
patterns from such data. In this case, it is important to adopt a
framework that enables privacy-preserving learning techniques.
The framework defines how data is collected, modified (to satisfy
the privacy requirement), and transmitted to application
developers.
6.4. Caching
In-network caching helps bring data closer to consumers, but its
usage differs in constrained and infrastructure part of the IoT
network.
Caching in ICN-IoT faces several challenges:
o An important challenge is to determine which nodes on the routing
path should cache the data. According to [52], caching the data
on a subset of nodes can achieve a better gain than caching on
every en-route routers. In particular, the authors propose a
"selective caching" scheme to locate those routers with better hit
probabilities to cache data. According to [53], selecting a
random router to cache data is as good as caching the content
everywhere. In [88], the authors suggest that edge caching
provides most of the benefits of in-network caching typically
discussed in NDN, with simpler deployment. However, it and other
Zhang, et al. Expires December 28, 2017 [Page 28]
Internet-Draft ICN based Architecture for IoT June 2017
papers consider workloads that are analogous to today's CDNs, not
the IoT applications considered here. Further work is likely
required to understand the appropriate caching approach for IoT
applications.
o Another challenge in ICN-IoT caching is what to cache for IoT
applications. In many IoT applications, customers often access a
stream of sensor data, and as a result, caching a particular
sensor data item for longer time may not be beneficial. In [90],
proposed a caching scheme that ensures that older instances of the
same sensor stream were first to be evicted from the cache when
needed. In [55], the authors suggest to cache IoT services on
intermediate routers, and in [57], the authors suggest to cache
control information such as pub/sub lists on intermediate nodes.
In addition, it is yet unclear what caching means in the context
of actuation in an IoT system. For example, it could mean caching
the result of a previous actuation request (using other ICN
mechanisms to suppress repeated actuation requests within a given
time period), or have little meaning at all if actuation uses
authenticated requests as in [89].
o Another challenge is that the efficiency of distributed caching
may be application dependent. When content popularity is
heterogeneous, some content is often requested repeatedly. In
that case, the network can benefit from caching. Another case
where caching would be beneficial is when devices with low duty
cycle are present in the network and when access to the cloud
infrastructure is limited. In [90], it is also shown that there
are benefits to caching in the network when edge links are lossy,
in particular if losses occur close to the content producer, as is
common in wireless IoT networks. However, using distributed
caching mechanisms in the network is not useful when each object
is only requested at most once, as a cache hit can only occur for
the second request and later. It may also be less beneficial to
have caches distributed throughout ICN nodes in cases when there
are overlays of distributed repositories, e.g., a cloud or a
Content Distribution Network (CDN), from which all clients can
retrieve the data. Using ICN to retrieve data from such services
may add some efficiency, but in case of dense occurrence of
overlay CDN servers the additional benefit of caching in ICN nodes
would be lower. Another example is when the name refers to an
object with variable content/state. For example, when the last
value for a sensor reading is requested or desired, the returned
data should change every time the sensor reading is updated. In
that case, ICN caching may increase the risk that cache
inconsistencies result in old data being returned.
Zhang, et al. Expires December 28, 2017 [Page 29]
Internet-Draft ICN based Architecture for IoT June 2017
6.5. Storage
Storage is useful for IoT systems both at longer and small time
scales.
Long terms storage can be distributed at vantage points including
both the edge and the main IoT service aggregation points such as in
the data centers, the difference being in the size of data,
processing intelligence and heterogeneity of information that has to
be dealt at the two points. The purpose of long terms storage at the
edge is to analyze, filter, aggregate and re-publish data for
consumption by either by the parent service components or directly by
the consumers. The aggregation service points, republish data to be
presented as part of the global pub/sub service to interested
consuming parties. Long term storage for IoT data also serves the
purpose of data backup and replication. Specifically, we face
several issues here. Firstly, we need to decide how many replicas we
should have for each stream of IoT data, and where we should store
these replicas. Given that many IoT applications consume data
locally, storage locations should be kept near to data sources as
well. Since IoT data are mostly appended to the end of a stream,
instead of being updated, managing multiple replicas becomes easier.
Secondly, we need to adopt a mechanism that can efficiently route
traffic to the nearest data replica. ICN provides several solutions
to this problem. For example, global name resolution service (GNRS)
can keep track of each replica's location [56].
Short-term in-network storage (here storage refers to temporary
buffer when an outgoing link is not available) helps improve
communication reliability, especially when network links are
unreliable, such as wireless links. ICN-IoT could adopt a
generalized storage-aware routing algorithm to support delay and
disruption tolerance in the routing layer. Each router employs in-
network storage that facilitates store vs. forward decisions in
response to varying link quality and disconnections [111]. These
decisions are based on both short-term and long-term path quality
metrics. In addition, packets along paths that become disconnected
are handled by a disruption tolerant networking (DTN) mode of the
protocol with delayed delivery and replication features. In
particular, each router maintains two types of topology information:
(i) An intra-partition graph is formed by collecting flooded link
state advertisements which carry fine-grained, time-sensitive
information about the intra-network links; (ii) A DTN graph is
maintained via epidemically disseminated link-state advertisements
which carry connection probabilities between all nodes in the
network. In-network storage faces the following challenges: (1) when
to store and how long to store the data, and (2) the next step after
the short-term storage. In [90] the authors also shows that it is
Zhang, et al. Expires December 28, 2017 [Page 30]
Internet-Draft ICN based Architecture for IoT June 2017
beneficial to store data even for shorter periods of time (and even
if only a single requester exist) if the network is lossy such that
retransmissions and error recovery can be done locally instead of
end-to-end.
