Network Working Group L. Feeney
Internet-Draft Uppsala University
Intended status: Informational V. Fodor
Expires: January 4, 2018 KTH
July 03, 2017
Inter-network Coexistence in the Internet of Things
draft-feeney-t2trg-inter-network-00
Abstract
The breadth of IoT applications implies that future wireless
environments will be characterized by the presence of many diverse,
administratively independent IoT networks operating in the same
physical location. In many cases, these networks will use unlicensed
spectrum, due to its low cost and ease of deployment. However, this
spectrum is becoming increasingly crowded. IoT networks will
therefore be subject to wireless interference, both from similar
networks and from networks that use the channel in very different
ways.
To date, there have been few studies or testbeds that fully reflect
this aspect of the future IoT operating environment. This document
describes some of the main issues in network co-existence in IoT
environments, focusing on protocol-level interactions. It identifies
two issues for the IRTF t2trg community. The first is to define best
practices for performance evaluation and protocol design in the
context of inter-network interference. The second is the potential
use of higher layer protocols to actively participate in interference
mitigation.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. IoT interference challenges . . . . . . . . . . . . . . . . . 3
2.1. Scale . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2. Independence . . . . . . . . . . . . . . . . . . . . . . 3
2.3. Battery lifetime . . . . . . . . . . . . . . . . . . . . 4
2.4. Resource constraints . . . . . . . . . . . . . . . . . . 4
2.5. Diversity . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Interaction behaviors . . . . . . . . . . . . . . . . . . . . 5
4. Network co-existence in the IRTF/IETF context . . . . . . . . 6
4.1. Responding to link layer evolution . . . . . . . . . . . 7
4.2. Protocol evaluation . . . . . . . . . . . . . . . . . . . 7
4.3. Active mitigation strategies . . . . . . . . . . . . . . 7
5. Security Considerations . . . . . . . . . . . . . . . . . . . 9
6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 10
7. Informative References . . . . . . . . . . . . . . . . . . . 10
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 11
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 11
1. Introduction
An enormous range of IoT applications are expected to become
pervasive in daily life. Networks will be installed in public
spaces, businesses, and residences by a wide range of individual,
commercial, and government actors. This means that there will be
many diverse, administratively independent networks operating in the
same physical location. For example, a future home environment may
include IoT applications for security, heating and cooling, elder
care, air quality monitoring, personal health and fitness, smart home
appliances, structural monitoring, lighting, utilities, and
entertainment.
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Many of these applications will use unlicensed spectrum due to low
cost and simplicity of deployment for both the user and developer.
In unlicensed spectrum, there is no authority that has a management
relationship with (or even knows about) all of the potentially
interfering networks that can be present in some location. This
means that there is no entity that can coordinate networks' use of
the shared wireless channel. Networks will therefore experience
interference caused by transmissions from devices belonging to other
networks.
Much existing work in inter-network interference is analytic, based
on statistical distributions of interfering waveforms under various
conditions (see e.g. [NIST]). There have also been a few papers
proposing interference mitigation strategies for interference between
specific protocols (see e.g. [SURVEY]), particularly between IEEE
802.11 and IEEE 802.15.4. In general, existing standards and
products tend to rely on frequency agility and low duty cycles to
avoid interference. To date, however, there have been very few
studies or testbeds that fully reflect the complex interference
scenarios of the future IoT environment, particularly in the context
of protocol-level interactions.
2. IoT interference challenges
The widespread deployment and diversity of IoT networks will create
new challenges in managing network coexistence.
2.1. Scale
As IoT becomes pervasive, there may be a large number of networks and
devices operating in any given location. Devices from the various
networks will be topologically inter-mingled. Interaction scenarios
will also be highly dynamic, with mobility leading to frequent
changes in the set of interfering devices.
2.2. Independence
In unlicensed spectrum, there is not necessarily any trust
relationship between networks. Networks with overlapping
transmission footprints may well have been deployed by different
actors (e.g. in adjacent apartments). There is no single authority
that has an administrative relationship with all of the potentially
interfering networks in some location. Devices within a network will
be able to authenticate themselves to each other, but the network
itself may not have any meaningful external identity.
