Internet DRAFT - draft-irtf-icnrg-icniot
draft-irtf-icnrg-icniot
ICN Research Group R. Ravindran, Ed.
Internet-Draft Huawei Technologies
Intended status: Informational Y. Zhang
Expires: November 3, 2019 WINLAB, Rutgers University
L. Grieco
Politecnico di Bari (DEI)
A. Lindgren
RISE SICS
J. Burke
UCLA REMAP
B. Ahlgren
RISE SICS
A. Azgin
Huawei Technologies
May 2, 2019
Design Considerations for Applying ICN to IoT
draft-irtf-icnrg-icniot-03
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 to enable a horizontally unified IoT
architecture. The objective of such an architecture is to make
resource objects securely 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 today's
Internet and the mostly information-centric nature of the IoT domain.
To address this mismatch, the common set of protocols and network
services offered by an information-centric networking (ICN)
architecture can be leveraged to realize an ICN-based IoT (or ICN-
IoT) architecture that can take advantage of the salient features of
ICN such as naming, security, mobility, compute and efficient content
and service delivery support offered by it.
In this draft, we summarize the general IoT demands, and ICN features
that support these requirements, and then discuss the challenges to
realize an ICN-based IoT framework. Beyond this, the goal of this
draft is not to offer any specific ICN-IoT architectural proposal.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Motivating ICN for IoT . . . . . . . . . . . . . . . . . . . 4
2.1. Advantages of using ICN for IoT . . . . . . . . . . . . . 5
2.2. Service Scenarios . . . . . . . . . . . . . . . . . . . . 6
3. IoT Architectural Requirements . . . . . . . . . . . . . . . 11
3.1. Naming . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2. Security and Privacy . . . . . . . . . . . . . . . . . . 12
3.3. Scalability . . . . . . . . . . . . . . . . . . . . . . . 13
3.4. Resource Constraints . . . . . . . . . . . . . . . . . . 13
3.5. Traffic Characteristics . . . . . . . . . . . . . . . . . 14
3.6. Contextual Communication . . . . . . . . . . . . . . . . 14
3.7. Handling Mobility . . . . . . . . . . . . . . . . . . . . 15
3.8. Storage and Caching . . . . . . . . . . . . . . . . . . . 15
3.9. Communication Reliability . . . . . . . . . . . . . . . . 16
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3.10. Self-Organization . . . . . . . . . . . . . . . . . . . . 16
3.11. Ad hoc and Infrastructure Mode . . . . . . . . . . . . . 17
3.12. IoT Platform Management . . . . . . . . . . . . . . . . . 17
4. State of the Art . . . . . . . . . . . . . . . . . . . . . . 18
4.1. Silo IoT Architecture . . . . . . . . . . . . . . . . . . 18
4.2. Application-Layer Unified IoT Solutions . . . . . . . . . 19
4.2.1. Weaknesses of the Application-Layer Approach . . . . 20
4.2.2. Relation to Delay Tolerant Networking (DTN)
architecture and its suitability for IoT . . . . . . 22
5. ICN Design Considerations for IoT . . . . . . . . . . . . . . 22
5.1. Naming Devices, Data, and Services . . . . . . . . . . . 22
5.2. Name Resolution . . . . . . . . . . . . . . . . . . . . . 26
5.3. Security and Privacy . . . . . . . . . . . . . . . . . . 27
5.4. Caching . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.5. Storage . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.6. Routing and Forwarding . . . . . . . . . . . . . . . . . 32
5.7. Mobility Management . . . . . . . . . . . . . . . . . . . 33
5.8. Contextual Communication . . . . . . . . . . . . . . . . 34
5.9. In-network Computing . . . . . . . . . . . . . . . . . . 35
5.10. Self-Organization . . . . . . . . . . . . . . . . . . . . 36
5.11. Communications Reliability . . . . . . . . . . . . . . . 36
5.12. Resource Constraints and Heterogeneity . . . . . . . . . 37
6. Differences from T2TRG . . . . . . . . . . . . . . . . . . . 37
7. Security Considerations . . . . . . . . . . . . . . . . . . . 38
8. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 38
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 38
10. Informative References . . . . . . . . . . . . . . . . . . . 38
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 50
1. Introduction
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 these systems towards a unified IoT
architecture, in which a large number of objects hosted by non-
interoperable protocol domains can connect to the Internet to enable
secure interactions with a diverse set of applications across
administrative domain. Note that, here, 'unified' is used to imply a
scenario, where all the IoT applications, services, and network
functions use a common set of transport APIs and network protocols to
interact with each other. Typical IoT applications involve sensing,
actuation, processing, and secure content distribution, each of which
can occur at different timescales and hierarchical levels that depend
on the application requirements. To adapt to different scenarios,
IoT systems need to adopt an architecture that can provide (i) pull/
push- and publish/subscribe-based application abstractions, (ii) a
common naming framework, (iii) support for payload encryption and
signature schemes, and (iv) open APIs as opposed to proprietary APIs
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that are common in today's systems. These requirements can pose
great challenges for the underlying network and systems. To name a
few, the IoT system needs to support 50-100 Billion networked objects
[1], many of which are mobile. These objects are expected to have
extremely heterogeneous means of connecting to the Internet, often
with severe resource constraints. Interactions between the
applications and the objects are often real-time and dynamic,
requiring strong security and privacy protections. In addition, the
IoT system design should offer efficient data exchange schemes that
take into consideration the application behavior. For instance, in
many IoT applications, data consumers usually need the data sensed
from the environment without any reference to the subset of sensors
that can provide the requested information.
In short, adopting a general IoT perspective, we first motivate the
discussion of ICN for IoT by focusing on well known scenarios. We
then discuss the IoT requirements that are generally applicable to
many of these well known IoT scenarios. Next we discuss how the
current application-layer unified IoT architectures are inefficient
to meet the above requirements, and how the key ICN features can make
it a better candidate to realize a unified IoT framework. Finally,
adopting an ICN perspective, we address the main IoT design
challenges and requirements posed towards an ICN-based-IoT system
design.
2. Motivating ICN for IoT
ICN offers many features that include name-based networking, content
object security, in-network caching, compute, and storage, active
mobility support, context-aware networking (see Section 3.6), and
support for ad hoc networking. Within the context of an IP based IoT
design (IP-IoT), all of these features offered by the ICN have to be
realized in an application-specific way demonstrating the compelling
nature of ICN to design IoT systems.
To be specific, the features offered by ICN can be used to enable a
distributed and intelligent data distribution platform that supports
heterogeneous IoT services requiring minimal configuration for device
bootstrapping, carrying simpler protocols to aid self-organizing
among the IoT elements, and offering natural support for compute and
caching logic at strategic points in the network. We outline general
advantages of using an ICN-based IoT system design and discuss these
from the perspective of the several service scenarios that are
difficult to realize over IP today, and whose characteristics
arguably match the features offered by ICN.