6.6. Routing and Forwarding
ICN-IoT supports both device-to-device (D2D) communication and
device-to-infrastructure (D2I) communication. Some D2D
communications are within a single IoT domain, while others might
cross IoT domains involving data forwarding within the source IoT
domain, in the infrastructure network, and within the destination IoT
domain. D2I communications involve data forwarding within the source
IoT domain and in the infrastructure network. Data forwarding within
an IoT domain can adopt sensor network popular routing protocols such
as RPL [81], AODV[82], etc. The main challenge it faces is the
resource constraint of the IoT nodes. In order to address this
challenge, we could adopt a light-weight, much shorter ICN name for
each communicating party within an IoT domain (see Section 6.12 for
details). Before we leave the IoT domain, the gateway node will
translate the party's short ICN name to its original ICN name. Data
forwarding in the ICN infrastructure part can adopt either direct
name-based routing or indirect routing using a name resolution
service (NRS).
o In direct name-based routing, packets are forwarded by the name of
the data [91][61][71] or the name of the destination node [72].
Here, the main challenge is to keep the ICN router state required
to route/forward data low. This challenge becomes more serious
when a flat naming scheme is used due to the lack of aggregation
capabilities.
o In indirect routing, packets are forwarded based upon the locater
of the destination node, and the locater is obtained through the
name resolution service. In particular, the name-locater binding
can be done either before routing (i.e., static binding) or during
routing (i.e., dynamic binding). For static binding, the router
state is the same as that in traditional routers, and the main
challenge is the need to have fast name resolution, especially
when the IoT nodes are mobile. For dynamic binding, ICN routers
need to main a name-based routing table, hence the challenge of
keeping the state information low. At the same time, the need of
fast name resolution is also critical.
Zhang, et al. Expires December 28, 2017 [Page 31]
Internet-Draft ICN based Architecture for IoT June 2017
6.7. Mobility Management
Considering the diversity of IoT applications mobility ranges from
tracking sensor data from mobile human beings to large fleets of
diverse mobile elements such as drones, vehicles, trucks, trains
associated with a transport infrastructure. These mobility could be
over heterogeneous access infrastructure ranging from short range
802.15.4 to cellular radios. Further, handling information delivery
in ad hoc setting involving vehicles, road side units (RSU) and the
corresponding infrastructure based services offers more challenges.
ICN architectures has generally been shown to handle consumer and
producer mobility [59], and even suitability to V2V scenarios [60].
Networking tools to handle mobility varies with application
requirements, which varies from being tolerant to packet losses and
latency to those that are mission critical with stringent requirement
on both these QoS metrics.
Related to this, the challenge is to quantify the cost associated
with mobility management both in the control and forwarding plane, to
handle both static binding versus dynamic binding (dynamic binding
here refers to enabling seamless mobility) of named resources to its
location when either or both consumer and producer is mobile.
During a network transaction, either the data producer or the
consumer may move away and thus we need to handle the mobility to
avoid information loss. ICN may differentiate mobility of a data
consumer from that of a producer:
o When a consumer moves to a new location after sending out the
request for Data, the Data may traverse to the previous point of
attachment (PoA) but leaving copies of it through its previous
path, which can be retrieved by the consumer by retransmitting its
request, a technique used by direct routing approach. Indirect
routing approach doesn't differentiate between consumer and
producer mobility [91], as it only requires an update to the name
resolution system, which can update the routers to rebind the
named resource to its new location, while using late-binding to
route the packet from the previous PoA to the new one.
o If the data producer itself has moved, the challenge is to control
the control overhead while searching for a new data producer (or
for the same data producer in its new position) [58]. To this
end, flooding techniques could be used rediscover the producer, or
the direct routing techniques can be enhanced with late-binding
feature to enable seamless mobility [59].
Zhang, et al. Expires December 28, 2017 [Page 32]
Internet-Draft ICN based Architecture for IoT June 2017
6.8. Contextual Communication
Contextualization through metadata in ICN control or application
payload allows IoT applications to adapt to different environments.
This enables intelligent networks which are self-configurable and
enable intelligent networking among consumers and producers [55].
For example, let us look at the following smart transportation
scenario: "James walks on NYC streets and wants to find an empty cab
closest to his location." In this example, the context is the
relative locations of James and taxi drivers. A context service, as
an IoT middleware, processes the contextual information and bridges
the gap between raw sensor information and application requirements.
Alternatively, naming conventions could be used to allow applications
to request content in namespaces related to their local context
without requiring a specific service, such as /local/geo/
mgrs/4QFJ/123/678 to retrieve objects published in the 100m grid area
4QFJ 123 678 of the military grid reference system (MGRS). In both
cases, trust providers may emerge that can vouch for an application's
local knowledge.
However, extracting contextual information on a real-time basis is
very challenging:
o We need to have a fast context resolution service through which
the involved IoT devices can continuously update its contextual
information to the application (e.g., each taxi's location and
Jame's information in the above example). Or, in the namespace
driven approach, mechanisms for continuous nearest neighbor
queries in the namespace need to be developed.
o The difficulty of this challenge grows rapidly when the number of
devices involved in a context as well as the number of contexts
increases.
6.9. In-network Computing
In-network computing enables ICN routers to host heterogeneous
services catering to various network functions and applications
needs. Contextual services for IoT networks require in-network
computing, in which each sensor node or ICN router implements context
reasoning [55]. Another major purpose of in-network computing is to
filter and cleanse sensed data in IoT applications, that is critical
as the data is noisy as is [73].
Named Function Networking [113] describes an extension of the ICN
concept to named functions processed in the network, which could be
used to generate data flow processing applications well-suited to,
for example, time series data processing in IoT sensing applications.