This means that there is no entity that all networks can trust to
coordinate their access to the shared channel.
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2.3. Battery lifetime
For battery-powered devices, maximizing lifetime is essential.
System design is often dominated by the need to minimize device
activity and especially by the need to keep the radio turned off as
much as possible.
This means that there must be some way for senders and receivers to
coordinate their radio operations. These mechanisms often depend
heavily on careful timing of radio operations, in addition to (or
instead of) exchanging control packets. Examples include the
synchronized beacon-enabled PAN, asynchronous wakeup based on low
power listening (e.g. ContikiMAC), and TSCH-based scheduled mesh
(e.g. WirelessHART). This timing dependence means that may be more
sensitive to disruption than might be expected from just considering
overall channel utilization and collision probabilities [FF15].
Battery constraints also severely limit devices' ability to listen to
the channel to observe the behavior of potentially interfering
networks.
2.4. Resource constraints
Iot networks may be severely resource constrained. Channel capacity
and battery limitations have been discussed above. It is also common
that IoT devices have very limited on-board CPU and memory. For many
IoT applications, devices must be very low-cost and easily deployed
and managed by non-expert users. These factors severely constrain
the design space and limit the complexity of any protocol for this
environment.
2.5. Diversity
Although even identical networks experience inter-network
interference, diversity of radios, protocols, and applications
creates additional challenges. This diversity is fundamentally due
to the diversity of the IoT application requirements, and therefore
convergence to a single solution is unlikely.
Different kinds of radios use different modulation schemes to encode
data on the channel, resulting different patterns of radio energy
distributed over time and spectrum. They also divide the spectrum
into channels differently. This means that network devices may not
be able to directly identify the kind of radio that is causing
interference and packet loss. In some cases, it may not be possible
for channel sensing mechanisms to reliably detect the presence of
interfering transmissions.
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Different radio technologies are intended to provide different data
rates, transmission powers, and coverage areas. In 2.4GHz spectrum,
IEEE 802.15.4 is a low power, low data-rate radio; its short (128B)
frames, transmitted at 250kbps, occupy the channel for up to a few
ms.. IEEE 802.11 networks have much higher data rates (10's of Mbps)
and (usually) higher transmit powers. In sub-GHz spectrum, IEEE
802.15.4g/Wi-SUN (smart utility network) radios has data rates 50-200
kbps to communicate over distances of up to ~1km, while LoRa radios
use data rates of <5 kbps to provide communication over 10's of km.
These differences imply large differences in packet transmission
times, which can range from <1 ms to 100's of ms. Timing parameters
in a given MAC layer, such as backoff and retransmission intervals,
tend to be proportional to packet transmission times for the
underlying PHY. This can reduce the effectiveness of backoff
strategies in mixed radio environments, though it can also provide
opportunities for co-existence strategies (e.g. ).
Even where networks use the same radio and PHY they may only share
part of their protocol stack. The range of protocols based on the
IEEE 802.15.4 PHY layer is a case in point. It includes beacon-
enabled star-topologies (with both CSMA and TDMA/GTS modes),
scheduled mesh (e.g. IEEE 802.15.4 TSCH, WirelessHART and ISA
100.11a standards) and decentralized, asynchronous low power MACs
(e.g. ContikiMAC).
Although IP(v6) is widely (though not universally) used in IEEE
802.15.4-based network stacks, there is also considerable diversity
in higher layer protocols. Some networks are unrouted star-
topologies, while others use multi-hop routing protocols, such as RPL
or SmartMesh. There is also diversity in transport protocols (e.g.
TCP, CoAP) and applications (many highly specialized).
IoT networks therefore have a wide range of channel utilization
patterns. These include synchronous and asynchronous wakeup,
periodic announcements and data collection, multi-hop forwarding, and
bursty responses to detected events. Communication requirements also
vary: While few IoT applications are intended as real time control
systems, many are based on "reasonably" reliable and timely delivery
of small amounts of sensor data and control traffic.
