Internet DRAFT - draft-ersue-opsawg-coman-use-cases
draft-ersue-opsawg-coman-use-cases
Internet Engineering Task Force M. Ersue, Ed.
Internet-Draft Nokia Solutions and Networks
Intended status: Informational D. Romascanu
Expires: April 28, 2014 Avaya
J. Schoenwaelder
Jacobs University Bremen
October 25, 2013
Management of Networks with Constrained Devices: Use Cases
draft-ersue-opsawg-coman-use-cases-00
Abstract
This document discusses the use cases concerning the management of
networks, where constrained devices are involved. A problem
statement, deployment options and the requirements on the networks
with constrained devices can be found in the companion document [COM-
REQ].
Status of this Memo
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This Internet-Draft will expire on April 28, 2014.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2. Terminology . . . . . . . . . . . . . . . . . . . . . . . 4
2. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1. Environmental Monitoring . . . . . . . . . . . . . . . . . 5
2.2. Medical Applications . . . . . . . . . . . . . . . . . . . 5
2.3. Industrial Applications . . . . . . . . . . . . . . . . . 6
2.4. Home Automation . . . . . . . . . . . . . . . . . . . . . 7
2.5. Building Automation . . . . . . . . . . . . . . . . . . . 8
2.6. Energy Management . . . . . . . . . . . . . . . . . . . . 9
2.7. Transport Applications . . . . . . . . . . . . . . . . . . 11
2.8. Infrastructure Monitoring . . . . . . . . . . . . . . . . 12
2.9. Community Network Applications . . . . . . . . . . . . . . 13
2.10. Mobile Applications . . . . . . . . . . . . . . . . . . . 15
2.11. Automated Metering Infrastructure (AMI) . . . . . . . . . 16
2.12. MANET Concept of Operations (CONOPS) in Military . . . . . 18
3. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 24
4. Security Considerations . . . . . . . . . . . . . . . . . . . 25
5. Contributors . . . . . . . . . . . . . . . . . . . . . . . . . 26
6. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 27
7. References . . . . . . . . . . . . . . . . . . . . . . . . . . 28
7.1. Normative References . . . . . . . . . . . . . . . . . . . 28
7.2. Informative References . . . . . . . . . . . . . . . . . . 28
Appendix A. Open issues . . . . . . . . . . . . . . . . . . . . . 29
Appendix B. Change Log . . . . . . . . . . . . . . . . . . . . . 30
B.1. draft-ersue-constrained-mgmt-03 -
draft-ersue-opsawg-coman-use-cases-00 . . . . . . . . . . 30
B.2. draft-ersue-constrained-mgmt-02-03 . . . . . . . . . . . . 30
B.3. draft-ersue-constrained-mgmt-01-02 . . . . . . . . . . . . 31
B.4. draft-ersue-constrained-mgmt-00-01 . . . . . . . . . . . . 32
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 33
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1. Introduction
1.1. Overview
Small devices with limited CPU, memory, and power resources, so
called constrained devices (aka. sensor, smart object, or smart
device) can be connected to a network. Such a network of constrained
devices itself may be constrained or challenged, e.g. with unreliable
or lossy channels, wireless technologies with limited bandwidth and a
dynamic topology, needing the service of a gateway or proxy to
connect to the Internet. In other scenarios, the constrained devices
can be connected to a non-constrained network using off-the-shelf
protocol stacks. Constrained devices might be in charge of gathering
information in diverse settings including natural ecosystems,
buildings, and factories and send the information to one or more
server stations.
Network management is characterized by monitoring network status,
detecting faults, and inferring their causes, setting network
parameters, and carrying out actions to remove faults, maintain
normal operation, and improve network efficiency and application
performance. The traditional network management application
periodically collects information from a set of elements that are
needed to manage, processes the data, and presents them to the
network management users. Constrained devices, however, often have
limited power, low transmission range, and might be unreliable. They
might also need to work in hostile environments with advanced
security requirements or need to be used in harsh environments for a
long time without supervision. Due to such constraints, the
management of a network with constrained devices offers different
type of challenges compared to the management of a traditional IP
network.
This document aims to understand the use cases for the management of
a network, where constrained devices are involved. The document
lists and discusses diverse use cases for the management from the
network as well as from the application point of view. The
application scenarios discussed aim to show where networks of
constrained devices are expected to be deployed. For each
application scenario, we first briefly describe the characteristics
followed by a discussion on how network management can be provided,
who is likely going to be responsible for it, and on which time-scale
management operations are likely to be carried out.
A problem statement, deployment and management topology options as
well as the requirements on the networks with constrained devices can
be found in the companion document [COM-REQ].
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1.2. Terminology
This documents builds on the terminology defined in
[I-D.ietf-lwig-terminology] and [COM-REQ].
[I-D.ietf-lwig-terminology] is a base document for the terminology
concerning constrained devices and constrained networks.
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2. Use Cases
2.1. Environmental Monitoring
Environmental monitoring applications are characterized by the
deployment of a number of sensors to monitor emissions, water
quality, or even the movements and habits of wildlife. Other
applications in this category include earthquake or tsunami early-
warning systems. The sensors often span a large geographic area,
they can be mobile, and they are often difficult to replace.
Furthermore, the sensors are usually not protected against tampering.
Management of environmental monitoring applications is largely
concerned with the monitoring whether the system is still functional
and the roll-out of new constrained devices in case the system looses
too much of its structure. The constrained devices themselves need
to be able to establish connectivity (auto-configuration) and they
need to be able to deal with events such as loosing neighbors or
being moved to other locations.
