Routing Requirements for Urban Low-Power and Lossy Networks
RFC 5548
| Document | Type | RFC - Informational (May 2009) | |
|---|---|---|---|
| Authors | Thomas Watteyne , Tim Winter , Dominique Barthel , Mischa Dohler | ||
| Last updated | 2015-10-14 | ||
| Replaces | draft-dohler-roll-urban-routing-reqs | ||
| RFC stream | Internet Engineering Task Force (IETF) | ||
| Formats | |||
| Reviews | |||
| Additional resources | Mailing list discussion | ||
| Stream | WG state | (None) | |
| Document shepherd | (None) | ||
| IESG | IESG state | RFC 5548 (Informational) | |
| Action Holders |
(None)
|
||
| Consensus boilerplate | Unknown | ||
| Telechat date | (None) | ||
| Responsible AD | Adrian Farrel | ||
| Send notices to | (None) |
RFC 5548
Network Working Group M. Dohler, Ed.
Request for Comments: 5548 CTTC
Category: Informational T. Watteyne, Ed.
BSAC, UC Berkeley
T. Winter, Ed.
Eka Systems
D. Barthel, Ed.
France Telecom R&D
May 2009
Routing Requirements for Urban Low-Power and Lossy Networks
Status of This Memo
This memo provides information for the Internet community. It does
not specify an Internet standard of any kind. Distribution of this
memo is unlimited.
Copyright Notice
Copyright (c) 2009 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents in effect on the date of
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Please review these documents carefully, as they describe your rights
and restrictions with respect to this document.
Abstract
The application-specific routing requirements for Urban Low-Power and
Lossy Networks (U-LLNs) are presented in this document. In the near
future, sensing and actuating nodes will be placed outdoors in urban
environments so as to improve people's living conditions as well as
to monitor compliance with increasingly strict environmental laws.
These field nodes are expected to measure and report a wide gamut of
data (for example, the data required by applications that perform
smart-metering or that monitor meteorological, pollution, and allergy
conditions). The majority of these nodes are expected to communicate
wirelessly over a variety of links such as IEEE 802.15.4, low-power
IEEE 802.11, or IEEE 802.15.1 (Bluetooth), which given the limited
radio range and the large number of nodes requires the use of
suitable routing protocols. The design of such protocols will be
mainly impacted by the limited resources of the nodes (memory,
processing power, battery, etc.) and the particularities of the
outdoor urban application scenarios. As such, for a wireless
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solution for Routing Over Low-Power and Lossy (ROLL) networks to be
useful, the protocol(s) ought to be energy-efficient, scalable, and
autonomous. This documents aims to specify a set of IPv6 routing
requirements reflecting these and further U-LLNs' tailored
characteristics.
Table of Contents
1. Introduction ....................................................3
2. Terminology .....................................................3
2.1. Requirements Language ......................................4
3. Overview of Urban Low-Power and Lossy Networks ..................4
3.1. Canonical Network Elements .................................4
3.1.1. Sensors .............................................4
3.1.2. Actuators ...........................................5
3.1.3. Routers .............................................6
3.2. Topology ...................................................6
3.3. Resource Constraints .......................................7
3.4. Link Reliability ...........................................7
4. Urban LLN Application Scenarios .................................8
4.1. Deployment of Nodes ........................................8
4.2. Association and Disassociation/Disappearance of Nodes ......9
4.3. Regular Measurement Reporting ..............................9
4.4. Queried Measurement Reporting .............................10
4.5. Alert Reporting ...........................................11
5. Traffic Pattern ................................................11
6. Requirements of Urban-LLN Applications .........................13
6.1. Scalability ...............................................13
6.2. Parameter-Constrained Routing .............................13
6.3. Support of Autonomous and Alien Configuration .............14
6.4. Support of Highly Directed Information Flows ..............15
6.5. Support of Multicast and Anycast ..........................15
6.6. Network Dynamicity ........................................16
6.7. Latency ...................................................16
7. Security Considerations ........................................16
8. References .....................................................18
8.1. Normative References ......................................18
8.2. Informative References ....................................18
Appendix A. Acknowledgements .....................................20
Appendix B. Contributors .........................................20
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1. Introduction
This document details application-specific IPv6 routing requirements
for Urban Low-Power and Lossy Networks (U-LLNs). Note that this
document details the set of IPv6 routing requirements for U-LLNs in
strict compliance with the layered IP architecture. U-LLN use cases
and associated routing protocol requirements will be described.