Zhang, et al. Expires December 28, 2017 [Page 33]
Internet-Draft ICN based Architecture for IoT June 2017
Related to this, is the need to support efficient function naming.
Functions, input parameters, and the output result could be
encapsulated in the packet header, the packet body, or mixture of the
two (e.g. [31]). If functions are encapsulated in packet headers,
the naming scheme affects how a computation task is routed in the
network, which IoT devices are involved in the computation task (e.g.
[54]), and how a name is decomposed into smaller computation tasks
and deployed in the network for a better performance.
Another is challenge is related to support computing-aware routing.
Normal routing is for forwarding requests to the nearest source or
cache and return the data to the requester, whereas the routing for
in-network computation has a different purpose. If the computation
task is for aggregating sensed data, the routing strategy is to route
the data to achieve a better aggregation performance [51].
In-network computing also includes synchronization challenges. Some
computation tasks may need synchronizations between sub-tasks or IoT
devices, e.g. a device may not send data as soon as it is available
because waiting for data from the neighbours may lead to a better
aggregation result; some devices may choose to sleep to save energy
while waiting for the results from the neighbours; while aggregating
the computation results along the path, the intermediate IoT devices
may need to choose the results generated within a certain time
window.
6.10. Self-Orgnization
General IoT deployments involves heterogeneous IoT systems consisting
of embedded systems, aggregators and service gateways in a IoT
domain. To scale IoT deployments to large scale, scope-based self-
organization is required. This relates to IoT system middleware
functions [118] which include device bootstrapping and discovery,
assigning local/global names to device and/or content, security and
trust management functions towards device authentication and data
privacy. ICN based on-boarding protocols have been studied [96] and
has shown to offer significant savings compared to existing
approaches. These challenges span both the constrained devices as
well as interaction with the aggregators and the service gateways
which may have to contact external services like authentication
servers to on-board devices. A critical performance optimization
metric of these functions while operating at scale is to have low
control and data overhead in order to maximize energy efficiency.
Further, in the infrastructure part scalable name-based resolution
mechanisms, pub/sub services, storage and caching, and in-network
computing techniques should be studied to meet the scope-based
content dissemination needs of an ICN-IoT system.
Zhang, et al. Expires December 28, 2017 [Page 34]
Internet-Draft ICN based Architecture for IoT June 2017
6.11. Communications Reliability
ICN offers many ingredients for reliable communication such as multi-
home interest anycast over heterogeneous interfaces, caching, and
forwarding intelligence for multi-path routing leveraging state-
based forwarding in protocols like CCN/NDN. However these features
have not been analyzed from the QoS perspective when heterogeneous
traffic patterns are mixed in a router, in general QoS for ICN is an
open area of research [121]. In-network reliability comes at the
cost of a complex network layer; hence the research challenges here
is to build redundancy and reliability in the network layer to handle
a wide range of disruption scenarios such as congestion, short or
long term disconnection, or last mile wireless impairments. Also an
ICN network should allow features such as opportunistic store and
forward mechanism to be enabled only at certain points in the
network, as these mechanisms also entail overheads in the control and
forwarding plane overhead which will adversely affect application
throughput, Please see the discussion on in-network storage
(Section 6.5) for more details .
6.12. Resource Constraints and Heterogeneity
An IoT architecture should take into consideration resource
constraints of (often) embedded IoT nodes. Having globally unique
IDs is a key feature in ICN, which may consist of tens of bytes.
Each device would have a persistent and unique ID no matter when and
where it moves. It is also important for ICN-IoT to keep this
feature. However, always carrying the long ID in the packet header
may not be always feasible over a low-rate layer-2 protocol such as
802.15.4. To solve this issue, ICN can operate using lighter-weight
packet header and a much shorter locally unique ID (LUID in short).
In this way, we map a device's long global ID to its short LUID when
we reach the local area IoT domain. To cope with collisions that may
occur in this mapping process, we let each domain have its own global
ID to LUID mapping which is managed by a gateway deployed at the edge
of the domain. Different from NAT and other existing domain-based or
gateway-based solutions, ICN-IoT does not change the identity the
application uses. The applications, either on constrained IoT
devices or on the infrastructure nodes, still use the long global IDs
to identify each other, while the network performs translation which
is transparent to these applications. An IoT node carries its global
ID no matter where it moves, even when it is relocated to another
local IoT domain and is assigned with a new LUID. This ensures the
global reach-ability and mobility handling yet still considers
resource constraints of embedded devices.
Zhang, et al. Expires December 28, 2017 [Page 35]
Internet-Draft ICN based Architecture for IoT June 2017
In addition, the optimizations for other components of the ICN-IoT
system (described in earlier subsections) can lead to optimized
energy efficiency as well.
7. Differences from T2TRG
T2TRG [9] is a IoT research group under IRTF focusing on research
challenges of realizing IoT solutions considering IP as the narrow
waist. IP-IoT has been a research topic over a decade and with
active industry solutions, hence this group provides an venue to
study advanced issues related to IP-IoT security, provisioning,
configuration and inter-operability considering various heterogeneous
application environments. ICN-IoT is a recent research effort, where
the objective to exploit ICN feature of name based routing and
security, caching, multicasting, mobility etc in an end-to-end manner
to enable IoT services spanning both ad hoc, infrastructure and
hybrid scenarios. More detailed comparison of IP-IoT versus ICN-IoT
is given in Section 4.
8. Security Considerations
ICN puts security in the forefront of its design which ICN-IoT can
leverage to build applications with varying security requirements,
which has been discussed quite elaborately in this draft. This is an
informational draft and doesn't create new considerations beyond what
has been discussed.