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2.1. Advantages of using ICN for IoT
A key concept of ICN is the ability to name data and services
independently from its original location (at which it is stored) and
this simplifies caching, and enables decoupling of consumers and
producers. Therefore, 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 the general benefits that the ICN can provide to
an IoT network.
o Naming of Devices, Data and Services: The heterogeneity of the
deployed network equipment and offered services by an IoT network
leads to a large variety of data, services, and devices. While
using a traditional host-centric architecture, only devices or
their network interfaces are named at the network level, leaving
the task to name data and services to the application layer. This
can cause different applications to use different naming schemes,
and, as a result, no consistent mapping from application layer
names to network names may exist. In many applications common to
an IoT network, data and services represent the main objective,
and ICN provides an intuitive way to name them in a way that can
be utilized at the network layer as well. Communication with a
specific device is often secondary, but when needed, the same ICN
naming mechanisms can also be used. In such case, network
distributes content and provides a service at the same time,
instead of only sending data between two named devices. In this
context, content and services can be provided by several devices,
or a 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 object security model to
secure data in the network. This concept is based on the idea of
securing information objects, unlike the 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 the keys established at the application level. All of
this means that the actual transmission of data does not have to
be secured, since the same security mechanisms protect the data
starting with its generation until its consumption, regardless of
its mobility/location (i.e., whether it is in transit over a
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communication channel or stored in an intermediate cache). In an
ICN network, each individual object within a stream of immutable
objects can potentially be retrieved from a cache in a different
location. However, having a trust relationship with each of these
different caches is not realistic. Through name-data integrity,
ICN automatically guarantees data integrity to the requesting
client 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, and if the device constraints are
severe enough that it is not able to perform the required
cryptographic operations for object security, then 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, as the cryptographic hash of
a public key also enables it to be self-certifying, in which case,
authenticating the resource object does not require an external
authority [27][28].
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, because of the resource constraints imposed on the
devices. Furthermore, wireless bandwidth and power supply can be
limited for multiple devices sharing a communication channel, and
especially for small mobile devices powered by batteries. In this
case, avoiding unnecessary transmissions to retrieve and
distribute IoT data from/to multiple places becomes important,
hence processing and storing such content in the network can save
wireless bandwidth and battery power. Moreover, as for other
types of networks, IoT-driven applications requiring shorter
delays can also benefit from local caches and services to reduce
the delays between content request and delivery.
o Sender/Receiver Decoupling: IoT devices may be mobile and face
intermittent network connectivity issues. When a 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.
2.2. Service Scenarios
o Smart Mobility: Smart end-user devices and machine-to-machine
(M2M) connections are undergoing a significant growth. By 2021,
there will be more than 10 billion mobile devices and connections,
including smartphones, tablets, wearables, and vehicles [1]. The
involved fields for these devices range from medicine and health
care to fitness, from clothing to environmental monitoring [42].
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In particular, one of the most affected domains is transportation
and the so-called Intelligent Transport Systems (ITS) [44]. The
objective of ITS is to provide a multi-modal transportation system
that embraces public and private municipal, regional, national,
and trans-national vehicles and fleets. This extremely
heterogeneous ecosystem of transportation means is made available
to the users through advanced services that can fulfill the
usability requirements, while pursuing system level objectives,
and which include: (i) the reduction of CO2 footprint, (ii) the
real-time delivery of specific goods, (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 [121]. Within this
context, IoT technologies can play a pivotal role. For instance,
they enable advanced design paradigms (e.g., Mobility as a Service
(MaaS) [41]) with significant implications on the system
architecture [50] or lead to novel approaches to traffic modeling
[49]. As a consequence, smart mobility support can be a
significant use case scenario for ICN-IoT, where the important ICN
features that corroborate mobility support are listed as follows:
* ICN is unique in that it supports both infrastructure- and ad
hoc-based communications. This makes it suitable to support
communication in vehicular ad hoc networks (VANETS) [19][126],
along with supporting communication with the infrastructure
components like the road side units to serve the needs of
several smart mobility applications. ICN's name based network
APIs along with its caching feature enable the system to
simultaneously operate over multiple heterogeneous radio
interfaces using broadcast, unicast or anycast communication
modes.
* ICN offers location independence of content, which allows one
to manage consumer mobility in a simpler way than it is with
IP. Furthermore, different from Mobile IP, which needs
'triangular routing' to locate moving hosts, ICN envisions a
mobile consumer to only re-issue content requests or use
network based late-binding functions once the mobile entity
handoffs from one attachment point to another [45];
* In ICN, since the content is not bound to a specific location,
it can be cached anywhere in the network, thereby adding
redundancy to the system. In doing so, if a producer loses
connectivity while it is moving, a request for its content can
be resolved to an intermediate node en-route to or routed
towards a nearby off-path caching node [45];
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* The name based request-response communication paradigm
considered for ICN decouples publish/subscribe operations in
time and space. Therefore, the involved entities (i.e.,
publishers and subscribers) do not need to be aware of each
other or be connected at the same time [46];
* The use of an in-network Name Resolution Service (NRS) design
allows to identify the current location of or associated with a
content name in the network, thanks to its network function,
which is responsible for updating the location information of a
named entity [58].
From a technological perspective, we can list the open challenges
as follows: (i) support for ad hoc communications and
interoperability across different IoT technologies, (ii) namespace
design that is able to harmonize different ITS standards, (iii)
scalable data-sharing model(s) across real-time (and non real-
time) traffic sources, (iv) design of travel-centric services
based on ICN-IoT, (v) seamless support to mobility, and (vi)
content authentication and cryptography.
o Smart Building: Buildings are gaining smart capabilities that
allow for enhanced comfort, increased safety and security, and
improved energy efficiency [105]. In particular, smart buildings
are no longer simple consumer(s) (for energy), but can also be
prosumers with on-site energy generation systems. These systems
can improve a building's usability towards (i) smart heating,
ventilation, and air conditioning (HVAC), (ii) smart lightings,
(iii) plug loads, and (iv) smart windows. We can list the main
requirements for these sub-systems as follows [105]: (i) context
awareness, (ii) support for resource-constrained devices, (iii)
interoperability across heterogeneous technologies, and (iv)
security and privacy protection. The ICN paradigm can ease the
fulfillment of these requirements for one simple reason: smart
building services are typically information centric by design. To
be specific, any time an autonomic management loop is established
within a smart building to control a set of physical variables of
interest, the information exchanged between the entities (e.g.,
users, sensors, actuators, and controllers) do not immediately
translate to specific nodes within the building, but can be
provided by multiple sensors or gateways. The relevance of ICN in
a smart building setting is recognized in the literature as well
with reference to the several frameworks deployed in various
environments. For instance, in [63], nodes are distributed to
different rooms, floors, and buildings of a campus university, and
their energy consumption and individual behaviors are monitored.
A smart home application is investigated in [107] by evaluating
the retrieval delay and packet loss statistics for data.
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Moreover, [108] designed and tested lighting control over NDN in a
theater setting. In short, within the smart building context, we
can list the ICN-specific challenges as follows: (i) design of a
scalable namespace for uniquely identifying the information of
interest and also host services for actuation, (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 Grid systems are increasingly transforming into
cyber-physical systems [18] with the goals of maximum automation
towards efficiency and minimal human intervention. The system is
a very complex one comprising of power distribution grids, end
user applications (e.g. Electric Vehicle (EV) charging systems
and appliances), smart monitoring systems (spanning the end users
and the power grids), heterogeneous energy producing sources
(including prosumers), and load distribution/balancing systems.
Current smart grid systems are managed using the centralized
Supervisory Control and Data Acquisition (SCADA) frameworks with
highly restrictive unidirectional communication support [20].