Management responsibility typically rests with the organization
running the environmental monitoring application. Since these
monitoring applications must be designed to tolerate a number of
failures, the time scale for detecting and recording failures is for
some of these applications likely measured in hours and repairs might
easily take days. However, for certain environmental monitoring
applications, much tighter time scales may exist and might be
enforced by regulations (e.g., monitoring of nuclear radiation).
2.2. Medical Applications
Constrained devices can be seen as an enabling technology for
advanced and possibly remote health monitoring and emergency
notification systems, ranging from blood pressure and heart rate
monitors to advanced devices capable to monitor implanted
technologies, such as pacemakers or advanced hearing aids. Medical
sensors may not only be attached to human bodies, they might also
exist in the infrastructure used by humans such as bathrooms or
kitchens. Medical applications will also be used to ensure
treatments are being applied properly and they might guide people
losing orientation. Fitness and wellness applications, such as
connected scales or wearable heart monitors, encourage consumers to
exercise and empower self-monitoring of key fitness indicators.
Different applications use Bluetooth, Wi-Fi or Zigbee connections to
access the patient's smartphone or home cellular connection to access
the Internet.
Constrained devices that are part of medical applications are managed
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either by the users of those devices or by an organization providing
medical (monitoring) services for physicians. In the first case,
management must be automatic and or easy to install and setup by
average people. In the second case, it can be expected that devices
be controlled by specially trained people. In both cases, however,
it is crucial to protect the privacy of the people to which medical
devices are attached. Even though the data collected by a heart beat
monitor might be protected, the pure fact that someone carries such a
device may need protection. As such, certain medical appliances may
not want to participate in discovery and self-configuration protocols
in order to remain invisible.
Many medical devices are likely to be used (and relied upon) to
provide data to physicians in critical situations since the biggest
market is likely elderly and handicapped people. As such, fault
detection of the communication network or the constrained devices
becomes a crucial function that must be carried out with high
reliability and, depending on the medical appliance and its
application, within seconds.
2.3. Industrial Applications
Industrial Applications and smart manufacturing refer not only to
production equipment, but also to a factory that carries out
centralized control of energy, HVAC (heating, ventilation, and air
conditioning), lighting, access control, etc. via a network. For the
management of a factory it is becoming essential to implement smart
capabilities. From an engineering standpoint, industrial
applications are intelligent systems enabling rapid manufacturing of
new products, dynamic response to product demand, and real-time
optimization of manufacturing production and supply chain networks.
Potential industrial applications e.g. for smart factories and smart
manufacturing are:
o Digital control systems with embedded, automated process controls,
operator tools, as well as service information systems optimizing
plant operations and safety.
o Asset management using predictive maintenance tools, statistical
evaluation, and measurements maximizing plant reliability.
o Smart sensors detecting anomalies to avoid abnormal or
catastrophic events.
o Smart systems integrated within the industrial energy management
system and externally with the smart grid enabling real-time
energy optimization.
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Sensor networks are an essential technology used for smart
manufacturing. Measurements, automated controls, plant optimization,
health and safety management, and other functions are provided by a
large number of networked sectors. Data interoperability and
seamless exchange of product, process, and project data are enabled
through interoperable data systems used by collaborating divisions or
business systems. Intelligent automation and learning systems are
vital to smart manufacturing but must be effectively integrated with
the decision environment. Wireless sensor networks (WSN) have been
developed for machinery Condition-based Maintenance (CBM) as they
offer significant cost savings and enable new functionalities.
Inaccessible locations, rotating machinery, hazardous areas, and
mobile assets can be reached with wireless sensors. WSNs can provide
today wireless link reliability, real-time capabilities, and quality-
of-service and enable industrial and related wireless sense and
control applications.
Management of industrial and factory applications is largely focused
on the monitoring whether the system is still functional, real-time
continuous performance monitoring, and optimization as necessary.
The factory network might be part of a campus network or connected to
the Internet. The constrained devices in such a network need to be
able to establish configuration themselves (auto-configuration) and
might need to deal with error conditions as much as possible locally.
Access control has to be provided with multi-level administrative
access and security. Support and diagnostics can be provided through
remote monitoring access centralized outside of the factory.
Management responsibility is typically owned by the organization
running the industrial application. Since the monitoring
applications must handle a potentially large number of failures, the
time scale for detecting and recording failures is for some of these
applications likely measured in minutes. However, for certain
industrial applications, much tighter time scales may exist, e.g. in
real-time, which might be enforced by the manufacturing process or
the use of critical material.
2.4. Home Automation
Home automation includes the control of lighting, heating,
ventilation, air conditioning, appliances, and entertainment devices
to improve convenience, comfort, energy efficiency, and security. It
can be seen as a residential extension of building automation.
Home automation networks need a certain amount of configuration
(associating switches or sensors to actors) that is either provided
by electricians deploying home automation solutions or done by
residents by using the application user interface to configure (parts
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of) the home automation solution. Similarly, failures may be
reported via suitable interfaces to residents or they might be
recorded and made available to electricians in charge of the
maintenance of the home automation infrastructure.
The management responsibility lies either with the residents or it
may be outsourced to electricians providing management of home
automation solutions as a service. The time scale for failure
detection and resolution is in many cases likely counted in hours to
days.
2.5. Building Automation
Building automation comprises the distributed systems designed and
deployed to monitor and control the mechanical, electrical and
electronic systems inside buildings with various destinations (e.g.,
public and private, industrial, institutions, or residential).
Advanced Building Automation Systems (BAS) may be deployed
concentrating the various functions of safety, environmental control,
occupancy, security. More and more the deployment of the various
functional systems is connected to the same communication
infrastructure (possibly Internet Protocol based), which may involve
wired or wireless communications networks inside the building.