Section 2 defines terminology useful in describing U-LLNs.
Section 3 provides an overview of U-LLN applications.
Section 4 describes a few typical use cases for U-LLN applications
exemplifying deployment problems and related routing issues.
Section 5 describes traffic flows that will be typical for U-LLN
applications.
Section 6 discusses the routing requirements for networks comprising
such constrained devices in a U-LLN environment. These requirements
may overlap with or be derived from other application-specific
requirements documents [ROLL-HOME] [ROLL-INDUS] [ROLL-BUILD].
Section 7 provides an overview of routing security considerations of
U-LLN implementations.
2. Terminology
The terminology used in this document is consistent with and
incorporates that described in "Terminology in Low power And Lossy
Networks" [ROLL-TERM]. This terminology is extended in this document
as follows:
Anycast: Addressing and Routing scheme for forwarding packets to at
least one of the "nearest" interfaces from a group, as
described in RFC4291 [RFC4291] and RFC1546 [RFC1546].
Autonomous: Refers to the ability of a routing protocol to
independently function without requiring any external
influence or guidance. Includes self-configuration and
self-organization capabilities.
DoS: Denial of Service, a class of attack that attempts to cause
resource exhaustion to the detriment of a node or network.
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ISM band: Industrial, Scientific, and Medical band. This is a
region of radio spectrum where low-power, unlicensed
devices may generally be used, with specific guidance from
an applicable local radio spectrum authority.
U-LLN: Urban Low-Power and Lossy Network.
WLAN: Wireless Local Area Network.
2.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
3. Overview of Urban Low-Power and Lossy Networks
3.1. Canonical Network Elements
A U-LLN is understood to be a network composed of three key elements,
i.e.,
1. sensors,
2. actuators, and
3. routers
that communicate wirelessly. The aim of the following sections
(3.1.1, 3.1.2, and 3.1.3) is to illustrate the functional nature of a
sensor, actuator, and router in this context. That said, it must be
understood that these functionalities are not exclusive. A
particular device may act as a simple router or may alternatively be
a router equipped with a sensing functionality, in which case it will
be seen as a "regular" router as far as routing is concerned.
3.1.1. Sensors
Sensing nodes measure a wide gamut of physical data, including but
not limited to:
1. municipal consumption data, such as smart-metering of gas, water,
electricity, waste, etc.;
2. meteorological data, such as temperature, pressure, humidity, UV
index, strength and direction of wind, etc.;
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3. pollution data, such as gases (sulfur dioxide, nitrogen oxide,
carbon monoxide, ozone), heavy metals (e.g., mercury), pH,
radioactivity, etc.;
4. ambient data, such as levels of allergens (pollen, dust),
electromagnetic pollution, noise, etc.
Sensor nodes run applications that typically gather the measurement
data and send it to data collection and processing application(s) on
other node(s) (often outside the U-LLN).
Sensor nodes are capable of forwarding data. Sensor nodes are
generally not mobile in the majority of near-future roll-outs. In
many anticipated roll-outs, sensor nodes may suffer from long-term
resource constraints.
A prominent example is a "smart grid" application that consists of a
city-wide network of smart meters and distribution monitoring
sensors. Smart meters in an urban "smart grid" application will
include electric, gas, and/or water meters typically administered by
one or multiple utility companies. These meters will be capable of
advanced sensing functionalities such as measuring the quality of
electrical service provided to a customer, providing granular
interval data, or automating the detection of alarm conditions. In
addition, they may be capable of advanced interactive
functionalities, which may invoke an actuator component, such as
remote service disconnect or remote demand reset. More advanced
scenarios include demand response systems for managing peak load, and
distribution automation systems to monitor the infrastructure that
delivers energy throughout the urban environment. Sensor nodes
capable of providing this type of functionality may sometimes be
referred to as Advanced Metering Infrastructure (AMI).
3.1.2. Actuators
Actuator nodes are capable of controlling urban devices; examples are
street or traffic lights. They run applications that receive
instructions from control applications on other nodes (possibly
outside the U-LLN). The amount of actuator points is well below the
number of sensing nodes. Some sensing nodes may include an actuator
component, e.g., an electric meter node with integrated support for
remote service disconnect. Actuators are capable of forwarding data.
Actuators are not likely to be mobile in the majority of near-future
roll-outs. Actuator nodes may also suffer from long-term resource
constraints, e.g., in the case where they are battery powered.