These systems typically have the following requirements: (i)
improved flexibility in distributing energy from the feeder,
through real-time reconfiguration of multiple monitoring devices
(e.g., phasor measurement units or PMUs) and management operations
requiring an efficient data delivery infrastructure; (ii) a large
scale data delivery infrastructure capable of supporting latency
sensitive applications and inter-connecting heterogeneous end user
devices that produce, monitor, and/or consume; (iii) resiliency,
which is critical to the operation and protection of the grid;
(iv) security, to protect mission critical grid applications from
network intrusions; and (v) understanding machine-to-machine
traffic patterns for optimal placement of storage and computing to
maximize efficiency. Smart grid systems can benefit from ICN in
the following ways [21][22]:
* ICN approach of naming content rather than hosts can ensure
that the data generated by one subsystem would be useful for
multiple entities. Furthermore, naming content can enable the
many-to-many communications model, which is very inefficient in
the case of host-centric architectures.
* ICN features such as in-network computing, storage, and caching
enable better use of network resources and can benefit diverse
application scenarios that vary from latency tolerant
applications with low data rates (e.g., smart grid and energy
pricing) to applications observing high data rates with
stringent delay/disruption requirements (e.g., synchrophasor
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measurements). Also, it is typical for smart grid systems to
have applications that consume the same data at different
rates, in which case in-network caching and computing can be of
significant use.
* Host-centric networking exposes a mission critical
infrastructure like the smart grid infrastructure to intrusion
and Denial of Service (DOS) attacks, which are directly related
to exposing the IP addresses of critical applications and
subsystems. Naming contents, services, or devices, on the
other hand, de-couples them from the location, thereby reducing
the exposure to being targeted based on a geographical context.
* ICN's name based networking offers the potential for self-
configuration during both the bootstrapping phase and the
regular operation of the grid, allowing scalable operation with
self-recovery during faults or maintenance tasks in the system.
o Smart Industrial Automation: In a smart and connected industrial
environment, equipment with sensors generate large volumes of data
during normal operation. This range from the highly time-critical
data for real-time control of production processes, to the less
time-critical data that is collected by a central cloud
environment for control room monitoring, and to pure log data
without latency requirements that is mainly kept for a posteriori
analysis. Industrial wireless networks are difficult environments
with many potential interferences occurring at the same time even
as hard reliability and real-time requirements are placed by many
applications. This means that the available network capacity is
not always high, so it becomes likely for traffic with less
stringent delay requirements to experience congestion. One such
example is, when errors occur in the production process, a mobile
workforce is expected to investigate the problem on-site and they
will need high resolution data from the faulty machine(s) as well
as other process data from the other parts of the plant. The
mobile workforces typically perform their diagnostics or
maintenance locally, and they rely on the information acquired
from the production system both for safety purposes and to solve
any other or related issues in the plant. Furthermore, they rely
on both the historical data flow (to pinpoint the root cause of
the problems) and the current data flow (to assess the present
state of the equipment under control). High resolution
measurements are typically generated close to the mobile
workforce, while the historic data has to be retrieved from the
historian servers. In this scenario, multiple workers involved in
the process typically access the same data, possibly with a slight
time-shift. The network thus needs to support mobile users to get
access to the data flows in a way suitable for their physical
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location and the task requirements. Introducing ICN functionality
into the system can lead to several benefits that 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 the OPC
Foundation [10] can be easily mapped to the CCN/NDN name space.
* ICN provides the possibility to get the newest data without
knowing the location of the caching nodes or whether a
particular piece of data is available locally or in a central
repository. ICN also gives the possibility to get either the
local high-resolution data or the remote low-resolution data
(as there is no need to store all the data centrally, which may
not even be possible due to the large data volume). However,
it may require well-defined naming conventions or routing
policies that can route interests to the right location.
* ICN can reduce the network utilization 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 can be inherently supported, without the need to
maintain a connection state.
* Use of ICN can help with removing tedious configurations in
clients, since that would be provided by the infrastructure.
* ICN allows the sharing of large volumes of data between users
that are in physical proximity, without introducing additional
traffic on the backbone network.
* Caching of data in ICN means avoiding additional accesses to a
distributed redundant database in the central infrastructure
with consistency requirements.
3. IoT Architectural Requirements
Future IoT platforms have to support secure interactions among a
large number of heterogeneous, constrained, static or mobile
resources across organization/domain boundaries. As a result, it
naturally poses stringent requirements in every aspect of the system
design. Below, we outline the important requirements that a future
IoT platform has to address.
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3.1. Naming
An important step towards realizing a unified IoT architecture is the
ability to assign names that are unique to (i) each device, (ii) each
data item generated by each of these devices, and (iii) each service
hosted in a device or a group of devices, towards a common objective.
We can assume the naming to have the following requirements. First,
names need to be persistent against dynamic features that are common
to IoT systems, such as lifetime, mobility, or migration. Second,
names that are derived from the keys need to be self-certifying, for
both device-centric and content-centric communications. For device-
centric communications, binding between device names and the device
must be secure. For content-centric communications, binding between
the names and the content has to be secure. Third, names usually
serve multiple purposes, i.e., routing, security (self-certifying),
or human-readability. For IoT applications, the choice of flat
versus human readable names needs to be made considering the
application and network requirements such as privacy and network
level scalability, resource constrained networking requirements, and
the name space explosion that may occur because of the complex
relationship between name hierarchies [124] that may confound
application logic.
One of the challenges in naming is to ensure the trustworthiness of
the names. A general approach would require a name certificate
service. 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 end.
3.2. Security and Privacy
A variety of security and privacy concerns exist in IoT systems as
they are infrastructure typically owned by private entities. For
example, the unified IoT architecture makes physical objects
accessible to applications across organizations and domains.
Furthermore, it often integrates with a critical infrastructure and
an industrial system with life safety implications, bringing with it
significant security challenges and regulatory requirements [13], as
will be discussed in Section 5.3. 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: (i) privacy of the data producer/consumer that is
directly related to each individual vertical domain such as health,
electricity, etc., (ii) privacy of data content, and (iii) privacy of
contextual information such as time and location of data transmission
[68].
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3.3. Scalability
Cisco [1] predicts that there will be around 50 Billion IoT devices
on the Internet by 2020 (and these devices include sensors, Radio-
Frequency IDentification (RFID) tags, and actuators), and a unified
IoT platform needs to name every entity within, which includes these
devices, and data and services accessed by/through them. Scalability
has to be addressed at multiple levels of the IoT architecture
including naming and name resolution, routing and forwarding, and
security. Mobility adds further challenges 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.
Additionally, scalability is also affected by the specific IoT system
features such as IoT resource object count, state and rate of
information update 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 being the most resource-constrained and type 3
being the most resource-rich [47], where the following are considered
as the most typical resource types: 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 [48]. Flexible
techniques to collect the relevant information are required, and
uploading every single produced data to a central server is not
desirable.
Computing constraints limit the type and amount of processing these
devices can perform. As a result, more complex processing needs to
be done at the cloud servers or at opportunistic points, for instance
at the network edge, hence it is important to balance local
computation versus communication costs.
Storage constraints of the IoT devices limit the amount of data that
can be stored on these devices. This constraint means that unused
sensor data may need to be discarded or stored in an aggregated
compact form from time to time.