Building automation requires the deployment of a large number (10-
100.000) of sensors that monitor the status of devices, and
parameters inside the building and controllers with different
specialized functionality for areas within the building or the
totality of the building. Inter-node distances between neighboring
nodes vary between 1 to 20 meters. Contrary to home automation, in
building management the devices are expected to be managed assets and
known to a set of commissioning tools and a data storage, such that
every connected device has a known origin. The management includes
verifying the presence of the expected devices and detecting the
presence of unwanted devices.
Examples of functions performed by such controllers are regulating
the quality, humidity, and temperature of the air inside the building
and lighting. Other systems may report the status of the machinery
inside the building like elevators, or inside the rooms like
projectors in meeting rooms. Security cameras and sensors may be
deployed and operated on separate dedicated infrastructures connected
to the common backbone. The deployment area of a BAS is typically
inside one building (or part of it) or several buildings
geographically grouped in a campus. A building network can be
composed of subnets, where a subnet covers a floor, an area on the
floor, or a given functionality (e.g. security cameras).
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Some of the sensors in Building Automation Systems (for example fire
alarms or security systems) register, record and transfer critical
alarm information and therefore must be resilient to events like loss
of power or security attacks. This leads to the need that some
components and subsystems operate in constrained conditions and are
separately certified. Also in some environments, the malfunctioning
of a control system (like temperature control) needs to be reported
in the shortest possible time. Complex control systems can
misbehave, and their critical status reporting and safety algorithms
need to be basic and robust and perform even in critical conditions.
Building Automation solutions are deployed in some cases in newly
designed buildings, in other cases it might be over existing
infrastructures. In the first case, there is a broader range of
possible solutions, which can be planned for the infrastructure of
the building. In the second case the solution needs to be deployed
over an existing structure taking into account factors like existing
wiring, distance limitations, the propagation of radio signals over
walls and floors. As a result, some of the existing WLAN solutions
(e.g. IEEE 802.11 or IEEE 802.15) may be deployed. In mission-
critical or security sensitive environments and in cases where link
failures happen often, topologies that allow for reconfiguration of
the network and connection continuity may be required. Some of the
sensors deployed in building automation may be very simple
constrained devices for which class 0 or class 1 may be assumed.
For lighting applications, groups of lights must be defined and
managed. Commands to a group of light must arrive within 200 ms at
all destinations. The installation and operation of a building
network has different requirements. During the installation, many
stand-alone networks of a few to 100 nodes co-exist without a
connection to the backbone. During this phase, the nodes are
identified with a network identifier related to their physical
location. Devices are accessed from an installation tool to connect
them to the network in a secure fashion. During installation, the
setting of parameters to common values to enable interoperability may
occur (e.g. Trickle parameter values). During operation, the
networks are connected to the backbone while maintaining the network
identifier to physical location relation. Network parameters like
address and name are stored in DNS. The names can assist in
determining the physical location of the device.
2.6. Energy Management
EMAN working group developed [I-D.ietf-eman-framework], which defines
a framework for providing Energy Management for devices within or
connected to communication networks. This document observes that one
of the challenges of energy management is that a power distribution
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network is responsible for the supply of energy to various devices
and components, while a separate communication network is typically
used to monitor and control the power distribution network. Devices
that have energy management capability are defined as Energy Devices
and identified components within a device (Energy Device Components)
can be monitored for parameters like Power, Energy, Demand and Power
Quality. If a device contains batteries, they can be also monitored
and managed.
Energy devices differ in complexity and may include basic sensors or
switches, specialized electrical meters, or power distribution units
(PDU), and subsystems inside the network devices (routers, network
switches) or home or industrial appliances. An Energy Management
System is a combination of hardware and software used to administer a
network with the primary purpose being Energy Management. The
operators of such a system are either the utility providers or
customers that aim to control and reduce the energy consumption and
the associated costs. The topology in use differs and the deployment
can cover areas from small surfaces (individual homes) to large
geographical areas. EMAN requirements document [RFC6988] discusses
the requirements for energy management concerning monitoring and
control functions.
It is assumed that Energy Management will apply to a large range of
devices of all classes and networks topologies. Specific resource
monitoring like battery utilization and availability may be specific
to devices with lower physical resources (device classes C0 or C1).
Energy Management is especially relevant to Smart Grid. A Smart Grid
is an electrical grid that uses data networks to gather and act on
energy and power-related information, in an automated fashion with
the goal to improve the efficiency, reliability, economics, and
sustainability of the production and distribution of electricity. As
such Smart Grid provides sustainable and reliable generation,
transmission, distribution, storage and consumption of electrical
energy based on advanced energy and ICT solutions and as such enables
e.g. following specific application areas: Smart transmission
systems, Demand Response/Load Management, Substation Automation,
Advanced Distribution Management, Advanced Metering Infrastructure
(AMI), Smart Metering, Smart Home and Building Automation,
E-mobility, etc.
Smart Metering is a good example of a M2M application and can be
realized as one of the vertical applications in an M2M environment.
Different types of possibly wireless small meters produce all
together a huge amount of data, which is collected by a central
entity and processed by an application server. The M2M
infrastructure can be provided by a mobile network operator as the
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meters in urban areas will have most likely a cellular or WiMAX
radio.
Smart Grid is built on a distributed and heterogeneous network and
can use a combination of diverse networking technologies, such as
wireless Access Technologies (WiMAX, Cellular, etc.), wireline and
Internet Technologies (e.g., IP/MPLS, Ethernet, SDH/PDH over Fiber
optic, etc.) as well as low-power radio technologies enabling the
networking of smart meters, home appliances, and constrained devices
(e.g. BT-LE, ZigBee, Z-Wave, Wi-Fi, etc.). The operational
effectiveness of the smart grid is highly dependent on a robust, two-
way, secure, and reliable communications network with suitable
availability.