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3.1.3. Routers
Routers generally act to close coverage and routing gaps within the
interior of the U-LLN; examples of their use are:
1. prolong the U-LLN's lifetime,
2. balance nodes' energy depletion, and
3. build advanced sensing infrastructures.
There can be several routers supporting the same U-LLN; however, the
number of routers is well below the amount of sensing nodes. The
routers are generally not mobile, i.e., fixed to a random or pre-
planned location. Routers may, but generally do not, suffer from any
form of (long-term) resource constraint, except that they need to be
small and sufficiently cheap. Routers differ from actuator and
sensing nodes in that they neither control nor sense. That being
said, a sensing node or actuator may also be a router within the
U-LLN.
Some routers provide access to wider infrastructures, such as the
Internet, and are named Low-Power and Lossy Network Border Routers
(LBRs) in that context.
LBR nodes in particular may also run applications that communicate
with sensor and actuator nodes (e.g., collecting and processing data
from sensor applications, or sending instructions to actuator
applications).
3.2. Topology
Whilst millions of sensing nodes may very well be deployed in an
urban area, they are likely to be associated with more than one
network. These networks may or may not communicate between one
another. The number of sensing nodes deployed in the urban
environment in support of some applications is expected to be in the
order of 10^2 to 10^7; this is still very large and unprecedented in
current roll-outs.
Deployment of nodes is likely to happen in batches, e.g., boxes of
hundreds to thousands of nodes arrive and are deployed. The location
of the nodes is random within given topological constraints, e.g.,
placement along a road, river, or at individual residences.
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3.3. Resource Constraints
The nodes are highly resource constrained, i.e., cheap hardware, low
memory, and no infinite energy source. Different node powering
mechanisms are available, such as:
1. non-rechargeable battery;
2. rechargeable battery with regular recharging (e.g., sunlight);
3. rechargeable battery with irregular recharging (e.g.,
opportunistic energy scavenging);
4. capacitive/inductive energy provision (e.g., passive Radio
Frequency IDentification (RFID));
5. always on (e.g., powered electricity meter).
In the case of a battery-powered sensing node, the battery shelf life
is usually in the order of 10 to 15 years, rendering network lifetime
maximization with battery-powered nodes beyond this lifespan useless.
The physical and electromagnetic distances between the three key
elements, i.e., sensors, actuators, and routers, can generally be
very large, i.e., from several hundreds of meters to one kilometer.
Not every field node is likely to reach the LBR in a single hop,
thereby requiring suitable routing protocols that manage the
information flow in an energy-efficient manner.
3.4. Link Reliability
The links between the network elements are volatile due to the
following set of non-exclusive effects:
1. packet errors due to wireless channel effects;
2. packet errors due to MAC (Medium Access Control) (e.g.,
collision);
3. packet errors due to interference from other systems;
4. link unavailability due to network dynamicity; etc.
The wireless channel causes the received power to drop below a given
threshold in a random fashion, thereby causing detection errors in
the receiving node. The underlying effects are path loss, shadowing
and fading.
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Since the wireless medium is broadcast in nature, nodes in their
communication radios require suitable medium access control protocols
that are capable of resolving any arising contention. Some available
protocols may not be able to prevent packets of neighboring nodes
from colliding, possibly leading to a high Packet Error Rate (PER)
and causing a link outage.
Furthermore, the outdoor deployment of U-LLNs also has implications
for the interference temperature and hence link reliability and range
if Industrial, Scientific, and Medical (ISM) bands are to be used.
For instance, if the 2.4 GHz ISM band is used to facilitate
communication between U-LLN nodes, then heavily loaded Wireless Local
Area Network (WLAN) hot-spots may become a detrimental performance
factor, leading to high PER and jeopardizing the functioning of the
U-LLN.
Finally, nodes appearing and disappearing causes dynamics in the
network that can yield link outages and changes of topologies.
4. Urban LLN Application Scenarios
Urban applications represent a special segment of LLNs with its
unique set of requirements. To facilitate the requirements
discussion in Section 6, this section lists a few typical but not
exhaustive deployment problems and usage cases of U-LLN.
4.1. Deployment of Nodes
Contrary to other LLN applications, deployment of nodes is likely to
happen in batches out of a box. Typically, hundreds to thousands of
nodes are being shipped by the manufacturer with pre-programmed
functionalities which are then rolled-out by a service provider or
subcontracted entities. Prior to or after roll-out, the network
needs to be ramped-up. This initialization phase may include, among
others, allocation of addresses, (possibly hierarchical) roles in the
network, synchronization, determination of schedules, etc.