Bandwidth constraints of the IoT devices limit the amount of
communication, hence, impose similar restrictions on the system
architecture as the power constraints, i.e., one cannot afford to
collect every single sensor data generated by the device and/or use
complex control plane protocols. It is also worth mentioning that,
this constraint also has implications on maintaining idle chatter in
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the background to maintain connectivity or other volatile service
state.
User interface constraints refer to whether the device is itself
capable of directly interacting with a user. Possible mechanisms
include, via a display and keypad ,LED indicators or requires network
connectivity, either locally or globally, to enable human
interaction.
The above discussed resources constraints also impact application
performance with respect to the end-to-end latency towards sensing or
executing control loop based actuation functions.
3.5. Traffic Characteristics
IoT traffic can be broadly classified into local area traffic and
wide area traffic. Local area traffic takes place among the nearby
devices. For example, neighboring cars may work together to detect
potential hazards on the highway, or sensors deployed in a room may
collaborate to determine how to adjust the heating level in the room.
These local area communications often involve data aggregation and
filtering, carry real time constraints, and require fast discovery
and association (for the device, data, or service). At the same
time, IoT platform has to also support wide area communications. For
example, in the case of Intelligent Transportation Systems, realtime
video and sensor feeds from the concerned IoT entities can be used
towards re-routing operations based on system state, traffic load,
availability of freights, weather forecasts, and so on. Wide area
communications also require efficient discovery and resolution
services for data/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 volumes for some
applications such as [2], which means that we have to optimize the
bandwidth use and energy consumption in both directions.
Furthermore, IoT traffic demonstrates certain periodicity and
burstiness [2]. As a result, traffic characteristics of the IoT
services have to be properly accounted for during system planning and
provisioning.
3.6. Contextual Communication
Many IoT applications rely on dynamic contexts in the IoT system to
initiate, maintain, and terminate communication among the 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
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administrative group, or the devices may be present near the same
proximity. For example, cars traveling on the highway may form a
"cluster" based upon their temporal physical proximity to one another
as well as the detection of the same event. These temporary groups
are referred to as contexts. There are two types of contexts: (i)
long-term quasi-static contexts (i.e., contexts based on social
contexts as well as stationary physical locations, such as sensors
inside a car or a building) and (ii) short-term dynamic contexts
(i.e., contexts based on temporary proximity). Between these two
classes, short-term contexts are more challenging to support as they
require fast formation, update, lookup and association. Therefore,
in this draft, our focus will be on the more challenging latter
class. In general, IoT applications need to support not only the
interactions among the members of a context, but also the
interactions across contexts.
3.7. Handling Mobility
There are several degrees of mobility corresponding to different IoT
scenarios, ranging from static (as in fixed assets) to highly dynamic
(as in vehicle-to-vehicle environments). Furthermore, mobility in an
IoT architecture can refer to: (i) data producer mobility, (ii) data
consumer mobility, (iii) IoT network mobility (e.g., a body-area
network in motion as a person is walking), and/or (iv) disconnection
between a source/destination pair (e.g., due to unreliable wireless
links). The requirement on mobility support is to deliver IoT data
earlier than an application's acceptable delay constraints for all
the above considered cases, and if necessary, to negotiate different
connectivity or security constraints specific to each mobile context.
More detailed discussions on this issue are presented in Section 5.7.
3.8. Storage and Caching
Storage and caching plays a very significant role depending on the
type of IoT ecosystem, which is also a function subjected to privacy
and security guidelines. Caching is usually needed to increase data
availability in the network and for reliability purposes, which is
especially useful for wireless access scenarios and with devices
experiencing intermittent connectivity to the infrastructure network.
Storage is more important for an IoT system, as data is typically
stored for long term analysis. Specifically, data is stored at
strategic locations in the network to reduce control and computation
related overheads. Depending on the application requirements,
caching will strictly be driven by application level policies,
considering also the privacy requirements. If, for certain type of
IoT data, pervasive caching is allowed, then intermediate nodes may
not need to always forward a content request to its original creator.
Instead, receiving a cached copy would be sufficient for the IoT
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applications. This approach may greatly reduce the content access
latencies.
Considering the hierarchical nature of the IoT systems, ICN
architectures can enable a flexible, heterogeneous, and potentially
fault-tolerant approach to storage and caching, thereby providing
contextual persistence at multiple levels. Within the context of IoT
and considering the application requirements, while offering
resolution to replicated stored copies, ICN can efficiently support
tradeoffs between content security/privacy and regulations.
3.9. Communication Reliability
IoT applications can be broadly categorized into mission critical and
non-mission critical applications. 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 low error rates during information transfer. To
support the objective of reliable communications, it is essential for
an underlying system to have the following capabilities: (i) seamless
mobility support under normal operating conditions, (i) efficient
routing in the presence of intermittent connection loss, (iii) QoS
aware routing, (iv) support for redundancy at every system level
(i.e., device, service, network, storage, etc.), and (v) 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.
3.10. Self-Organization
Considering the scalability and efficiency requirements, the unified
IoT architecture should be able to self-organize to meet various
application requirements, e.g., context-driven discovery, which
refers to the capability to quickly discover heterogeneous and
relevant local/global devices/data/services based on the context. A
publish-subscribe service, or a private trust-driven community
grouping or clustering scheme, can be used to support this discovery
process. For the former case, the publish-subscribe service must be
implemented in a way to efficiently support seamless mobility using
techniques such as in-network caching and name-based routing. For
the latter case, the IoT architecture should be able to discover the
private community groups/clusters in a resource efficient way.
Another aspect of self-organization is the decoupling of the sensing
infrastructure from the applications. In a typical IoT deployment,
various applications run on top of a vast number of IoT devices. It
is not an easy task to upgrade the firmware of the IoT devices, and
it is also not practical to re-program these IoT devices to
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accommodate every change in these applications. Therefore,
infrastructure and application specific logics need to be decoupled,
and a common interface is required (i) to dynamically configure the
interactions among the IoT devices and (ii) to easily modify these
application logics on top of the sensing/actuating infrastructure
[32] [33].
3.11. Ad hoc and Infrastructure Mode
Depending on the presence of a communication infrastructure, an IoT
system can operate in an ad-hoc mode or an infrastructure mode, (or
use a combination of two). For example, a vehicle may determine to
report its location and status information to a server periodically
through a cellular connection, or, a group of vehicles may form an
ad-hoc network that collectively detects the road conditions around
them. In cases, where an infrastructure is sparse, one of the
participating nodes may choose to become a temporary gateway node.
The unified IoT architecture needs to design a common protocol that
serves both of these modes. Such a protocol should address the
challenges that may arise in them: (i) scalability and low latency
for the infrastructure mode and (ii) 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.
3.12. IoT Platform Management
Service, control and data planes for an IoT platform will be governed
by its own management infrastructure, which includes (i) distributed
and centralized middleware, (ii) discovery, naming, self-configuring,
and analytic functions, and (iii) information dissemination, to
achieve the specific IoT system objectives [27][28][29]. Towards
this, new IoT management mechanisms and service metrics need to be
developed to measure the success of an IoT deployment. Considering
an IoT system's defining characteristics (such as the potential to
carry a large number of IoT devices, the objective to save power,
mobility, and ad hoc communications), autonomous self-management
schemes become very critical. Furthermore, considering its
hierarchical information processing deployment model, the platform
needs to orchestrate computational tasks based on the involved
sensors and the available computation resources, which may change
over time. An efficient resource discovery and management protocol
is required to facilitate this process. The trade-off between
information transmission and processing is another challenge.