3. Interaction behaviors
Interference between WiFi networks is widely observed, especially in
dense residential and urban areas, where there are many independently
deployed networks. Wifi is an example of a strongly homogeneous
interference environment. Most WiFi networks consist of an AP and
associated devices that communicate directly with their AP. This
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simplifies intra-network coordination and tends to create a somewhat
cellular topology. There is also a strong convention for
interference-reducing channel assignments (channels 1, 6, and 11 in
2.4GHz spectrum). Nearly all WiFi devices use the same CSMA-based
MAC and traffic is dominated by one application - media streaming -
which is supported by adaptive mechanisms throughout the protocol
stack. Despite these simplifying factors, interference is still
considered a problem, even by the general public.
2.4GHz spectrum is also a heterogeneous interference environment. A
common scenario will involve high-power, high-traffic WiFi networks
impacting networks based on low-power, low-bitrate radios, such as
IEEE 802.15.4. This case has been widely studied and several
specific protocol variations have been proposed (e.g. [JP14]), but
practical solutions mostly involve identifying and using least
interfered channels. But in places where there is a lot of WiFi
traffic, there may be very few such channels. As a result, the
various low-power IoT networks operating in these areas may be
crowded into a very small number of "good" channels.
This leads to a variety of interactions among IEEE 802.15.4 based
protocols. For example, two networks may allocate TDMA transmission
slots that conflict with each other. This is because it not possible
for independent networks to explicitly coordinate their slot
allocations, while battery constraints make it hard to do a lot of
channel sensing.
Recent results [FF15] show that interference between both TDMA and
CSMA-based IEEE 802.15.4 beacon-enabled PANs can lead to
synchronization/ desynchronization patterns and episodes of severe
packet loss - even when the channel itself is only lightly loaded.
These outages can, in turn, affect the operation of higher-layer
protocols. More generally, this shows the negative impact of
periodic behavior, which is intended to reduce the radio duty cycle
and hence energy consumption.
4. Network co-existence in the IRTF/IETF context
A recent, very broad survey of spectrum sharing research is found in
[SURVEY]. To date, there have been few studies of the interference
scenarios outlined above, particularly at the scale and diversity
that are expected in future IoT scenarios. In addition, there are
very few testbeds or simulation tools that are intended to reflect
the future IoT operating environment.
A discussion of the challenges of testing wireless co-existence for
both licensed and unlicensed spectrum is found in NIST. However,
this document only considers only radio PHY layer interactions.
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There is a substantial need for better understanding of network co-
existence among the most widely used IoT technologies. This is an
open research problem for practical deployment of IoT networks, with
several areas of relevance for IETF/IRTF activities. In particular,
we highlight 1) developing best practices for protocol performance
evaluation and 2) research into higher layer protocols for explicit
network coordination as issues that are particularly relevant to IRTF
t2trg.
4.1. Responding to link layer evolution
Radio technologies and link layer standards will continue to evolve
to provide increased resilience to interference. Such developments
are naturally relevant to IETF activities regarding the definition of
IPv6 over various IoT link layers (e.g. 6low, 6tisch) and closely
related higher layers protocols such as RPL and CoAP.
4.2. Protocol evaluation
Maximizing channel and battery efficiency and minimizing the impact
of both intra- and inter-network interference is largely in the
domain of spectrum regulation and the PHY/MAC layer and therefore
out-of-scope for IETF/IRTF.
Nevertheless, higher-layer protocols are also affected by - and can
contribute to - adverse interactions between networks sharing the
wireless channel. For example, they may have adaptive behaviors or
timing dependencies that are sensitive to patterns of loss and delay
created by inter-network interference. Or they may have periodic or
bursty communication patterns that contribute to adverse
interactions. The performance of existing (and forthcoming) IETF
protocols such as 6LoWPAN, 6tisch, 6lpwan, RPL, and CoAP under
complex IoT interference scenarios is not well understood.