If initialization is performed prior to roll-out, all nodes are
likely to be in one another's one-hop radio neighborhood. Pre-
programmed Media Access Control (MAC) and routing protocols may hence
fail to function properly, thereby wasting a large amount of energy.
Whilst the major burden will be on resolving MAC conflicts, any
proposed U-LLN routing protocol needs to cater for such a case. For
instance, zero-configuration and network address allocation needs to
be properly supported, etc.
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After roll-out, nodes will have a finite set of one-hop neighbors,
likely of low cardinality (in the order of 5 to 10). However, some
nodes may be deployed in areas where there are hundreds of
neighboring devices. In the resulting topology, there may be regions
where many (redundant) paths are possible through the network. Other
regions may be dependent on critical links to achieve connectivity
with the rest of the network. Any proposed LLN routing protocol
ought to support the autonomous self-organization and self-
configuration of the network at lowest possible energy cost [Lu2007],
where autonomy is understood to be the ability of the network to
operate without external influence. The result of such organization
should be that each node or set of nodes is uniquely addressable so
as to facilitate the set up of schedules, etc.
Unless exceptionally needed, broadcast forwarding schemes are not
advised in urban sensor networking environments.
4.2. Association and Disassociation/Disappearance of Nodes
After the initialization phase and possibly some operational time,
new nodes may be injected into the network as well as existing nodes
removed from the network. The former might be because a removed node
is replaced as part of maintenance, or new nodes are added because
more sensors for denser readings/actuations are needed, or because
routing protocols report connectivity problems. The latter might be
because a node's battery is depleted, the node is removed for
maintenance, the node is stolen or accidentally destroyed, etc.
The protocol(s) hence should be able to convey information about
malfunctioning nodes that may affect or jeopardize the overall
routing efficiency, so that self-organization and self-configuration
capabilities of the sensor network might be solicited to facilitate
the appropriate reconfiguration. This information may include, e.g.,
exact or relative geographical position, etc. The reconfiguration
may include the change of hierarchies, routing paths, packet
forwarding schedules, etc. Furthermore, to inform the LBR(s) of the
node's arrival and association with the network as well as freshly
associated nodes about packet forwarding schedules, roles, etc.,
appropriate updating mechanisms should be supported.
4.3. Regular Measurement Reporting
The majority of sensing nodes will be configured to report their
readings on a regular basis. The frequency of data sensing and
reporting may be different but is generally expected to be fairly
low, i.e., in the range of once per hour, per day, etc. The ratio
between data sensing and reporting frequencies will determine the
memory and data aggregation capabilities of the nodes. Latency of an
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end-to-end delivery and acknowledgements of a successful data
delivery may not be vital as sensing outages can be observed at data
collection applications -- when, for instance, there is no reading
arriving from a given sensor or cluster of sensors within a day. In
this case, a query can be launched to check upon the state and
availability of a sensing node or sensing cluster.
It is not uncommon to gather data on a few servers located outside of
the U-LLN. In such cases, a large number of highly directional
unicast flows from the sensing nodes or sensing clusters are likely
to transit through a LBR. Thus, the protocol(s) should be optimized
to support a large number of unicast flows from the sensing nodes or
sensing clusters towards a LBR, or highly directed multicast or
anycast flows from the nodes towards multiple LBRs.
Route computation and selection may depend on the transmitted
information, the frequency of reporting, the amount of energy
remaining in the nodes, the recharging pattern of energy-scavenged
nodes, etc. For instance, temperature readings could be reported
every hour via one set of battery-powered nodes, whereas air quality
indicators are reported only during the daytime via nodes powered by
solar energy. More generally, entire routing areas may be avoided
(e.g., at night) but heavily used during the day when nodes are
scavenging energy from sunlight.
4.4. Queried Measurement Reporting
Occasionally, network-external data queries can be launched by one or
several applications. For instance, it is desirable to know the
level of pollution at a specific point or along a given road in the
urban environment. The queries' rates of occurrence are not regular
but rather random, where heavy-tail distributions seem appropriate to
model their behavior. Queries do not necessarily need to be reported
back to the same node from where the query was launched. Round-trip
times, i.e., from the launch of a query from a node until the
delivery of the measured data to a node, are of importance. However,
they are not very stringent where latencies should simply be
sufficiently smaller than typical reporting intervals; for instance,
in the order of seconds or minutes. The routing protocol(s) should
consider the selection of paths with appropriate (e.g., latency)
metrics to support queried measurement reporting. To facilitate the
query process, U-LLN devices should support unicast and multicast
routing capabilities.