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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, and
towards a unified IoT architecture, in which the existing silo IoT
systems, as well as the new systems that are rapidly deployed, can
coexist. Here, a unified architecture refers to the case, where all
the application and network functions use common APIs and network
protocols to interact with each other. This will make their data and
services accessible to general Internet applications (which is the
case for ETSI-M2M [3] and oneM2M [4] standards). In such a unified
architecture, resources can be accessed over the Internet and shared
across the physical boundaries of an enterprise. However, current
approaches to achieve this objective are mostly based on service
overlays over the Internet, whose inherent inefficiencies caused by
the use of the IP protocol [58] hinders the architecture from
satisfying the IoT requirements outlined earlier, particularly in
terms of scalability, security, mobility, and self-organization,
which are discussed in more details in Section 4.2.
4.1. Silo IoT Architecture
[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
include the devices, applications, gateway and server nodes. Many
IoT devices have limited power and computing resources, unable to
directly run the normal IP-based access network protocols (i.e.,
Ethernet, WiFi, 3G/LTE, etc.). Consequently, these devices operate
over non-IP protocols to connect to the Internet servers using an IoT
gateway. Through the IoT server, applications can subscribe to the
data collected by these devices, or interact with them.
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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 a device-level abstraction,
rather than an information driven one, leading to a fragmented
information and protocol space that requires application level
solutions to achieve interoperability.
4.2. Application-Layer Unified IoT Solutions
The current approach to create a unified IoT architecture is to make
IoT gateways and servers adopt standard APIs. IoT devices connect to
the Internet through standard APIs and IoT applications subscribe/
receive data through standard control/data APIs. Built 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] and
oneM2M[4]. IoT service providers can then use such frameworks to
build common IOT gateways and servers for their customers. In
addition, IETF's Constrained RESTful Environments (CORE) working
group [5] is developing a set of protocols like Constrained
Application Protocol (CoAP) [81], that is a lightweight protocol
modeled after HTTP [82] and adapted specifically for the 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 application level protocols for M2M
communications, as well as for IoT. For example, oneM2M (which is
one of the leading standards for a unified M2M architecture) has
protocol bindings to both HTTP and CoAP for its primitives. Figure 2
shows the architecture adopted in this approach.
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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 outlined in
Section 3, and the reasoning for that is explained as follows:
o Naming: In current application-layer IoT systems, naming scheme is
a host-centric one, that is, the name of a given resource/service
is linked to the device that can provide it. In turn, device
names are coupled to the IP addresses, which are not persistent in
mobile scenarios. On the other side, in IoT systems, the same
service/resource can be offered by different devices.
o Security and Trust: In IP, security and trust model is based on
the session established between two hosts. Session-based
protocols rely on the exchange of several messages to establish a
secure session. Use of such protocols in constrained IoT devices
can have serious consequences in terms of energy efficiency,
because transmission and reception of messages are often more
costly than the cryptographic operations. This problem may be
amplified with the number of nodes that a constrained device has
to interact with, due to increase in both the computation cost and
the per-session key state managed by the constrained device.
Furthermore, because of focusing on securing communication
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channels rather than managing the data that needs to be secured
directly, current trust management schemes can be considered to be
relatively weak.
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. Furthermore, the
orthogonal 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, to a gateway or to the
IoT server. Resource constraints of the IoT devices, especially
in power and bandwidth, can seriously limit the performance of
this approach.
o Traffic Characteristics: In this approach, applications are
written in a host-centric manner suitable for point-to-point
communication. IoT, however, requires multicast support that is
challenging for the application-layer based IoT systems today,
which have only limited deployment in the current Internet.
o Contextual Communications: The application-layer based IoT
approach may not react to dynamic contextual changes in a timely
fashion. The main reason is that the context lists are usually
kept at the IoT server and they cannot help with efficient routing
of requests 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 that is enabled via
name-based routing or lookups.
o Self-Organization: As the application-layer approach is bound to
IP semantics, it is considered as topology-based, and, as a
result, it cannot sufficiently satisfy the requirement on self-
organization. In addition to the topological self-organization,
IoT also requires self-organization at the data and service levels
[101], which are also not supported by this approach.
o Ad hoc and Infrastructure Mode: As mentioned above, the overlay-
based approach lacks self-organization and adaptation to dynamic
topology changes, and, therefore, it cannot provide efficient
support for the ad hoc mode of communication.
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4.2.2. Relation to Delay Tolerant Networking (DTN) architecture and its
suitability for IoT
In [23][24], delay-tolerant networking (DTN) has been considered to
support future IoT architectures. DTN was initially developed to
support information delivery in the presence of network disruptions
and disconnections, but it has also 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 (or endpoint IDs), each of which usually corresponds
to a host or a service, and is mainly a way to transport data, while
ICN generalizes this notion to named data, hosts and services and
offers ways to address IoT application [25] challenges through
features such as (information) naming, discovery, request and
dissemination. However, endpoint IDs can also be used to 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 a transport would still require other components
from an ICN architecture such as naming conventions. However, since
the exact transport is not a major focus of the issues addressed by
this draft, most of the provided discussions are applicable to a
generic ICN architecture.
5. 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 involved to support large scale IoT deployments with diverse
application requirements.
Though ICN integrates (i) abstractions at the content, service, and
host levels, (ii) name-based routing, and (iii) computation, caching,
and storage as part of the network infrastructure, IoT requires
special considerations given the heterogeneity of devices and
interfaces such as for constrained networking [63][123][125], data
processing, and content distribution models to meet specific
application requirements, which we identify as challenges in this
section.
5.1. Naming Devices, Data, and Services
Even though the ICN approach of named data and services (i.e., device
independent naming) is typically desirable when retrieving IoT data,
such data-centric naming may also pose certain challenges.
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o Naming of devices: Naming devices [127] [128]can be useful in an
IoT system. For example, actuators may require clients to act on
a specific node of the deployed network (to switch it on or off),
or it could be necessary to access a particular device for
administration purposes. This can only be achieved through a
specific name that uniquely identifies the targeted network
entity. Moreover, a persistent name allows a device to change its
attachment point without loosing its identity. A friendly way to
address a device is to use a contextual hierarchical name, which
is of the same type as one that is used for data objects. Also
note that, through disabling of caching and request aggregation on
names associated with a device, it is possible to ensure that the
requests targeting that device always reach the device.
o Size of data/service name: Content names can have variable
lengths. 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), their lengths can be quite long in
relation to the size of the content itself. In particular, for
specific application, content name size can even exceed the Data
size. This can be the case for IoT networks with sensed values
that usually consist only of a few bytes (i.e., data can be as
small as a short integer in case of temperature values, or one-
byte in case of control messages corresponding to an actuator
state as on/off). Moreover, a name that is too long is likely to
trigger fragmentation at the link layer, and create additional
problems (i.e., several transmissions, increased delay and
security issues). Various approaches have been investigated to
handle fragmentation and reassembly issues associated with ICN
packets. For instance, the work in [109] proposes to perform hop-
by-hop operations, i.e., 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, thereby 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 received content is the one
requested. This is only possible in contexts, where the requested
object already exists, and where there is a directory service to
look up names or the names are learned through a manifest service.