The management of a distributed system like smart grid requires an
end-to-end management of and information exchange through different
type of networks. However, as of today there is no integrated smart
grid management approach and no common smart grid information model
available. Specific smart grid applications or network islands use
their own management mechanisms. For example, the management of
smart meters depends very much on the AMI environment they have been
integrated to and the networking technologies they are using. In
general, smart meters do only need seldom reconfiguration and they
send a small amount of redundant data to a central entity. For a
discussion on the management needs of an AMI network see
Section 2.11. The management needs for Smart Home and Building
Automation are discussed in Section 2.4 and Section 2.5.
2.7. Transport Applications
Transport Application is a generic term for the integrated
application of communications, control, and information processing in
a transportation system. Transport telematics or vehicle telematics
are used as a term for the group of technologies that support
transportation systems. Transport applications running on such a
transportation system cover all modes of the transport and consider
all elements of the transportation system, i.e. the vehicle, the
infrastructure, and the driver or user, interacting together
dynamically. The overall aim is to improve decision making, often in
real time, by transport network controllers and other users, thereby
improving the operation of the entire transport system. As such,
transport applications can be seen as one of the important M2M
service scenarios with the involvement of manifold small devices.
The definition encompasses a broad array of techniques and approaches
that may be achieved through stand-alone technological applications
or as enhancements to other transportation communication schemes.
Examples for transport applications are inter and intra vehicular
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communication, smart traffic control, smart parking, electronic toll
collection systems, logistic and fleet management, vehicle control,
and safety and road assistance.
As a distributed system, transport applications require an end-to-end
management of different types of networks. It is likely that
constrained devices in a network (e.g. a moving in-car network) have
to be controlled by an application running on an application server
in the network of a service provider. Such a highly distributed
network including mobile devices on vehicles is assumed to include a
wireless access network using diverse long distance wireless
technologies such as WiMAX, 3G/LTE or satellite communication, e.g.
based on an embedded hardware module. As a result, the management of
constrained devices in the transport system might be necessary to
plan top-down and might need to use data models obliged from and
defined on the application layer. The assumed device classes in use
are mainly C2 devices. In cases, where an in-vehicle network is
involved, C1 devices with limited capabilities and a short-distance
constrained radio network, e.g. IEEE 802.15.4 might be used
additionally.
Management responsibility typically rests within the organization
running the transport application. The constrained devices in a
moving transport network might be initially configured in a factory
and a reconfiguration might be needed only rarely. New devices might
be integrated in an ad-hoc manner based on self-management and
-configuration capabilities. Monitoring and data exchange might be
necessary to do via a gateway entity connected to the back-end
transport infrastructure. The devices and entities in the transport
infrastructure need to be monitored more frequently and can be able
to communicate with a higher data rate. The connectivity of such
entities does not necessarily need to be wireless. The time scale
for detecting and recording failures in a moving transport network is
likely measured in hours and repairs might easily take days. It is
likely that a self-healing feature would be used locally.
2.8. Infrastructure Monitoring
Infrastructure monitoring is concerned with the monitoring of
infrastructures such as bridges, railway tracks, or (offshore)
windmills. The primary goal is usually to detect any events or
changes of the structural conditions that can impact the risk and
safety of the infrastructure being monitored. Another secondary goal
is to schedule repair and maintenance activities in a cost effective
manner.
The infrastructure to monitor might be in a factory or spread over a
wider area but difficult to access. As such, the network in use
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might be based on a combination of fixed and wireless technologies,
which use robust networking equipment and support reliable
communication. It is likely that constrained devices in such a
network are mainly C2 devices and have to be controlled centrally by
an application running on a server. In case such a distributed
network is widely spread, the wireless devices might use diverse
long-distance wireless technologies such as WiMAX, or 3G/LTE, e.g.
based on embedded hardware modules. In cases, where an in-building
network is involved, the network can be based on Ethernet or wireless
technologies suitable for in-building usage.
The management of infrastructure monitoring applications is primarily
concerned with the monitoring of the functioning of the system.
Infrastructure monitoring devices are typically rolled out and
installed by dedicated experts and changes are rare since the
infrastructure itself changes rarely. However, monitoring devices
are often deployed in unsupervised environments and hence special
attention must be given to protecting the devices from being
modified.
Management responsibility typically rests with the organization
owning the infrastructure or responsible for its operation. The time
scale for detecting and recording failures is likely measured in
hours and repairs might easily take days. However, certain events
(e.g., natural disasters) may require that status information be
obtained much more quickly and that replacements of failed sensors
can be rolled out quickly (or redundant sensors are activated
quickly). In case the devices are difficult to access, a self-
healing feature on the device might become necessary.
2.9. Community Network Applications
Community networks are comprised of constrained routers in a multi-
hop mesh topology, communicating over a lossy, and often wireless
channel. While the routers are mostly non-mobile, the topology may
be very dynamic because of fluctuations in link quality of the
(wireless) channel caused by, e.g., obstacles, or other nearby radio
transmissions. Depending on the routers that are used in the
community network, the resources of the routers (memory, CPU) may be
more or less constrained - available resources may range from only a
few kilobytes of RAM to several megabytes or more, and CPUs may be
small and embedded, or more powerful general-purpose processors.