The same approach is also applicable for schedule update,
provisioning of patches and upgrades, etc. In this case, however,
the provision of acknowledgements and the support of unicast,
multicast, and anycast are of importance.
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4.5. Alert Reporting
Rarely, the sensing nodes will measure an event that classifies as an
alarm where such a classification is typically done locally within
each node by means of a pre-programmed or prior-diffused threshold.
Note that on approaching the alert threshold level, nodes may wish to
change their sensing and reporting cycles. An alarm is likely being
registered by a plurality of sensing nodes where the delivery of a
single alert message with its location of origin suffices in most,
but not all, cases. One example of alert reporting is if the level
of toxic gases rises above a threshold; thereupon, the sensing nodes
in the vicinity of this event report the danger. Another example of
alert reporting is when a recycling glass container -- equipped with
a sensor measuring its level of occupancy -- reports that the
container is full and hence needs to be emptied.
Routes clearly need to be unicast (towards one LBR) or multicast
(towards multiple LBRs). Delays and latencies are important;
however, for a U-LLN deployed in support of a typical application,
deliveries within seconds should suffice in most of the cases.
5. Traffic Pattern
Unlike traditional ad hoc networks, the information flow in U-LLNs is
highly directional. There are three main flows to be distinguished:
1. sensed information from the sensing nodes to applications outside
the U-LLN, going through one or a subset of the LBR(s);
2. query requests from applications outside the U-LLN, going through
the LBR(s) towards the sensing nodes;
3. control information from applications outside the U-LLN, going
through the LBR(s) towards the actuators.
Some of the flows may need the reverse route for delivering
acknowledgements. Finally, in the future, some direct information
flows between field devices without LBRs may also occur.
Sensed data is likely to be highly correlated in space, time, and
observed events; an example of the latter is when temperature
increase and humidity decrease as the day commences. Data may be
sensed and delivered at different rates with both rates being
typically fairly low, i.e., in the range of minutes, hours, days,
etc. Data may be delivered regularly according to a schedule or a
regular query; it may also be delivered irregularly after an
externally triggered query; it may also be triggered after a sudden
network-internal event or alert. Schedules may be driven by, for
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example, a smart-metering application where data is expected to be
delivered every hour, or an environmental monitoring application
where a battery-powered node is expected to report its status at a
specific time once a day. Data delivery may trigger acknowledgements
or maintenance traffic in the reverse direction. The network hence
needs to be able to adjust to the varying activity duty cycles, as
well as to periodic and sporadic traffic. Also, sensed data ought to
be secured and locatable.
Some data delivery may have tight latency requirements, for example,
in a case such as a live meter reading for customer service in a
smart-metering application, or in a case where a sensor reading
response must arrive within a certain time in order to be useful.
The network should take into consideration that different application
traffic may require different priorities in the selection of a route
when traversing the network, and that some traffic may be more
sensitive to latency.
A U-LLN should support occasional large-scale traffic flows from
sensing nodes through LBRs (to nodes outside the U-LLN), such as
system-wide alerts. In the example of an AMI U-LLN, this could be in
response to events such as a city-wide power outage. In this
scenario, all powered devices in a large segment of the network may
have lost power and be running off of a temporary "last gasp" source
such as a capacitor or small battery. A node must be able to send
its own alerts toward an LBR while continuing to forward traffic on
behalf of other devices that are also experiencing an alert
condition. The network needs to be able to manage this sudden large
traffic flow.
A U-LLN may also need to support efficient large-scale messaging to
groups of actuators. For example, an AMI U-LLN supporting a city-
wide demand response system will need to efficiently broadcast
demand-response control information to a large subset of actuators in
the system.
Some scenarios will require internetworking between the U-LLN and
another network, such as a home network. For example, an AMI
application that implements a demand-response system may need to
forward traffic from a utility, across the U-LLN, into a home
automation network. A typical use case would be to inform a customer
of incentives to reduce demand during peaks, or to automatically
adjust the thermostat of customers who have enrolled in such a demand
management program. Subsequent traffic may be triggered to flow back
through the U-LLN to the utility.
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6. Requirements of Urban-LLN Applications
Urban Low-Power and Lossy Network applications have a number of
specific requirements related to the set of operating conditions, as
exemplified in the previous sections.