We therefore argue that performance evaluation of IoT protocols
should consider whether they will perform acceptably in the presence
of diverse networks operating in the same spectrum. This is a poorly
understood area and there is a lack of simulation or testbed
environments that provide scale and diversity characteristic of
future IoT environments. Documentation and advocacy of best
practices for protocol evaluation scenarios is therefore relevant to
IRTF t2trg activities.
4.3. Active mitigation strategies
Interference mitigation is likely to rely primarily on improved
resilience and local adaptation in PHY and MAC layer protocols and
(to a lesser extent) in higher layer protocols. However, there may
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be opportunities for high layer protocols to actively participate in
interference mitigation by enabling explicit coordination between
networks.
When two networks use the same radio and channel, it may be possible
for frames transmitted by devices in one network to be successfully
received by devices in other networks. These external frames cannot
be authenticated and are generally discarded at the MAC layer.
However, they might provide a way for networks to exchange signaling
information at the network layer, despite their diverse channel
access or higher-layer protocols. This could be used for devices to
announce their expected channel utilization, for example.
There are substantial challenges in developing such a mechanism:
1) There is an enormous diversity of radios, channel access methods
and utilization patterns that might need to be described. It is not
clear what information should be signaled or what actions a receiver
should take in response.
2) Battery lifetime, channel capacity, and device CPU / memory
resources continue to be significant limitations. In particular, the
radio duty cycle is highly constrained, limiting both sensing and
communication..
3) Any such mechanism must operate effectively in the absence of any
administrative or trust relationship between networks. Any proposed
solution will therefore need to be resilient to the possibility of
incompatible, oblivious, selfish, or even hostile networks
participating (or not) in some mitigation mechanism. (See Security
Considerations.)
4) The privacy implications of networks sharing information about
their activity must be carefully considered. (See Security
Considerations.)
This remains a very open research area and one that we argue is
particularly amenable to standards and interoperability oriented
approaches enabled by IRTF t2trg. There may be synergy with IRTF
t2trg work in IoT semantic interoperability, allowing IoT networks to
describe not only the 'things' they connect, but also themselves.
There may also be synergy with IETF activities (e.g. spud/plus) in
making signaling information available within encrypted flows.
It is also possible to consider the possibility of coordination
between networks that use different radios and cannot exchange
packets Specialized techniques for very simple low bitrate signaling
between networks using different radios have been proposed. It is
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also possible to consider explicit mitigation strategies that enable
information exchange via some service coordinated in the Internet
infrastructure. Inspiration here is from cognitive radio solutions
where secondary users obtain information about activity of primary
users from trusted sources.
5. Security Considerations
This document focuses on co-existence between independently
administrated networks operating in the same location. The biggest
security challenge is therefore that such networks do not necessarily
have any basis for a trust relationship.
Regulations concerning unlicensed spectrum control radio behaviors
such as power spectral density, channelization, or duty cycle. They
do not mandate the use of any specific protocol, nor is it possible
to ensure that a potentially interfering network is correctly
implementing any particular co-existence mechanism.
Any proposed solution will therefore need to be resilient to the
possibility of incompatible, oblivious, selfish, or even hostile
networks participating (or not) in some interference mitigation
mechanism. This is especially true for methods in which networks
actively coordinate their use of the shared channel. At a minimum,
participating in information exchange should not substantially
increase vulnerability to disruption in the case of a malicious (or
merely incompatible) actor.
IoT networks that try to be friendly toward each other may disclose
substantial information about their operation. There are privacy
issues associated with IoT networks making such information visible,
because of their close coupling with human activity. Particularly
for health-related applications, even being able to identify the type
of network application or its level of activity may reveal sensitive
information. Ideally, it should be possible for a network to both
obfuscate its communication patterns (if needed) and to cooperate in
minimizing adverse interactions.
One maxim that may be useful in designing the set of information that
a network discloses as a matter of course with the intention of
facilitating coexistence is that the information disclosed should not
provide more insight than that information an attacker might have
gained by simply observing the network for a while. But note that
simply disclosing that information in an accessible way still changes
the economy of surveillance -- the objective is that it also changes
the economy of coexistence, and these effects need to be carefully
weighed against each other.