Examples of such community networks are the FunkFeuer network
(Vienna, Austria), FreiFunk (Berlin, Germany), Seattle Wireless
(Seattle, USA), and AWMN (Athens, Greece). These community networks
are public and non-regulated, allowing their users to connect to each
other and - through an uplink to an ISP - to the Internet. No fee,
other than the initial purchase of a wireless router, is charged for
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these services. Applications of these community networks can be
diverse, e.g., location based services, free Internet access, file
sharing between users, distributed chat services, social networking
etc, video sharing etc.
As an example of a community network, the FunkFeuer network comprises
several hundred routers, many of which have several radio interfaces
(with omnidirectional and some directed antennas). The routers of
the network are small-sized wireless routers, such as the Linksys
WRT54GL, available in 2011 for less than 50 Euros. These routers,
with 16 MB of RAM and 264 MHz of CPU power, are mounted on the
rooftops of the users. When new users want to connect to the
network, they acquire a wireless router, install the appropriate
firmware and routing protocol, and mount the router on the rooftop.
IP addresses for the router are assigned manually from a list of
addresses (because of the lack of autoconfiguration standards for
mesh networks in the IETF).
While the routers are non-mobile, fluctuations in link quality
require an ad hoc routing protocol that allows for quick convergence
to reflect the effective topology of the network (such as NHDP
[RFC6130] and OLSRv2 [I-D.ietf-manet-olsrv2] developed in the MANET
WG). Usually, no human interaction is required for these protocols,
as all variable parameters required by the routing protocol are
either negotiated in the control traffic exchange, or are only of
local importance to each router (i.e. do not influence
interoperability). However, external management and monitoring of an
ad hoc routing protocol may be desirable to optimize parameters of
the routing protocol. Such an optimization may lead to a more stable
perceived topology and to a lower control traffic overhead, and
therefore to a higher delivery success ratio of data packets, a lower
end-to-end delay, and less unnecessary bandwidth and energy usage.
Different use cases for the management of community networks are
possible:
o One single Network Management Station (NMS), e.g. a border gateway
providing connectivity to the Internet, requires managing or
monitoring routers in the community network, in order to
investigate problems (monitoring) or to improve performance by
changing parameters (managing). As the topology of the network is
dynamic, constant connectivity of each router towards the
management station cannot be guaranteed. Current network
management protocols, such as SNMP and Netconf, may be used (e.g.,
using interfaces such as the NHDP-MIB [RFC6779]). However, when
routers in the community network are constrained, existing
protocols may require too many resources in terms of memory and
CPU; and more importantly, the bandwidth requirements may exceed
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the available channel capacity in wireless mesh networks.
Moreover, management and monitoring may be unfeasible if the
connection between the NMS and the routers is frequently
interrupted.
o A distributed network monitoring, in which more than one
management station monitors or manages other routers. Because
connectivity to a server cannot be guaranteed at all times, a
distributed approach may provide a higher reliability, at the cost
of increased complexity. Currently, no IETF standard exists for
distributed monitoring and management.
o Monitoring and management of a whole network or a group of
routers. Monitoring the performance of a community network may
require more information than what can be acquired from a single
router using a network management protocol. Statistics, such as
topology changes over time, data throughput along certain routing
paths, congestion etc., are of interest for a group of routers (or
the routing domain) as a whole. As of 2012, no IETF standard
allows for monitoring or managing whole networks, instead of
single routers.
2.10. Mobile Applications
M2M services are increasingly provided by mobile service providers as
numerous devices, home appliances, utility meters, cars, video
surveillance cameras, and health monitors, are connected with mobile
broadband technologies. This diverse range of machines brings new
network and service requirements and challenges. Different
applications e.g. in a home appliance or in-car network use
Bluetooth, Wi-Fi or Zigbee and connect to a cellular module acting as
a gateway between the constrained environment and the mobile cellular
network.
Such a gateway might provide different options for the connectivity
of mobile networks and constrained devices, e.g.:
o a smart phone with 3G/4G and WLAN radio might use BT-LE to connect
to the devices in a home area network,
o a femtocell might be combined with home gateway functionality
acting as a low-power cellular base station connecting smart
devices to the application server of a mobile service provider.
o an embedded cellular module with LTE radio connecting the devices
in the car network with the server running the telematics service,
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o an M2M gateway connected to the mobile operator network supporting
diverse IoT connectivity technologies including ZigBee and CoAP
over 6LoWPAN over IEEE 802.15.4.
Common to all scenarios above is that they are embedded in a service
and connected to a network provided by a mobile service provider.
Usually there is a hierarchical deployment and management topology in
place where different parts of the network are managed by different
management entities and the count of devices to manage is high (e.g.
many thousands). In general, the network is comprised by manifold
type and size of devices matching to different device classes. As
such, the managing entity needs to be prepared to manage devices with
diverse capabilities using different communication or management
protocols. In case the devices are directly connected to a gateway
they most likely are managed by a management entity integrated with
the gateway, which itself is part of the Network Management System
(NMS) run by the mobile operator. Smart phones or embedded modules
connected to a gateway might be themselves in charge to manage the
devices on their level. The initial and subsequent configuration of
such a device is mainly based on self-configuration and is triggered
by the device itself.
The challenges in the management of devices in a mobile application
are manifold. Firstly, the issues caused through the device mobility
need to be taken into consideration. While the cellular devices are
moving around or roaming between different regional networks, they
should report their status to the corresponding management entities
with regard to their proximity and management hierarchy. Secondly, a
variety of device troubleshooting information needs to be reported to
the management system in order to provide accurate service to the
customer. Third but not least, the NMS and the used management
protocol need to be tailored to keep the cellular devices lightweight
and as energy efficient as possible.