6.1. Scalability
The large and diverse measurement space of U-LLN nodes -- coupled
with the typically large urban areas -- will yield extremely large
network sizes. Current urban roll-outs are composed of sometimes
more than one hundred nodes; future roll-outs, however, may easily
reach numbers in the tens of thousands to millions. One of the
utmost important LLN routing protocol design criteria is hence
scalability.
The routing protocol(s) MUST be capable of supporting the
organization of a large number of sensing nodes into regions
containing on the order of 10^2 to 10^4 sensing nodes each.
The routing protocol(s) MUST be scalable so as to accommodate a very
large and increasing number of nodes without deteriorating selected
performance parameters below configurable thresholds. The routing
protocols(s) SHOULD support the organization of a large number of
nodes into regions of configurable size.
6.2. Parameter-Constrained Routing
Batteries in some nodes may deplete quicker than in others; the
existence of one node for the maintenance of a routing path may not
be as important as of another node; the energy-scavenging methods may
recharge the battery at regular or irregular intervals; some nodes
may have a constant power source; some nodes may have a larger memory
and are hence be able to store more neighborhood information; some
nodes may have a stronger CPU and are hence able to perform more
sophisticated data aggregation methods, etc.
To this end, the routing protocol(s) MUST support parameter-
constrained routing, where examples of such parameters (CPU, memory
size, battery level, etc.) have been given in the previous paragraph.
In other words, the routing protocol MUST be able to advertise node
capabilities that will be exclusively used by the routing protocol
engine for routing decision. For the sake of example, such a
capability could be related to the node capability itself (e.g.,
remaining power) or some application that could influence routing
(e.g., capability to aggregate data).
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Routing within urban sensor networks SHOULD require the U-LLN nodes
to dynamically compute, select, and install different paths towards
the same destination, depending on the nature of the traffic. Such
functionality in support of, for example, data aggregation, may imply
use of some mechanisms to mark/tag the traffic for appropriate
routing decision using the IPv6 packet format (e.g., use of Diffserv
Code Point (DSCP), Flow Label) based on an upper-layer marking
decision. From this perspective, such nodes MAY use node
capabilities (e.g., to act as an aggregator) in conjunction with the
anycast endpoints and packet marking to route the traffic.
6.3. Support of Autonomous and Alien Configuration
With the large number of nodes, manually configuring and
troubleshooting each node is not efficient. The scale and the large
number of possible topologies that may be encountered in the U-LLN
encourages the development of automated management capabilities that
may (partly) rely upon self-organizing techniques. The network is
expected to self-organize and self-configure according to some prior
defined rules and protocols, as well as to support externally
triggered configurations (for instance, through a commissioning tool
that may facilitate the organization of the network at a minimum
energy cost).
To this end, the routing protocol(s) MUST provide a set of features
including zero-configuration at network ramp-up, (network-internal)
self-organization and configuration due to topological changes, and
the ability to support (network-external) patches and configuration
updates. For the latter, the protocol(s) MUST support multicast and
anycast addressing. The protocol(s) SHOULD also support the
formation and identification of groups of field devices in the
network.
The routing protocol(s) SHOULD be able to dynamically adapt, e.g.,
through the application of appropriate routing metrics, to ever-
changing conditions of communication (possible degradation of quality
of service (QoS), variable nature of the traffic (real-time versus
non-real-time, sensed data versus alerts), node mobility, a
combination thereof, etc.).
The routing protocol(s) SHOULD be able to dynamically compute,
select, and possibly optimize the (multiple) path(s) that will be
used by the participating devices to forward the traffic towards the
actuators and/or a LBR according to the service-specific and traffic-
specific QoS, traffic engineering, and routing security policies that
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will have to be enforced at the scale of a routing domain (that is, a
set of networking devices administered by a globally unique entity),
or a region of such domain (e.g., a metropolitan area composed of
clusters of sensors).
6.4. Support of Highly Directed Information Flows
As pointed out in Section 4.3, it is not uncommon to gather data on a
few servers located outside of the U-LLN. In this case, the
reporting of the data readings by a large amount of spatially
dispersed nodes towards a few LBRs will lead to highly directed
information flows. For instance, a suitable addressing scheme can be
devised that facilitates the data flow. Also, as one gets closer to
the LBR, the traffic concentration increases, which may lead to high
load imbalances in node usage.