9. Conclusions
This draft offers a comprehensive view of the benefits and design
challenges of using ICN to deliver IoT services, not only because of
its suitability for constraint networks but also towards ad hoc and
infrastructure environments. The draft begins by motivating the need
for ICN-IoT by considering popular IoT scenarios and then delves into
understanding the IoT requirements from application and networking
perspective. We then discuss why current approach of application
layer unified IoT solutions based on IP falls short of meeting these
requirements, and how ICN architecture is a more suitable towards
this. We then elaborate on the design challenges in realizing an
ICN-IoT architecture at scale and one that offers reliability,
security, energy efficiency, mobility, self-organization among others
to accommodate varying IoT service needs.
10. Acknowledgements
We thank all the contributors, reviewers and the valuable comments
offered by the chairs to improve this draft.
Zhang, et al. Expires December 28, 2017 [Page 36]
Internet-Draft ICN based Architecture for IoT June 2017
11. Informative References
[1] Cisco System Inc., CISCO., "Cisco visual networking index:
Global mobile data traffic forecast update.", 2016-2021.
[2] Shafig, M., Ji, L., Liu, A., Pang, J., and J. Wang, "A
first look at cellular machine-to-machine traffic: large
scale measurement and characterization.", Proceedings of
the ACM Sigmetrics , 2012.
[3] The European Telecommunications Standards Institute,
ETSI., "http://www.etsi.org/.", 1988.
[4] Global Intiative for M2M Standardization, oneM2M.,
"http://www.onem2m.org/.", 2012.
[5] Constrained RESTful Environments, CoRE.,
"https://datatracker.ietf.org/wg/core/charter/.", 2013.
[6] Ghodsi, A., Shenker, S., Koponen, T., Singla, A.,
Raghavan, B., and J. Wilcox, "Information-Centric
Networking: Seeing the Forest of the Trees.", Hot Topics
in Networking , 2011.
[7] Dong, L., Zhang, Y., and D. Raychaudhuri, "Enhance Content
Broadcast Efficiency in Routers with Integrated Caching.",
Proceedings of the IEEE Symposium on Computers and
Communications (ISCC) , 2011.
[8] NSF FIA project, MobilityFirst.,
"http://mobilityfirst.winlab.rutgers.edu/", 2010.
[9] Thing-to-Thing Research Group, T2TRG.,
"https://datatracker.ietf.org/rg/t2trg/about/", 2017.
[10] OPC Foundation, OPC., "https://opcfoundation.org/", 2017.
[11] Kim, B., Lee, S., Lee, Y., Hwang, I., and Y. Rhee,
"Mobiiscape: Middleware Support for Scalable Mobility
Pattern Monitoring of Moving Objects in a Large-Scale
City.", Journal of Systems and Software, Elsevier, 2011.
[12] Dietrich, D., Bruckne, D., Zucker, G., and P. Palensky,
"Communication and Computation in Buildings: A Short
Introduction and Overview", IEEE Transactions on
Industrial Electronics, 2010.
Zhang, et al. Expires December 28, 2017 [Page 37]
Internet-Draft ICN based Architecture for IoT June 2017
[13] Keith, K., Falco, F., and K. Scarfone, "Guide to
Industrial Control Systems (ICS) Security", NIST,
Technical Report 800-82 Revision 1, 2013.
[14] Darianian, M. and Martin. Michael, "Smart home mobile
RFID-based Internet-of-Things systems and services.",
IEEE, ICACTE, 2008.
[15] Zhu, Q., Wang, R., Chen, Q., Chen, Y., and W. Qin, "IOT
Gateway: Bridging Wireless Sensor Networks into Internet
of Things", IEEE/IFIP, EUC, 2010.
[16] Biswas, T., Chakrabort, A., Ravindran, R., Zhang, X., and
G. Wang, "Contextualized information-centric home
network", ACM, Sigcomm, 2013.
[17] Huang, R., Zhang, J., Hu, Y., and J. Yang, "Smart Campus:
The Developing Trends of Digital Campus", 2012.
[18] Yan, Y., Qian, Y., Hu, Y., and J. Yang, "A Survey on Smart
Grid Communication Infrastructures: Motivations,
Requirements and Challenges", IEEE Communications Survey
and Tutorials, 2013.
[19] Chai, W., Katsaros, K., Strobbe, M., and P. Romano,
"Enabling Smart Grid Applications with ICN", ICN Sigcomm,
2015.
[20] Katsaros, K., Chai, W., Wang, N., and G. Pavlou,
"Information-centric Networking for Machine-to-Machine
Data Delivery: A Case Study in Smart Grid Applications",
IEEE Network, 2014.
[21] Mael, A., Maheo, Y., and F. Raimbault, "CoAP over BP for a
delay-tolerant internet of things", Future Internet of
Things and Cloud (FiCloud), IEEE, 2015.
[22] Patrice, R. and H. Rivano, "Tests Scenario on DTN for IOT
III Urbanet collaboration", Dissertation, INRIA, 2015.
[23] Kevin, F., "Comparing Information-Centric and Delay-
Tolerant Networking", Local Computer Networks (LCN), 2012
IEEE 37th Conference on. IEEE, 2012..
[24] Miao, Y. and Y. Bu, "Research on the Architecture and Key
Technology of Internet of Things (loT) Applied on Smart
Grid", IEEE, ICAEE, 2010.
Zhang, et al. Expires December 28, 2017 [Page 38]
Internet-Draft ICN based Architecture for IoT June 2017
[25] Castro, M. and A. Jara, "An analysis of M2M platforms:
challenges and opportunities for the Internet of Things",
IMIS, 2012.
[26] Gubbi, J., Buyya, R., and S. Marusic, "Internet of Things
(IoT): A vision, architectural elements, and future
directions", Future Generation Computer Systems, 2013.