This approach is suitable for systems with large sized data
objects, where it is important to verify the content.
o Hierarchical names: The use of hierarchical names, as is the case
with the CCN and NDN architectures, makes it easier to create
names a priori based on a predefined naming convention. It also
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provides a convenient way to use the same naming scheme for device
names. However, since names are not self-certifying, this will
require other mechanisms for verification of object integrity. If
routing is also performed on the hierarchical names, the system
will lose some of its location independence and caching will
mostly be done on the path towards the publisher.
o Semantic and metadata-based content name: A semantic-based naming
approach can allow for successful retrieval of name through a set
of keywords (for example, 'noise level at position X'), even if a
perfect matching of the name is not available [65]. Moreover,
enriching contents with metadata allows to better describe the
names and to establish association between similar ones. However,
this mechanism requires more advanced functionality to match such
metadata in the data object to the semantics of the name (e.g.,
comparing the position information of an object with the position
information of the requested name). The need for such
(potentially) computationally heavy tasks at the intermediate
nodes in the network may be considered to understand the trade-
offs between application and network performance. [64] proposes a
metadata-based naming approach to support ICN-IoT networking with
service function identification and processing of IoT data at some
vantage points in the local IoT network, before returning the
processed result to the consumers.
o Naming of services: Similar to naming of devices or data, services
can also be referred to with a unique identifier, provided by a
specific device or by an authorized entity (i.e., someone assigned
by a central authority as the service provider). It can also be a
service provided by anyone meeting certain metadata conditions.
Example of services may include content retrieval, which takes a
content name or description as an input and returns the value of
that content, and actuation, which takes an actuation command as
an input and possibly returns a status code.
o Trust: Names can be used to verify the authenticity and the
integrity of the data. Multiple approaches can be used to provide
security functionalities through names. For instance,
hierarchical, schematized, Web-of-Trust models can enable public
key verification, whereas self-certifying names can enable in-
network integrity checks of the name-key or name-content binding
without the need of a Public Key Infrastructure (PKI) or another
third party to establish whether the key is trustworthy or not.
This can be realized either directly or indirectly. In the former
case, the hash of the content is bound to the name. In the latter
case, first, the hash of the content is signed with the secret key
of the publisher, and then the public key of the publisher and the
signed hash are bound to the name [46]. The hash algorithm can be
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applied to the already existing contents and where there is a
directory service or manifest to look up names. In case of yet-
to-be-published but on-demand generated contents, the hash cannot
be known a-priori, hence different trust mechanisms should be
investigated. Furthermore, self-certified naming approach can
hide the content semantics, thus making names less human friendly.
Since trends show that users prefer to find contents through a
search engine using keywords, having non-human-friendly names can
be a barrier, unless the content is enriched with keywords.
However, this problem does not concern M2M applications, as human-
readable names may not be useful in the context of just
communicating machines.
o Flexibility: Further challenges may arise for the hierarchical
naming schema, associated with the requirements on "constructible
names" and "on-demand publishing" [37][38]. The 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 using partially specified names. The latter
refers to the possibility of requesting a not-yet-published
content, thereby triggering its creation.
o Scoping: From an application's point of view, scopes are used to
gather related data, whereas from the network's perspective,
scopes are used to mark where the content is available [68]. For
instance, nodes that are involved with caching coordination can
vary according to scope [69]. As a result, scoping can be used
(i) to limit propagation of requests, thereby improving resource
usage efficiency by reducing bandwidth and energy consumption, and
(ii) to control content dissemination thanks to access control
rules, which can be different for each scope [67]. Note that,
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 in certain scenarios, for instance,
to limit propagation of requests and provide a simple means to
attain context-sensitive communications. Finally, perimeter- and
channel-based access control is often violated by the 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 (which may also violate the privacy
requirements), 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 an ICN naming scheme such as Attribute-Based
Encryption [66] and access control delegation [67]. In the first
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solution, a trusted third party assigns a set of attributes to
each network entity. Then, a publisher performs the following
operations in order: (i) encrypting the data with a random key,
(ii) generating the metadata for the decryption phase, (iii)
creating an access policy that is used to encrypt the random key,
and (iv) appending 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 can authenticate himself and request authorization for
the particular policy to the Access Control Provider through the
URI.
5.2. 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 [59]
[72] [73] [95]. 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 [52] [54]:
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
[59]. 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 [89] may offer further scalability and
efficiency.
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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 [99]. In addition,
fast name lookup are necessary to ensure soft/hard real time
services [110][111][112]. This challenge is especially important
for applications with stringent latency requirements, such as
health monitoring, emergency handling and smart transportation
[113].
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 [101].
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.
5.3. Security and Privacy
Security and privacy is crucial to all the IoT 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 [77], while at the same
time this and other car 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
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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 Transport Layer Security
(TLS)/Datagram Transport Layer Security (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 [86], 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 as its main
objective generating data and providing some services, while the
communication between two devices is a secondary task. 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 [83] 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 resource-constrained nodes, energy limitation is the biggest
challenge. Moreover, a node 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 [78] [57].
o In the infrastructure part, we have several new threats introduced
by ICN-IoT [88] particularly in architectures employing name
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resolution service [123]. 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
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 be 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 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.
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5.4. Caching
In-network caching helps bring data closer to the consumers, but its
usage differs in constrained and infrastructure parts of the IoT
network. Furthermore, caching in ICN-IoT faces several challenges:
o Which nodes on the routing path should cache the data: According
to [54], caching the data on a subset of nodes can achieve a
better gain than caching it 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 [55], selecting a random router to cache data is as
good as caching the content everywhere. In [91], the authors
suggest that edge caching provides most of the benefits of in-
network caching but with simpler deployment. However, the
existing research on this topic typically consider workloads that
are analogous to today's CDNs, rather than the workload that can
be attributed to IoT applications considered here. Therefore,
further work is needed to understand the appropriate caching
approach for IoT applications.
o What to cache for the IoT applications: In many IoT applications,
customers often access a stream of sensor data, and as a result,
caching a particular sensor data for longer periods may not be
beneficial. In [93], a caching scheme is proposed to ensure that
older instances of the same sensor stream were first to be evicted
from the cache when needed. In [57], the authors suggest to cache
IoT services at the intermediate routers, and in [59], the authors
suggest to cache the control information such as pub/sub lists at
the intermediate nodes. In addition, it is not yet clear 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 the repeated
actuation requests within a given time period), or it could have
little meaning at all if the actuation uses authenticated requests
as in [92].
o Efficiency of distributed caching may be application dependent:
When content popularity is heterogeneous, some content is often
requested repeatedly. In this case, the network can definitely
benefit from caching. Another case where caching would be
beneficial is when devices with low duty cycle are present in the
network and when the access to the cloud infrastructure is
limited. In [93], it is also shown that there are benefits to
caching in the network when edge links are lossy, in particular if
the losses occur close to the content producer, as is common for
the wireless IoT networks. Furthermore, IoT devices can
collaborate to cache content in a manner that optimizes energy
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efficiency and content availability [94]. 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 and subsequent requests. It may also be
less beneficial to have caches distributed throughout the ICN
network, especially 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 dynamic
content/state. For example, when the last value for a sensor
reading is requested or desired, the returned data may change any
time the sensor reading is updated. In such case, in-network
caching may increase the risk of returning old or stale data.