To this end, the routing protocol(s) SHOULD support and utilize the
large number of highly directed traffic flows to facilitate
scalability and parameter-constrained routing.
The routing protocol MUST be able to accommodate traffic bursts by
dynamically computing and selecting multiple paths towards the same
destination.
6.5. Support of Multicast and Anycast
Routing protocols activated in urban sensor networks MUST support
unicast (traffic is sent to a single field device), multicast
(traffic is sent to a set of devices that are subscribed to the same
multicast group), and anycast (where multiple field devices are
configured to accept traffic sent on a single IP anycast address)
transmission schemes.
The support of unicast, multicast, and anycast also has an
implication on the addressing scheme, but it is beyond the scope of
this document that focuses on the routing requirements.
Some urban sensing systems may require low-level addressing of a
group of nodes in the same subnet, or for a node representative of a
group of nodes, without any prior creation of multicast groups. Such
addressing schemes, where a sender can form an addressable group of
receivers, are not currently supported by IPv6, and not further
discussed in this specification [ROLL-HOME].
The network SHOULD support internetworking when identical protocols
are used, while giving attention to routing security implications of
interfacing, for example, a home network with a utility U-LLN. The
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network may support the ability to interact with another network
using a different protocol, for example, by supporting route
redistribution.
6.6. Network Dynamicity
Although mobility is assumed to be low in urban LLNs, network
dynamicity due to node association, disassociation, and
disappearance, as well as long-term link perturbations is not
negligible. This in turn impacts reorganization and reconfiguration
convergence as well as routing protocol convergence.
To this end, local network dynamics SHOULD NOT impact the entire
network to be reorganized or re-reconfigured; however, the network
SHOULD be locally optimized to cater for the encountered changes.
The routing protocol(s) SHOULD support appropriate mechanisms in
order to be informed of the association, disassociation, and
disappearance of nodes. The routing protocol(s) SHOULD support
appropriate updating mechanisms in order to be informed of changes in
connectivity. The routing protocol(s) SHOULD use this information to
initiate protocol-specific mechanisms for reorganization and
reconfiguration as necessary to maintain overall routing efficiency.
Convergence and route establishment times SHOULD be significantly
lower than the smallest reporting interval.
Differentiation SHOULD be made between node disappearance, where the
node disappears without prior notification, and user- or node-
initiated disassociation ("phased-out"), where the node has enough
time to inform the network about its pending removal.
6.7. Latency
With the exception of alert-reporting solutions and (to a certain
extent) queried reporting, U-LLNs are delay tolerant as long as the
information arrives within a fraction of the smallest reporting
interval, e.g., a few seconds if reporting is done every 4 hours.
The routing protocol(s) SHOULD also support the ability to route
according to different metrics (one of which could, e.g., be
latency).
7. Security Considerations
As every network, U-LLNs are exposed to routing security threats that
need to be addressed. The wireless and distributed nature of these
networks increases the spectrum of potential routing security
threats. This is further amplified by the resource constraints of
the nodes, thereby preventing resource-intensive routing security
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approaches from being deployed. A viable routing security approach
SHOULD be sufficiently lightweight that it may be implemented across
all nodes in a U-LLN. These issues require special attention during
the design process, so as to facilitate a commercially attractive
deployment.
The U-LLN MUST deny any node that has not been authenticated to the
U-LLN and authorized to participate to the routing decision process.
An attacker SHOULD be prevented from manipulating or disabling the
routing function, for example, by compromising routing control
messages. To this end, the routing protocol(s) MUST support message
integrity.
Further examples of routing security issues that may arise are the
abnormal behavior of nodes that exhibit an egoistic conduct, such as
not obeying network rules or forwarding no or false packets. Other
important issues may arise in the context of denial-of-service (DoS)
attacks, malicious address space allocations, advertisement of
variable addresses, a wrong neighborhood, etc. The routing
protocol(s) SHOULD support defense against DoS attacks and other
attempts to maliciously or inadvertently cause the mechanisms of the
routing protocol(s) to over-consume the limited resources of LLN
nodes, e.g., by constructing forwarding loops or causing excessive
routing protocol overhead traffic, etc.