[27] Vandikas, K. and V. Tsiatsis, "Performance Evaluation of
an IoT Platform. In Next Generation Mobile Apps, Services
and Technologies(NGMAST)", Next Generation Mobile Apps,
Services and Technologies (NGMAST), 2014.
[28] Zhang, Y., Yu, R., Nekovee, M., Liu, Y., Xie, S., and S.
Gjessing, "Cognitive Machine-to-Machine Communications:
Visions and Potentials for the Smart Grid", IEEE, Network,
2012.
[29] Zhou, H., Liu, B., and D. Wang, "Design and Research of
Urban Intelligent Transportation System Based on the
Internet of Things", Springer Link, 2012.
[30] Alessandrelli, D., Petracca, M., and P. Pagano, "T-Res:
enabling reconfigurable in-network processing in IoT-based
WSNs.", International Conference on Distributed Computing
in Sensor Systems (DCOSS) , 2013.
[31] Kovatsch, M., Mayer, S., and B. Ostermaier, "Moving
application logic from the firmware to the Cloud: towards
the thin server architecture for the internet of things.",
in Proc. 6th Int. Conf. on Innovative Mobile and Internet
Services in Ubiquitous Computing (IMIS) , 2012.
[32] Zhang, M., Yu, T., and G. Zhai, "Smart Transport System
Based on the Internet of Things", Applied Mechanics and
Materials, 2012.
[33] Zhang, A., Yu, R., Nekovee, M., and S. Xie, "The Internet
of Things for Ambient Assisted Living", IEEE, ITNG, 2010.
[34] Savola, R., Abie, H., and M. Sihvonen, "Towards metrics-
driven adaptive security management in E-health IoT
applications.", ACM, BodyNets, 2012.
[35] Jacobson, V., Smetters, D., Plass, M., Stewart, P.,
Thornton, J., and R. Braynard, "VoCCN: Voice-over Content-
Centric Networks", ACM, ReArch, 2009.
Zhang, et al. Expires December 28, 2017 [Page 39]
Internet-Draft ICN based Architecture for IoT June 2017
[36] Piro, G., Cianci, I., Grieco, L., Boggia, G., and P.
Camarda, "Information Centric Services in Smart Cities",
ACM, Journal of Systems and Software, 2014.
[37] Gaur, A., Scotney, B., Parr, G., and S. McClean, "Smart
City Architecture and its Applications Based on IoT -
Smart City Architecture and its Applications Based on
IoT", Procedia Computer Science, Volume 52, 2015, Pages
1089-1094.
[38] Herrera-Quintero, L., Banse, K., Vega-Alfonso, J., and A.
Venegas-Sanchez, "Smart ITS sensor for the transportation
planning using the IoT and Bigdata approaches to produce
ITS cloud services", 8th Euro American Conference on
Telematics and Information Systems (EATIS), Cartagena,
2016, pp. 1-7.
[39] Melis, A., Pardini, M., Sartori, L., and F. Callegati,
"Public Transportation, IoT, Trust and Urban Habits",
Internet Science: Third International Conference, INSCI
2016, Florence, Italy, September 12-14, 2016, Proceedings.
[40] Tonneau, A., Mitton, N., and J. Vandaele, "A Survey on
(mobile) Wireless Sensor Network Experimentation
Testbeds", 2014 IEEE International Conference on
Distributed Computing in Sensor Systems, Marina Del Rey,
CA, 2014, pp. 263-268.
[41] Zhilin, Y., "Mobile phone location determination and its
impact on intelligent transportation systems", IEEE
Transactions on Intelligent Transportation Systems, vol.
1, no. 1, pp. 55-64, Mar 2000.
[42] Papadimitratos, P., La Fortelle, A., Evenssen, K.,
Brignolo, R., and S. Cosenza, "Vehicular communication
systems: Enabling technologies, applications, and future
outlook on intelligent transportation", IEEE
Communications Magazine, vol. 47, no. 11, pp. 84-95,
November 2009.
[43] Zhang, Yu., Afanasyev, A., Burke, J., and L. Zhang, "A
survey of mobility support in named data networking",
Computer Communications Workshops (INFOCOM WKSHPS), 2016
IEEE Conference on. IEEE, 2016.
Zhang, et al. Expires December 28, 2017 [Page 40]
Internet-Draft ICN based Architecture for IoT June 2017
[44] Xylomenos, G., Ververidis, C., Siris, V., and N. Fotiou et
al, "A survey of information-centric networking research",
IEEE Communications Surveys and Tutorials, Volume: 16,
Issue: 2, Second Quarter 2014 .
[45] Mavromoustakis, C., Mastorakis, G., and J. Batalla,
"Internet of Things (IoT) in 5G Mobile Technologies",
ISBN,3319309137,Springer.
[46] Firner, S., Medhekar, S., and Y. Zhang, "PIP Tags:
Hardware Design and Power Optimization", in Proceedings of
HotEmNets, 2008.
[47] Masek, P., Masek, J., Frantik, P., and R. Fujdiak, "A
Harmonized Perspective on Transportation Management in
Smart Cities: The Novel IoT-Driven Environment for Road
Traffic Modeling", Sensors, Volume 16, Issue 11, 2016.
[48] Abreu, D., Velasquez, K., Curado, M., and E. Monteiro, "A
resilient Internet of Things architecture for smart
cities", Annals of Telecommunications, Volume 72, Issue 1,
Pages 19-30, 2017.
[49] Ravindran, R., Biswas, T., Zhang, X., Chakrabort, A., and
G. Wang, "Information-centric Networking based Homenet",
IEEE/IFIP, 2013.