5.5. Storage
Storage is useful for IoT systems regardless of its type, be it as a
long-term storage or as a short-term storage.
In the case of long-term in-network storage, resources can be
distributed among vantage points, which include the network edge and
the main IoT service aggregation points such as in the data centers.
The main differences, in regards to IoT-driven storage, between the
two locations are the size of data, processing intelligence and
heterogeneity of information that has to be dealt at these locations.
Specifically, the purpose of long term storage at the edge is to
analyze, filter, aggregate, and re-publish IoT data for consumption
either by the parent service components or directly by the consumers.
At the aggregation service points, the purpose is to re-publish the
data that will be presented as part of the global pub/sub service to
the interested consumers. Long term storage for IoT data also serves
the purpose of backup and replication of data, which come with
additional caveats. First, we need to decide on the number of
replicas needed for each IoT data stream, and the storage locations
for these replicas. Also note that, given that many IoT applications
consume data locally, storage locations should be kept near the data
sources. However, since IoT data is mostly appended to the end of a
stream, instead of being updated, it becomes easier to manage these
multiple replicas. Second, we need to adopt a mechanism that can
efficiently route traffic to the nearest data replica. ICN provides
several solutions to this problem, e.g., global name resolution
service (GNRS), which can keep track of each replica's location [58].
In the case of short-term in-network storage (where the term storage
refers to a temporary buffer, when an outgoing link is not
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available), the objective is to improve communication reliability,
especially when network links are unreliable, such as wireless links.
ICN-IoT can adopt a generalized storage-aware routing algorithm to
support delay and disruption tolerant packet forwarding. In such
case, each router can employ the in-network storage to facilitate
store vs. forward decisions in response to varying link conditions
and potential network interruptions [115]. These decisions can be
based on both short-term and long-term path quality metrics.
Additionally, packets along disconnected paths can be handled using a
disruption tolerant networking (DTN) based approach to offer delayed
delivery and replication features. In particular, each router
maintains two types of topology information: (i) an intra-partition
graph that is formed by collecting flooded link state advertisements,
which carry fine-grained, time-sensitive information about the intra-
network links, and (ii) a DTN graph that is maintained via
epidemically disseminated link-state advertisements, which carry
connection probabilities among all the network nodes. However, for
this scenario, we observe the following challenges: (i) when and how
long to store the data, and (ii) the next step after the short-term
storage. In [93] the authors show that it is 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.
5.6. Routing and Forwarding
ICN-IoT supports both device-to-device (D2D) and device-to-
infrastructure (D2I) communications. D2D communications may occur
within a single IoT domain, or across IoT domains, and may involve
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 routing protocols such as RPL [84], AODV[85], etc, with the
main challenge being the resource constraints of the IoT nodes. In
order to address this challenge, we can adopt a light-weight protocol
using much shorter ICN names for each communicating party within an
IoT domain (see Section 5.12 for details). In such case, before a
packet leaves the IoT domain, gateway node translates this short ICN
name associated with the source device to its original ICN name.
At the ICN infrastructure, data forwarding can adopt one of two
approaches: (i) direct name-based routing or (ii) indirect name
resolution service (NRS) driven routing.
o In direct name-based routing, packets are forwarded using the name
corresponding to either the data itself [95][63][74] or the name
of the destination node [75]. Here, the main challenge is to keep
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the state information required for data routing/forwarding at the
ICN router small. This can become an especially challenging
issue, if the architecture uses a flat naming scheme due to lack
of aggregation capabilities.
o In indirect routing, packets are forwarded based on the locator of
the destination node, which is obtained through a name resolution
service. Here, name-locator binding can be done either before
routing (i.e., assuming static binding) or during routing (i.e.,
assuming dynamic binding). In the case of static binding, router
state is the same as that in traditional routers, and the main
challenge is to perform name resolution fast, especially with
mobile IoT devices. In the case of dynamic binding, ICN routers
need to maintain a name-based routing table, and the challenge
becomes keeping the state information small, while at the same
time performing fast name resolution.
5.7. Mobility Management
Considering the diversity of IoT applications, mobility scenarios
range from tracking sensor data from mobile human beings to large
fleets of diverse mobile elements such as drones, vehicles, trucks,
trains (each of which may be associated with a transport
infrastructure). These mobility scenarios can take place over
heterogeneous access infrastructure that ranges from short range
802.15.4 communications to cellular radios. It is therefore expected
that handling information delivery in an ad hoc setting, which
involves vehicles, road side units (RSU), and the corresponding
infrastructure based services, shall offer more challenges. ICN
architectures have been generally shown to handle consumer and
producer mobility scenarios efficiently [61][129], and to be suitable
for V2V scenarios [62]. Networking tools to handle mobility varies
based on application requirements, which vary from delay and loss
tolerant to mission critical (with stringent delay and loss
requirements).
Therefore, the challenge becomes to quantify the cost associated with
mobility management in both the control and the forwarding planes, to
handle both static binding and dynamic binding (which enables
seamless mobility) of a named resource to its location when either or
both of consumer and/or producer is mobile.
During a network transaction, either the producer or the consumer may
move away, and thus we need mechanisms that can handle the mobility
of either or both to avoid information loss. ICN differentiates the
mobility of a consumer (Case I) from that of a producer (Case II):
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o Case I: When a consumer moves to a new location after sending out
a request for data, the data may traverse the path towards the
previous point of attachment (PoA), and in doing so, leaving
copies of it along that path. The data can then be retrieved by
the consumer by simply reissuing its request for the data, which
is a technique used by the direct routing approach. Conversely,
indirect routing approach does not differentiate between consumer
and producer mobility [95], as the indirect routing approach only
requires an update on the NRS, which can then update the routers
to re-bind the named resource to its new location, while using
late-binding to route the packet from the previous PoA to the new
one.
o Case II: In the case of a producer that has moved, the challenge
becomes managing the control overhead while searching for a new
data producer (or for re-locating the initial producer) [60]. For
this purpose, flooding techniques can be used to re-discover the
producer, or direct routing techniques can be employed after
enhancing them with the late-binding feature that enables seamless
mobility [61].
5.8. Contextual Communication
ICN enables contextualized communications by allowing metadata to be
included within control or application payload. Doing so can help
IoT applications to adapt to different environments, thereby enabling
intelligent networks that are self-configurable and intelligent
networking among consumers and producers [57]. For example, let us
look at the following smart transportation scenario: "James walks on
an NYC street and wants to find an empty taxi closest to his
location." In this example, the context is the location information
corresponding to James and the 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, we can use naming conventions that 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 within a 100m grid
area of 4QFJ 123 678 based on 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 can
become very challenging:
o First, we need to have a fast context resolution service, through
which the subscribed IoT devices can continuously update their
contextual information to the application (e.g., for the example
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above, that would be the locations of James and the taxis). Or,
in the case of a namespace driven approach, we need to have
mechanisms that can query the nearest neighbor based on a given
namespace on a continual basis.
o The difficulty of this challenge grows rapidly as the number of
involved devices as well as the number of contexts increase.
5.9. 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, with each sensor node or ICN router implementing context
reasoning [57]. Another major target for in-network computing is to
filter (and cleanse) the sensed data for IoT applications, as the
sensed data can be noisy [76].