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6. Conclusion
Understanding and mitigating the impact of inter-network interference
on performance and reliability is essential for successful large-
scale deployment of IoT solutions. Particularly in residential and
urban environments, high density of WiFi networks will limit the
number of "good" channels available to low-power IoT networks. As a
result, administratively independent IoT networks - possibly with
quite different channel access behavior - are likely to operate on
shared channels.
Potential interactions among these networks are not well understood.
For example: What happens if two or more independent networks using
CoAP over RPL over 6LowPAN (or 6tisch) over IEEE 1802.15.4 are
operating in the same room? What happens if a beacon-enabled PAN (or
a Thread or ZigBee or ContikiMAC network, etc.) is thrown into the
mix? Especially in a WiFi heavy environment, the value of channel
hopping for interference mitigation in IEEE 802.15.4 networks may be
limited. Similarly, how will LPWAN networks such as LoRa and SigFox,
with coverage areas of 10's of km sq., interact with other sub-GHz
networks such as Wi-SUN/IEEE 802.15.4g?
Interference mitigation is largely the domain of spectrum regulation
and the PHY/MAC layers. There are IETF/IRTF interests as well, most
obviously for IoT protocols such as 6LowPAN, 6tisch, RPL, and CoAP.
Two open issues are especially relevant to IRTF t2trg: Many
interference scenarios are not well understood, particularly with
regard to protocol-level interactions. Best practices for
performance evaluation should be developed to reflect future IoT
environments. There may also be opportunities for active
interference mitigation via explicit coordination and information
sharing, topics which are particularly amenable to interoperability
and standards oriented research. However, there are substantial
research challenges.
7. Informative References
[FF15] Feeney, L. and V. Fodor, "Reliability in co-located
802.15.4 personal area networks", Proceedings of the 6th
ACM International Workshop on Pervasive Wireless
Healthcare - MobiHealth '16 , DOI 10.1145/2944921.2944923,
2016.
[IEEE802154]
"IEEE Standard for Low-Rate Wireless Networks",
IEEE standard, DOI 10.1109/ieeestd.2016.7460875, n.d..
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[JP14] Javed, Q. and R. Prakash, "CHAMELEON: A Framework for
Coexistence of Wireless Technologies in an Unlicensed
Band", Wireless Personal Communications Vol. 77, pp.
777-808, DOI 10.1007/s11277-013-1536-7, November 2013.
[NIST] Koepke, G., Young, W., Ladbury, J., and J. Coder,
"Interference and Coexistence of Wireless Systems in
Critical Infrastructure", National Institute of Standards
and Technology report, DOI 10.6028/nist.tn.1885, July
2015.
[SEMINT] Feeney, L., "Exploring semantic interference in
heterogeneous sensor networks", Proceeding of the 1st ACM
international workshop on Heterogeneous sensor and actor
networks - HeterSanet '08 , DOI 10.1145/1374699.1374708,
2008.
[SURVEY] Han, Y., Ekici, E., Kremo, H., and O. Altintas, "Spectrum
sharing methods for the coexistence of multiple RF
systems: A survey", Ad Hoc Networks Vol. 53, pp. 53-78,
DOI 10.1016/j.adhoc.2016.09.009, December 2016.
Acknowledgements
The authors would like to thank Michael Frey, Charalampos Orfanidis,
Martin Jacobsson, and Per Gunningberg for their valuable
collaboration in simulation and measurement studies of inter-network
interference. We would also like to thank Carsten Bormann for his
support and encouragement in preparing this document, particularly
the discussion of security considerations.
Authors' Addresses
Laura Marie Feeney
Uppsala University
Box 337
Uppsala SE-751 05
Sweden
Email: lmfeeney@it.uu.se
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Viktoria Fodor
KTH
Osquldas vaeg 10
Stockholm SE-100 44
Sweden
Email: vjfodor@kth.se
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