[50] Dannewitz, C., D' Ambrosio, M., and V. Vercellone,
"Hierarchical DHT-based name resolution for information-
centric networks", 2013.
[51] Fasoloy, E., Rossiy, M., and M. Zorziy, "In-network
Aggregation Techniques for Wireless Sensor Networks: A
Survey", IEEE Wireless Communications, 2007.
[52] Chai, W., He, D., and I. Psaras, "Cache "less for more" in
information-centric networks", ACM, IFIP, 2012.
[53] Eum, S., Nakauchi, K., Murata, M., Shoji, Yozo., and N.
Nishinaga, "Catt: potential based routing with content
caching for icn", IEEE Communication Magazine, 2012.
[54] Drira, W. and F. Filali, "Catt: An NDN Query Mechanism for
Efficient V2X Data Collection", Eleventh Annual IEEE
International Conference on Sensing, Communication, and
Networking Workshops (SECON Workshops), 2014.
Zhang, et al. Expires December 28, 2017 [Page 41]
Internet-Draft ICN based Architecture for IoT June 2017
[55] Eum, S., Shvartzshnaider, Y., Francisco, J., Martini, R.,
and D. Raychaudhuri, "Enabling internet-of-things services
in the mobilityfirst future internet architecture", IEEE,
WoWMoM, 2012.
[56] Raychaudhuri, D., Nagaraj, K., and A. Venkatramani,
"Mobilityfirst: a robust and trustworthy mobility-centric
architecture for the future internet.", ACM SIGMOBILE
Mobile Computing and Communications Review 16.3 (2012):
2-13.
[57] Sun, Y., Qiao, X., Cheng, B., and J. Chen, "A low-delay,
lightweight publish/subscribe architecture for delay-
sensitive IOT services", IEEE, ICWS, 2013.
[58] Azgin, A., Ravindran, R., and GQ. Wang, "Mobility study
for Named Data Networking in wireless access networks",
IEEE, ICC, 2014.
[59] Azgin, A., Ravindran, R., Chakraborti, A., and GQ. Wang,
"Seamless Producer Mobility as a Service in Information
Centric Networks", ACM ICN Sigcomm, IC5G Workshop, 2016.
[60] Wang, L., Wakikawa, R., Kuntz, R., and R. Vuyyuru, "Data
Naming in Vehicle-to-Vehicle Communications", IEEE,
Infocm, Nomen Workshop, 2012.
[61] Baccelli, E., Mehlis, C., Hahm, O., Schmidt, T., and M.
Wahlisch, "Information Centric Networking in the
IoT:Experiments with NDN in the Wild", ACM, ICN Siggcomm,
2014.
[62] Simona, C. and M. Mongiello, "Pushing the role of
information in ICN", Telecommunications (ICT), 2016 23rd
International Conference on. IEEE, 2016..
[63] Li, B., Huang, D., Wang, Z., and Y. Zhu, "Attribute-based
Access Control for ICN Naming Scheme", IEEE Transactions
on Dependable and Secure Computing, vol.PP, no.99,
pp.1-1..
[64] Polyzos, G. and N. Fotiou, "Building a reliable Internet
of Things using Information-Centric Networking", Journal
of Reliable Intelligent Environments, vol.1, no.1, 2015..
Zhang, et al. Expires December 28, 2017 [Page 42]
Internet-Draft ICN based Architecture for IoT June 2017
[65] Pandurang, K., Xu, W., Trappe, W., and Y. Zhang, "Temporal
privacy in wireless sensor networks: Theory and practice",
ACM Transactions on Sensor Networks (TOSN) 5, no. 4
(2009): 28..
[66] Trossen, D., Sarela, M., and K. Sollins, "Arguments for an
information-centric internetworking architecture.", ACM
SIGCOMM Computer Communication Review 40.2 (2010): 26-33.
[67] Zhang, G., Li, Y., and T. Lin, "Caching in information
centric networking: A survey.", Computer Networks 57.16
(2013): 3128-3141.
[68] Gronbaek, I., "Architecture for the Internet of Things
(IoT): API and interconnect", IEEE, SENSORCOMM, 2008.
[69] Tian, Y., Liu, Y., Yan, Z., Wu, S., and H. Li, "RNS-A
Public Resource Name Service Platform for the Internet of
Things", IEEE, GreenCom, 2012.
[70] Roussos, G. and P. Chartier, "Scalable id/locator
resolution for the iot", IEEE, iThings,CPSCom, 2011.
[71] Amadeo, M. and C. Campolo, "Potential of information-
centric wireless sensor and actuator networking", IEEE,
ComManTel, 2013.
[72] Nelson, S., Bhanage, G., and D. Raychaudhuri, "GSTAR:
generalized storage-aware routing for mobilityfirst in the
future mobile internet", ACM, MobiArch, 2011.
[73] Trappe, W., Zhang, Y., and B. Nath, "MIAMI: methods and
infrastructure for the assurance of measurement
information", ACM, DMSN, 2005.
[74] Rouf, I., Mustafa, H., Taylor, T., Oh, S., Xu, W.,
Gruteser, M., Trappe, W., and I. Seskar, "Security and
privacy vulnerabilities of in-car wireless networks: A
tire pressure monitoring system case study", USENIX, 2010.
[75] Liu, R. and W. Trappe, "Securing Wireless Communications
at the Physical Layer", Springer, 2010.
[76] Xiao, L., Greenstein, L., Mandayam, N., and W. Trappe,
"Using the physical layer for wireless authentication in
time-variant channels", IEEE Transactions on Wireless
Communications, 2008.