Within this framework, Named Function Networking (NFN) [117] is
proposed as an extension of the ICN concept to named functions, which
are processed in the network, and which can be used to generate data
flow processing applications (for instance, one that is well-suited
to time series data processing by IoT sensing applications). Related
to this is the need to support efficient function naming, with
functions, input parameters, and the output result can all be
encapsulated within the packet header, the packet body, or a mixture
of the two (e.g. [33]). If functions are encapsulated within the
packet header, naming scheme can impact (i) how a computation task is
routed within the network, (ii) which IoT devices are involved with
the computation task (e.g. [56]), and (iii) how a name is decomposed
into smaller computation tasks and deployed in the network to achieve
better performance.
Another challenge is related to how to support compute-aware routing.
Default routing is typically used for forwarding requests towards the
nearest cache (or source/repository) and return the matching data to
the requester. Compute-aware routing, on the other hand, has a
different purpose. For instance, if the computation task is for
aggregating the sensed data, then the routing strategy becomes
routing the data to achieve a better aggregation performance [53].
In-network computing also includes synchronization challenges. Some
computation tasks, for instance, may need synchronization among sub-
tasks or IoT devices. For instance, a device may not send the
generated data as soon as it is available, because waiting for data
from the neighbouring devices can lead to better aggregation
performance. Or, some devices may choose to sleep to save energy,
while waiting for the results from the neighbours. Furthermore,
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while aggregating the computation results along the path,
intermediate IoT devices may need to choose the results generated
within a certain time window.
5.10. Self-Organization
General IoT deployments involve heterogeneous IoT systems that
consist of embedded systems, aggregators and service gateways in an
IoT domain. To scale the IoT deployments to a large scale, scope-
based self-organization is typically required. This specifically
relates to the IoT system middleware functions [122] that include (i)
device bootstrapping and discovery, (ii) assigning local/global names
to device and/or content, and (iii) security and trust management
functions towards device authentication and data privacy. ICN based
on-boarding protocols have been studied [100] and has been shown to
offer significant savings compared to the existing approaches. These
challenges span both the constrained devices as well as the
interactions among the aggregators and the service gateways, which
may need to contact external services like the authentication servers
to on-board these devices. A critical performance optimization
metric for these functions, while operating at scale, is to have low
control/data overhead in order to maximize the energy efficiency.
Furthermore, within the infrastructure part of the network, 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.
5.11. 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 that leverage
state-based forwarding in protocols like CCN/NDN. However, these
features have not been analyzed from the QoS perspective, when
heterogeneous traffic patterns are multiplexed at a router. In
general, QoS for ICN is an open area of research [125]. In-network
reliability comes at the cost of a complex network layer, hence a
research challenge here is to build redundancy and reliability at the
network layer to handle a wide range of disruption scenarios, such as
congestion, short/long term connection loss, or wireless impairments
along the last mile. An ICN network should allow features such as
opportunistic store-and-forward mechanisms to be enabled only at
certain points in the network, as these mechanisms entail additional
control/forwarding plane overheads that can adversely affect the
application throughput. For additional details, see Section 5.5, for
the discussion on in-network storage.
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5.12. Resource Constraints and Heterogeneity
An IoT architecture should take into consideration the resource
constraints of the often embedded IoT nodes. Having globally unique
IDs (GUID in short) is a key feature in ICN, and these IDs may
consist of tens of bytes. Each device would then 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, for
instance, for transmissions over a low-rate layer-2 protocol such as
802.15.4. To solve this issue, ICN can operate using a lighter-
weight packet header and a much shorter locally unique ID (LUID in
short). In this way, we can map a device's long GUID to its short
LUID when the packet targeting the device reaches the local area IoT
domain. To cope with collisions that may occur with this mapping
process, we let each domain to have its own GUID-to-LUID mapping
scheme, which can be managed by a gateway deployed at the edge of the
domain. Different from NAT and other existing domain- or gateway-
based solutions, ICN-IoT does not change the identity of an
application. The applications, either on the constrained IoT devices
or on the infrastructure nodes, continue to use the long GUIDs to
identify one another, while the network performs the translation,
which is transparent to these applications. An IoT node carries its
GUID no matter where it moves, even when it is relocated to another
local IoT domain and assigned a new LUID. This ensures the global
reachability under mobility, while taking into consideration the
resource constraints of the embedded devices.
In addition, optimizations for the other components of the ICN-IoT
system (described in earlier subsections) can lead to optimization of
the energy consumption as well.
6. Differences from T2TRG
Thing-to-Thing Research Group (T2TRG) [9] is an IoT research group
under IRTF, which focuses on the research challenges of realizing IoT
solutions assuming IP as the narrow waist. As IP-IoT has been a
research topic for over a decade and with active industry solutions,
this group provides a venue to study the advanced issues related to
its security, provisioning, configuration and inter-operability
considering the various heterogeneous application environments. ICN-
IoT, on the other hand, is a recent research effort, where the
objective is to exploit the ICN features of name based routing and
security, caching, multicasting, mobility, etc. in an end-to-end
manner to enable IoT services spanning all kind of networking
scenarios, i.e., ad hoc, infrastructure, and hybrid scenarios. More
detailed comparison of IP-IoT versus ICN-IoT is presented in
Section 4.
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7. Security Considerations
ICN puts security in the forefront of its design, which the ICN-IoT
designs can leverage to build applications with varying security
requirements. This issue has been discussed quite elaborately in
this draft. However, as this is an informational draft and it does
not create new considerations beyond what has been discussed.
8. 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 for 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 both application and
networking perspectives. We then discuss why the current IP-based
application layer unified IoT solutions fall short of meeting these
requirements, and how an ICN architecture is more suitable towards
addressing the IoT service needs. 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 these varying IoT service
needs.
9. Acknowledgements
We thank all the contributors, reviewers and the valuable comments
offered by the chairs to improve this draft.
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[6] Ghodsi, A., Shenker, S., Koponen, T., Singla, A.,
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Authors' Addresses
Ravishankar Ravindran
Huawei Technologies
2330 Central Expressway
Santa Clara, CA 95050
USA
Email: ravi.ravindran@huawei.com
Yanyong Zhang
WINLAB, Rutgers University
671, U.S 1
North Brunswick, NJ 08902
USA
Email: yyzhang@winlab.rutgers.edu
Ravindran, Ed., et al. Expires November 3, 2019 [Page 50]
Internet-Draft ICN based Architecture for IoT May 2019
Luigi Alfredo Grieco
Politecnico di Bari (DEI)
Via Orabona 4
Bari 70125
Italy
Email: alfredo.grieco@poliba.it
Anders Lindgren
RISE SICS
Box 1263
Kista SE-164 29
SE
Email: anders.lindgren@ri.se
Jeff Burke
UCLA REMAP
102 East Melnitz Hall
Los Angeles, CA 90095
USA
Email: jburke@ucla.edu
Bengt Ahlgren
RISE SICS
Box 1263
Kista, CA SE-164 29
SE
Email: bengt.ahlgren@ri.se
Aytac Azgin
Huawei Technologies
2330 Central Expressway
Santa Clara, CA 95050
USA
Email: aytac.azgin@huawei.com
Ravindran, Ed., et al. Expires November 3, 2019 [Page 51]