The data models used in these scenario are mostly derived from the
models of the operator NMS and might be used to monitor the status of
the devices and to exchange the data sent by or read from the
devices. The gateway might be in charge of filtering and aggregating
the data received from the device as the information sent by the
device might be mostly redundant.
2.11. Automated Metering Infrastructure (AMI)
An AMI network enables an electric utility to retrieve frequent
electric usage data from each electric meter installed at a
customer's home or business. With an AMI network, a utility can also
receive immediate notification of power outages when they occur,
directly from the electric meters that are experiencing those
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outages. In addition, if the AMI network is designed to be open and
extensible, it could serve as the backbone for communicating with
other distribution automation devices besides meters, which could
include transformers and reclosers.
In this use case, each meter in the AMI network contains a
constrained device. These devices are typically C2 devices. Each
meter connects to a constrained mesh network with a low-bandwidth
radio. These radios can be 50, 150, or 200 kbps at raw link speed,
but actual network throughput may be significantly lower due to
forward error correction, multihop delays, MAC delays, lossy links,
and protocol overhead.
The constrained devices are used to connect the metering logic with
the network, so that usage data and outage notifications can be sent
back to the utility's headend systems over the network. These
headend systems are located in a data center managed by the utility,
and may include meter data collection systems, meter data management
systems, and outage management systems.
The meters are connected to a mesh network, and each meter can act as
both a source of traffic and as a router for other meters' traffic.
In a typical AMI application, smaller amounts of traffic (read
requests, configuration) flow "downstream" from the headend to the
mesh, and larger amounts of traffic flow "upstream" from the mesh to
the headend. However, during a firmware update operation, larger
amounts of traffic might flow downstream while smaller amounts flow
upstream. Other applications that make use of the AMI network may
have their own distinct traffic flows.
The mesh network is anchored by a collection of higher-end devices,
which contain a mesh radio that connects to the constrained network
as well as a backhaul link that connects to a less-constrained
network. The backhaul link could be cellular, WiMAX, or Ethernet,
depending on the backhaul networking technology that the utility has
chosen. These higher-end devices (termed "routers" in this use case)
are typically installed on utility poles throughout the service
territory. Router devices are typically less constrained than
meters, and often contain the full routing table for all the
endpoints routing through them.
In this use case, the utility typically installs on the order of 1000
meters per router. The collection of meters comprised in a local
network that are routing through a specific router is called in this
use case a Local Meter Network (LMN). When powered on, each meter is
designed to discover the nearby LMNs, select the optimal LMN to join,
and select the optimal meters in that LMN to route through when
sending data to the headend. After joining the LMN, the meter is
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designed to continuously monitor and optimize its connection to the
LMN, and it may change routes and LMNs as needed.
Each LMN may be configured e.g. to share an encryption key, providing
confidentiality for all data traffic within the LMN. This key may be
obtained by a meter only after an end-to-end authentication process
based on certificates, ensuring that only authorized and
authenticated meters are allowed to join the LMN, and by extension,
the mesh network as a whole.
After joining the LMN, each endpoint obtains a routable and possibly
private IPv6 address that enables end-to-end communication between
the headend systems and each meter. In this use case, the meters are
always-on. However, due to lossy links and network optimization, not
every meter will be immediately accessible, though eventually every
meter will be able to exchange data with the headend.
In a large AMI deployment, there may be 10 million meters supported
by 10.000 routers, spread across a very large geographic area.
Within a single LMN, the meters may range between 1 and approx. 20
hops from the router. During the deployment process, these meters
are installed and turned on in large batches, and those meters must
be authenticated, given addresses, and provisioned with any
configuration information necessary for their operation. During
deployment and after deployment is finished, the network must be
monitored continuously and failures must be handled. Configuration
parameters may need to be changed on large numbers of devices, but
most of the devices will be running the same configuration.
Moreover, eventually, the firmware in those meters will need to be
upgraded, and this must also be done in large batches because most of
the devices will be running the same firmware image.
Because there may be thousands of routers, this operational model
(batch deployment, automatic provisioning, continuous monitoring,
batch reconfiguration, batch firmware update) should also apply to
the routers as well as the constrained devices. The scale is
different (thousands instead of millions) but still large enough to
make individual management impractical for routers as well.
2.12. MANET Concept of Operations (CONOPS) in Military
The use case on the Concept of Operations (CONOPS) focuses on the
configuration and monitoring of networks that are currently being
used in military and as such, it offers insights and challenges of
network management that military agencies are facing.
As technology advances, military networks nowadays become large and
consist of varieties of different types of equipments that run
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different protocols and tools that obviously increase complexity of
the tactical networks. Moreover, lacks of open common interfaces and
Application Programming Interface (API) are often a challenge to
network management. Configurations are, most likely, manually
performed. Some devices do not support IP networks. Integration and
evaluation process are no longer trivial for a large set of protocols
and tools. In addition, majority of protocols and tools developed by
vendors that are being used are proprietary which makes integration
more difficult. The main reason that leads to this problem is that
there is no clearly defined standard for the MANET Concept of
Operations (CONOPS). In the following, a set of scenarios of network
operations are described, which might lead to the development of
network management protocols and a framework that can potentially be
used in military networks.
Note: The term "node" is used at IETF for either a host or router.
The term "unit" or "mobile unit" in military (e.g. Humvees, tanks)
is a unit that contains multiple routers, hosts, and/or other non-IP-
based communication devices.
Scenario: Parking Lot Staging Area:
The Parking Lot Staging Area is the most common network operation
that is currently widely used in military prior to deployment. MANET
routers, which can be identical such as the platoon leader's or
rifleman's radio, are shipped to a remote location along with a Fixed
Network Operations Center (NOC), where they are all connected over
traditional wired or wireless networks. The Fixed NOC then performs
mass-configuration and evaluation of configuration processes. The
same concept can be applied to mobile units. Once all units are
successfully configured, they are ready to be deployed.