Zhang, et al. Expires December 28, 2017 [Page 43]
Internet-Draft ICN based Architecture for IoT June 2017
[77] Sun, S., Lannom, L., and B. Boesch, "Handle system
overview", IETF, RFC3650, 2003.
[78] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<http://www.rfc-editor.org/info/rfc7252>.
[79] Fielding, R., Ed. and J. Reschke, Ed., "Hypertext Transfer
Protocol (HTTP/1.1): Message Syntax and Routing",
RFC 7230, DOI 10.17487/RFC7230, June 2014,
<http://www.rfc-editor.org/info/rfc7230>.
[80] Barnes, R., "Use Cases and Requirements for JSON Object
Signing and Encryption (JOSE)", RFC 7165,
DOI 10.17487/RFC7165, April 2014,
<http://www.rfc-editor.org/info/rfc7165>.
[81] Winter, T., Ed., Thubert, P., Ed., Brandt, A., Hui, J.,
Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur,
JP., and R. Alexander, "RPL: IPv6 Routing Protocol for
Low-Power and Lossy Networks", RFC 6550,
DOI 10.17487/RFC6550, March 2012,
<http://www.rfc-editor.org/info/rfc6550>.
[82] Perkins, C., Belding-Royer, E., and S. Das, "Ad hoc On-
Demand Distance Vector (AODV) Routing", RFC 3561,
DOI 10.17487/RFC3561, July 2003,
<http://www.rfc-editor.org/info/rfc3561>.
[83] marc.mosko@parc.com, m., Uzun, E., and C. Wood, "CCNx Key
Exchange Protocol Version 1.0", draft-wood-icnrg-
ccnxkeyexchange-01 (work in progress), October 2016.
[84] Sun, S., "Hypertext Transfer Protocol (HTTP/1.1): Message
Syntax and Routing", 2014.
[85] Liu, X., Trappe, W., and Y. Zhang, "Secure Name Resolution
for Identifier-to-Locator Mappings in the Global
Internet", IEEE, ICCCN, 2013.
[86] Boguna, M., Fragkiskos, P., and K. Dmitri, "Sustaining the
internet with hyperbolic mapping", Nature Communications,
2010.
[87] Shang, W., "Securing building management systems using
named data networking", IEEE Network 2014.
Zhang, et al. Expires December 28, 2017 [Page 44]
Internet-Draft ICN based Architecture for IoT June 2017
[88] Fayazbakhsh, S. and et. et al, "Less pain, most of the
gain: Incrementally deployable icn", ACM, Siggcomm, 2013.
[89] Burke, J. and et. et al, "Securing instrumented
environments over Content-Centric Networking: the case of
lighting control", INFOCOM, Computer Communications
Workshop, 2013.
[90] Rao, A., Schelen, O., and A. Lindgren, "Performance
Implications for IoT over Information Centric Networks",
Performance Implications for IoT over Information Centric
Networks, ACM CHANTS 2016.
[91] Li, S., Zhang, Y., Dipankar, R., and R. Ravindran, "A
comparative study of MobilityFirst and NDN based ICN-IoT
architectures", IEEE, QShine, 2014.
[92] Chen, J., Li, S., Yu, H., Zhang, Y., and R. Ravindran,
"Exploiting icn for realizing service-oriented
communication in iot", IEEE, Communication Magazine, 2016.
[93] Quevedo, J., Corujo, D., and R. Aguiar, "A Case for ICN
usage in IoT environments", Global Communications
Conference GLOBECOM, IEEE, Dec 2014, Pages 2770-2775.
[94] Lindgren, A., Ben Abdesslem, F., Ahlgren, B., and O.
Schelen, "Design Choices for the IoT in Information-
Centric Networks", IEEE Annual Consumer Communications and
Networking Conference (CCNC) 2016.
[95] Grieco, L., Alaya, M., and K. Drira, "Architecting
Information Centric ETSI-M2M systems", IEEE, Pervasive and
Computer Communications Workshop (PERCOM), 2014.
[96] Compagno, A., Conti, M., and R. Dorms, "OnboardICNg: a
Secure Protocol for On-boarding IoT Devices in ICN", ICN,
Sigcomm, 2016.
[97] Grieco, L., Rizzo, A., Colucci, R., Sicari, S., Piro, G.,
Di Paola, D., and G. Boggia, "IoT-aided robotics
applications: technological implications, target domains
and open issues", Elsevier Computer Communications, Volume
54, 1 December, 2014.
[98] InterDigital, WhitePaper., "Standardized M2M Software
Development Platform", 2011.
Zhang, et al. Expires December 28, 2017 [Page 45]
Internet-Draft ICN based Architecture for IoT June 2017
[99] Boswarthick, D., "M2M Communications: A Systems Approach",
2012.
[100] Swetina, J., Lu, G., Jacobs, P., Ennesser, F., and J.
Song, "Toward a standardized common M2M service layer
platform: Introduction to oneM2M", IEEE Wireless
Communications, Volume 21, Number 3, June 2014.
[101] Wang, L., Wang, Z., and R. Yang, "Intelligent Multiagent
Control System for Energy and Comfort Management in Smart
and Sustainable Buildings", IEEE Transactions on Smart
Grid, vol. 3, no. 2, pp. 605-617, June 2012..
[102] Lawrence, T., Boudreau, M., and L. Helsen, "Ten questions
concerning integrating smart buildings into the smart
grid, Building and Environment", Building and Environment,
Volume 108, 1 November 2016, Pages 273-283..
[103] Hassan, A. and D. Kim, "Named data networking-based smart
home", ICT Express 2.3 (2016): 130-134..
[104] Burke, J., Horn, A., and A. Marianantoni, "Authenticated
lighting control using named data networking", UCLA, NDN
Technical Report NDN-0011 (2012)..