The properties of self-configuration and self-organization that are
desirable in a U-LLN introduce additional routing security
considerations. Mechanisms MUST be in place to deny any node that
attempts to take malicious advantage of self-configuration and self-
organization procedures. Such attacks may attempt, for example, to
cause DoS, drain the energy of power-constrained devices, or to
hijack the routing mechanism. A node MUST authenticate itself to a
trusted node that is already associated with the U-LLN before the
former can take part in self-configuration or self-organization. A
node that has already authenticated and associated with the U-LLN
MUST deny, to the maximum extent possible, the allocation of
resources to any unauthenticated peer. The routing protocol(s) MUST
deny service to any node that has not clearly established trust with
the U-LLN.
Consideration SHOULD be given to cases where the U-LLN may interface
with other networks such as a home network. The U-LLN SHOULD NOT
interface with any external network that has not established trust.
The U-LLN SHOULD be capable of limiting the resources granted in
support of an external network so as not to be vulnerable to DoS.
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With low computation power and scarce energy resources, U-LLNs' nodes
may not be able to resist any attack from high-power malicious nodes
(e.g., laptops and strong radios). However, the amount of damage
generated to the whole network SHOULD be commensurate with the number
of nodes physically compromised. For example, an intruder taking
control over a single node SHOULD NOT be able to completely deny
service to the whole network.
In general, the routing protocol(s) SHOULD support the implementation
of routing security best practices across the U-LLN. Such an
implementation ought to include defense against, for example,
eavesdropping, replay, message insertion, modification, and man-in-
the-middle attacks.
The choice of the routing security solutions will have an impact on
the routing protocol(s). To this end, routing protocol(s) proposed
in the context of U-LLNs MUST support authentication and integrity
measures and SHOULD support confidentiality (routing security)
measures.
8. References
8.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
8.2. Informative References
[Lu2007] Lu, JL., Valois, F., Barthel, D., and M. Dohler,
"FISCO: A Fully Integrated Scheme of Self-Configuration
and Self-Organization for WSN", 11-15 March 2007,
pp. 3370-3375, IEEE WCNC 2007, Hong Kong, China.
[RFC1546] Partridge, C., Mendez, T., and W. Milliken, "Host
Anycasting Service", RFC 1546, November 1993.
[RFC4291] Hinden, R. and S. Deering, "IP Version 6 Addressing
Architecture", RFC 4291, February 2006.
[ROLL-BUILD] Martocci, J., Ed., De Mil, P., Vermeylen, W., and N.
Riou, "Building Automation Routing Requirements in Low
Power and Lossy Networks", Work in Progress,
February 2009.
[ROLL-HOME] Brandt, A. and G. Porcu, "Home Automation Routing
Requirements in Low Power and Lossy Networks", Work
in Progress, November 2008.
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[ROLL-INDUS] Pister, K., Ed., Thubert, P., Ed., Dwars, S., and T.
Phinney, "Industrial Routing Requirements in Low Power
and Lossy Networks", Work in Progress, April 2009.
[ROLL-TERM] Vasseur, J., "Terminology in Low power And Lossy
Networks", Work in Progress, October 2008.
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Appendix A. Acknowledgements
The in-depth feedback of JP Vasseur, Jonathan Hui, Iain Calder, and
Pasi Eronen is greatly appreciated.
Appendix B. Contributors
Christian Jacquenet
France Telecom R&D
4 rue du Clos Courtel BP 91226
35512 Cesson Sevigne
France
EMail: christian.jacquenet@orange-ftgroup.com
Giyyarpuram Madhusudan
France Telecom R&D
28 Chemin du Vieux Chene
38243 Meylan Cedex
France
EMail: giyyarpuram.madhusudan@orange-ftgroup.com
Gabriel Chegaray
France Telecom R&D
28 Chemin du Vieux Chene
38243 Meylan Cedex
France
EMail: gabriel.chegaray@orange-ftgroup.com
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Authors' Addresses
Mischa Dohler (editor)
CTTC
Parc Mediterrani de la Tecnologia
Av. Canal Olimpic S/N
08860 Castelldefels, Barcelona
Spain
EMail: mischa.dohler@cttc.es
Thomas Watteyne (editor)
Berkeley Sensor & Actuator Center, University of California, Berkeley
497 Cory Hall #1774
Berkeley, CA 94720-1774
USA
EMail: watteyne@eecs.berkeley.edu
Tim Winter (editor)
Eka Systems
20201 Century Blvd. Suite 250
Germantown, MD 20874
USA
EMail: wintert@acm.org
Dominique Barthel (editor)
France Telecom R&D
28 Chemin du Vieux Chene
38243 Meylan Cedex
France
EMail: Dominique.Barthel@orange-ftgroup.com
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