+---------+ +----------+
| Fixed |<---+------->| router_1 |
| NOC | | +----------+
+---------+ |
| +----------+
+------->| router_2 |
| +----------+
| 0
| 0
| 0
| +----------+
+------->| router_N |
+----------+
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Figure 1: Parking Lot Staging Area
Scenario: Monitoring with SatCom Reachback:
The Monitoring with SatCom Reachback, which is considered another
possible common scenario to military's network operations, is similar
to the Parking Lot Staging Area. Instead, the Fixed NOC and MANET
routers are connected through a Satellite Communications (SatCom)
network. The Monitoring with SatCom Reachback is a scenario where
MANET routers are augmented with SatCom Reachback capabilities while
On-The-Move (OTM). Vehicles carrying MANET routers support multiple
types of wireless interfaces, including High Capacity Short Range
Radio interfaces as well as Low Capacity OTM SatCom interfaces. The
radio interfaces are the preferred interfaces for carrying data
traffic due to their high capacity, but the range is limiting with
respect to connectivity to a Fixed NOC. Hence, OTM SatCom interfaces
offer a more persistent but lower capacity reachback capability. The
existence of a SatCom persistent Reachback capability offers the NOC
the ability to monitor and manage the MANET routers over the air.
Similarly to the Parking Lot Staging scenario, the same concept can
be applied to mobile units.
--- +--+ ---
/ /---|SC|---/ /
--- +--+ ---
+---------+ |
| Fixed |<---------------------+
| NOC | +--------------|
+---------+ | +-------------------+
| | |
+----------+ | +----------+
| router_1 | +----------+ | router_N |
+----------+ | | +----------+
* | | * *
* +----------+ | * *
*********| router_2 |*****|******* *
+----------+ | *
* | *
* +----------+ *
********| router_3 |****
+----------+
--- SatCom links
*** Radio links
Figure 2: Monitoring with one-hop SatCom Reachback network
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Scenario: Hierarchical Management:
Another reasonable scenario common to military operations in a MANET
environment is the Hierarchical Management scenario. Vehicles carry
a rather complex set of networking devices, including routers running
MANET control protocols. In this hierarchical architecture, the
MANET mobile unit has a rather complex internal architecture where a
local manager within the unit is responsible for local management.
The local management includes management of the MANET router and
control protocols, the firewall, servers, proxies, hosts and
applications. In addition, a standard management interface is
required in this architecture. Moreover, in addition to requiring
standard management interfaces into the components comprising the
MANET nodal architecture, the local manager is responsible for local
monitoring and the generation of periodic reports back to the Fixed
NOC.
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Interface
|
V
+---------+ +-------------------------+
| Fixed | Interface | +---+ +---+ |
| NOC |<---+------->| | R |--+--| F | |
+---------+ | | +---+ | +---+ |
| | | | +---+ |
| | +---+ | +--| P | |
| | | M |--+ | +---+ |
| | +---+ | |
| | | +---+ |
| | +--| D | |
| | | +---+ |
| | | |
| | | +---+ |
| | +--| H | |
| | | +---+ |
| | unit_1 |
| +-------------------------+
|
|
| +--------+
+------->| unit_2 |
| +--------+
| 0
| 0
| 0
| +--------+
+------->| unit_N |
+--------+
Key: R-Router
F-Firewall
P-PEP (Performance Enhancing Proxy)
D-Servers, e.g., DNS
H-hosts
M-Local Manager
Figure 3: Hierarchical Management
Scenario: Management over Lossy/Intermittent Links:
In the future of military operations, the standard management will be
done over lossy and intermittent links and ideally the Fixed NOC will
become mobile. In this architecture, the nature and current quality
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of each link are distinct. However, there are a number of issues
that would arise and need to be addressed:
1. Common and specific configurations are undefined:
A. When mass-configuring devices, common set of configurations
are undefined at this time.
B. Similarly, when performing a specific device, set of specific
configurations is unknown.
2. Once the total number of units becomes quite large, scalability
would be an issue and need to be addressed.
3. The state of the devices are different and may be in various
states of operations, e.g., ON/OFF, etc.
4. Pushing large data files over reliable transport, e.g., TCP,
would be problematic. Would a new mechanism of transmitting
large configurations over the air in low bandwidth be
implemented? Which protocol would be used at transport layer?
5. How to validate network configuration (and local configuration)
is complex, even when to cutover is an interesting question.
6. Security as a general issue needs to be addressed as it could be
problematic in military operations.
+---------+ +----------+
| Mobile |<----------->| router_1 |
| NOC |?--+ +----------+
+---------+ |
^ | +----------+
| +------->| router_2 |
| +----------+
| 0
| 0
| 0
| +----------+
+---------------->| router_N |
+----------+
Figure 4: Management over Lossy/intermittent Links
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3. IANA Considerations
This document does not introduce any new code-points or namespaces
for registration with IANA.
Note to RFC Editor: this section may be removed on publication as an
RFC.
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4. Security Considerations
This document discusses the use cases for a network of constrained
devices and does not introduce any security issues by itself.
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5. Contributors
Following persons made significant contributions to and reviewed this
document:
o Ulrich Herberg (Fujitsu Laboratories of America) contributed the
Section 2.9 on Community Network Applications.
o Peter van der Stok contributed to Section 2.5 on Building
Automation.
o Zhen Cao contributed to Section 2.10 on Mobile Applications.
o Gilman Tolle contributed the Section 2.11 on Automated Metering
Infrastructure.
o James Nguyen and Ulrich Herberg contributed the Section 2.12 on
MANET Concept of Operations (CONOPS) in Military.