[105] Afanasyev, A., "Packet fragmentation in ndn: Why ndn uses
hop-by-hop fragmentation.", UCLA, NDN Technical Report
NDN-0032 (2015)..
[106] Quan, Wei., Xu, C., Guan, J., Zhang, H., and L. Grieco,
"Scalable Name Lookup with Adaptive Prefix Bloom Filter
for Named Data Networking", IEEE Communications Letters,
2014.
[107] Wang, Yi., Pan, T., Mi, Z., Dai, H., Guo, X., Zhang, T.,
Liu, B., and Q. Dong, "NameFilter: Achieving fast name
lookup with low memory cost via applying two-stage Bloom
filters", INFOCOM, 2013.
[108] So, W., Narayanan, A., Oran, D., and Y. Wang, "Toward fast
NDN software forwarding lookup engine based on Hash
tables", ACM, ANCS, 2012.
[109] Amadeo, M., Campolo, C., Iera, A., and A. Molinaro, "Named
data networking for IoT: An architectural perspective",
IEEE, EuCNC, 2014.
Zhang, et al. Expires December 28, 2017 [Page 46]
Internet-Draft ICN based Architecture for IoT June 2017
[110] Amadeo, M., Campolo, C., Iera, A., and A. Molinaro,
"Information centric networking in iot scenarios: The case
of a smart home", IEEE ICC, June 2015.
[111] Somani, N., Chanda, A., Nelson, S., and D. Raychaudhuri,
"Storage- Aware Routing for Robust and Efficient Services
in the Future Mobile Internet", Proceedings of ICC
FutureNet V, 2012.
[112] Blefari Melazzi, N., Detti, A., Arumaithurai, M., and K.
Ramakrishnan, "Internames: A name-to-name principle for
the future internet", QShine, August 2014.
[113] Sifalakis, M., Kohler, B., Christopher, C., and C.
Tschudin, "An information centric network for computing
the distribution of computations", ACM, ICN Sigcomm, 2014.
[114] Lu, R., Lin, X., Zhu, H., and X. Shen, "SPARK: a new
VANET-based smart parking scheme for large parking lots",
INFOCOM, 2009.
[115] Wang, H. and W. He, "A reservation-based smart parking
system", The First International Workshop on Cyber-
Physical Networking Systems, 2011.
[116] Qian, L., "Constructing Smart Campus Based on the Cloud
Computing and the Internet of Things", Computer Science
2011.
[117] Project, BonVoyage., "European Unions - Horizon 2020,
http://bonvoyage2020.eu/", 2016.
[118] Li, S., Zhang, Y., Raychaudhuri, D., Ravindran, R., Zheng,
Q., Wang, GQ., and L. Dong, "IoT Middleware over
Information-Centric Network", Global Communications
Conference (GLOBECOM) ICN Workshop, 2015.
[119] Li, S., Chen, J., Yu, H., Zhang, Y., Raychaudhuri, D.,
Ravindran, R., Gao, H., Dong, L., Wang, GQ., and H. Liu,
"MF-IoT: A MobilityFirst-Based Internet of Things
Architecture with Global Reachability and Communication
Diversity", IEEE International Conference on Internet-of-
Things Design and Implementation (IoTDI), 2016.
[120] Adhatarao, S., Chen, J., Arumaithurai, M., and X. Fu,
"Comparison of naming schema in ICN", IEEE LANMAN, June ,
2016.
Zhang, et al. Expires December 28, 2017 [Page 47]
Internet-Draft ICN based Architecture for IoT June 2017
[121] Campolo, C., Corujo, D., Iera, A., and R. Aguiar,
"Information-centric Networking for Internet-of-things:
Challenges and Opportunities", IEEE Networks, Jan , 2015.
Authors' Addresses
Prof.Yanyong Zhang
WINLAB, Rutgers University
671, U.S 1
North Brunswick, NJ 08902
USA
Email: yyzhang@winlab.rutgers.edu
Prof. Dipankar Raychadhuri
WINLAB, Rutgers University
671, U.S 1
North Brunswick, NJ 08902
USA
Email: ray@winlab.rutgers.edu
Prof. Luigi Alfredo Grieco
Politecnico di Bari (DEI)
Via Orabona 4
Bari 70125
Italy
Email: alfredo.grieco@poliba.it
Prof. Emmanuel Baccelli
INRIA
Room 148, Takustrasse 9
Berlin 14195
France
Email: Emmanuel.Baccelli@inria.fr
Zhang, et al. Expires December 28, 2017 [Page 48]
Internet-Draft ICN based Architecture for IoT June 2017
Jeff Burke
UCLA REMAP
102 East Melnitz Hall
Los Angeles, CA 90095
USA
Email: jburke@ucla.edu
Ravishankar Ravindran
Huawei Technologies
2330 Central Expressway
Santa Clara, CA 95050
USA
Email: ravi.ravindran@huawei.com
Guoqiang Wang
Huawei Technologies
2330 Central Expressway
Santa Clara, CA 95050
USA
Email: gq.wang@huawei.com
Anders Lindgren
RISE SICS
Box 1263
Kista SE-164 29
SE
Email: anders.lindgren@ri.se
Bengt Ahlgren
RISE SICS
Box 1263
Kista, CA SE-164 29
SE
Email: bengt.ahlgren@ri.se
Zhang, et al. Expires December 28, 2017 [Page 49]
Internet-Draft ICN based Architecture for IoT June 2017
Olov Schelen
Lulea University of Technology
Lulea SE-971 87
SE
Email: lov.schelen@ltu.se
Zhang, et al. Expires December 28, 2017 [Page 50]