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6. Acknowledgments
Following persons reviewed and provided valuable comments to
different versions of this document:
Dominique Barthel, Carsten Bormann, Zhen Cao, Benoit Claise, Bert
Greevenbosch, Ulrich Herberg, James Nguyen, Anuj Sehgal, Zach Shelby,
and Peter van der Stok.
The editors would like to thank the reviewers and the participants on
the Coman maillist for their valuable contributions and comments.
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7. References
7.1. Normative References
7.2. Informative References
[RFC6130] Clausen, T., Dearlove, C., and J. Dean, "Mobile Ad Hoc
Network (MANET) Neighborhood Discovery Protocol (NHDP)",
RFC 6130, April 2011.
[RFC6779] Herberg, U., Cole, R., and I. Chakeres, "Definition of
Managed Objects for the Neighborhood Discovery Protocol",
RFC 6779, October 2012.
[RFC6988] Quittek, J., Chandramouli, M., Winter, R., Dietz, T., and
B. Claise, "Requirements for Energy Management", RFC 6988,
September 2013.
[I-D.ietf-lwig-terminology]
Bormann, C., Ersue, M., and A. Keranen, "Terminology for
Constrained Node Networks", draft-ietf-lwig-terminology-05
(work in progress), July 2013.
[I-D.ietf-eman-framework]
Parello, J., Claise, B., Schoening, B., and J. Quittek,
"Energy Management Framework",
draft-ietf-eman-framework-11 (work in progress),
October 2013.
[I-D.ietf-manet-olsrv2]
Clausen, T., Dearlove, C., Jacquet, P., and U. Herberg,
"The Optimized Link State Routing Protocol version 2",
draft-ietf-manet-olsrv2-19 (work in progress), March 2013.
[COM-REQ] Ersue, M., "Constrained Management: Problem statement and
Requirements", draft-ersue-coman-prostate-reqs (work in
progress), October 2013.
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Appendix A. Open issues
o It has been noted that the use cases the Industrial Application,
Home Automation and Building Automation have an intersect.
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Appendix B. Change Log
B.1. draft-ersue-constrained-mgmt-03 -
draft-ersue-opsawg-coman-use-cases-00
o Reduced the terminology section for terminology addressed in the
LWIG and Coman Requirements drafts. Referenced the other drafts.
o Checked and aligned all terminology against the LWIG terminology
draft.
o Spent some effort to resolve the intersection between the
Industrial Application, Home Automation and Building Automation
use cases.
o Moved section section 3. Use Cases from the companion document
[COM-REQ] to this draft.
o Reformulation of some text parts for more clarity.
B.2. draft-ersue-constrained-mgmt-02-03
o Extended the terminology section and removed some of the
terminology addressed in the new LWIG terminology draft.
Referenced the LWIG terminology draft.
o Moved Section 1.3. on Constrained Device Classes to the new LWIG
terminology draft.
o Class of networks considering the different type of radio and
communication technologies in use and dimensions extended.
o Extended the Problem Statement in Section 2. following the
requirements listed in Section 4.
o Following requirements, which belong together and can be realized
with similar or same kind of solutions, have been merged.
* Distributed Management and Peer Configuration,
* Device status monitoring and Neighbor-monitoring,
* Passive Monitoring and Reactive Monitoring,
* Event-driven self-management - Self-healing and Periodic self-
management,
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* Authentication of management systems and Authentication of
managed devices,
* Access control on devices and Access control on management
systems,
* Management of Energy Resources and Data models for energy
management,
* Software distribution (group-based firmware update) and Group-
based provisioning.
o Deleted the empty section on the gaps in network management
standards, as it will be written in a separate draft.
o Added links to mentioned external pages.
o Added text on OMA M2M Device Classification in appendix.
B.3. draft-ersue-constrained-mgmt-01-02
o Extended the terminology section.
o Added additional text for the use cases concerning deployment
type, network topology in use, network size, network capabilities,
radio technology, etc.
o Added examples for device classes in a use case.
o Added additional text provided by Cao Zhen (China Mobile) for
Mobile Applications and by Peter van der Stok for Building
Automation.
o Added the new use cases 'Advanced Metering Infrastructure' and
'MANET Concept of Operations in Military'.
o Added the section 'Managing the Constrainedness of a Device or
Network' discussing the needs of very constrained devices.
o Added a note that the requirements in [COM-REQ] need to be seen as
standalone requirements and the current document does not
recommend any profile of requirements.
o Added a section in [COM-REQ] for the detailed requirements on
constrained management matched to management tasks like fault,
monitoring, configuration management, Security and Access Control,
Energy Management, etc.
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o Solved nits and added references.
o Added Appendix A on the related development in other bodies.
o Added Appendix B on the work in related research projects.
B.4. draft-ersue-constrained-mgmt-00-01
o Splitted the section on 'Networks of Constrained Devices' into the
sections 'Network Topology Options' and 'Management Topology
Options'.
o Added the use case 'Community Network Applications' and 'Mobile
Applications'.
o Provided a Contributors section.
o Extended the section on 'Medical Applications'.
o Solved nits and added references.
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Authors' Addresses
Mehmet Ersue (editor)
Nokia Solutions and Networks
Email: mehmet.ersue@nsn.com
Dan Romascanu
Avaya
Email: dromasca@avaya.com
Juergen Schoenwaelder
Jacobs University Bremen
Email: j.schoenwaelder@jacobs-university.de
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