Internet DRAFT - draft-feeney-t2trg-inter-network
draft-feeney-t2trg-inter-network
Network Working Group L. Feeney
Internet-Draft Uppsala University
Intended status: Informational V. Fodor
Expires: November 26, 2018 KTH
May 25, 2018
Inter-network Coexistence in the Internet of Things
draft-feeney-t2trg-inter-network-03
Abstract
The breadth of IoT applications implies that there will be many
diverse, administratively independent 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 wireless channel in very
different ways.
High-density, heterogeneous wireless environments present formidable
challenges for network coexistence. The PHY and MAC layers are
primarily responsible for managing how radios use the channel. But
higher layer protocols are also a key factor in inter-network
interaction. To date, there have been few performance studies of
coexistence in future IoT operating environments, particularly with
respect to protocol behavior and network-scale interactions.
This document describes key challenges for coexistence and highlights
some recent research results that demonstrate the impact of protocol
level interactions on network performance. It identifies both
concrete and speculative opportunities for the IRTF T2TRG community.
The former include developing and documenting best practices for
performance evaluation and contributing IoT-related protocols being
developed within IETF. The latter include speculative research into
the design of high-layer protocols that allow networks to actively
coordinate their access to the shared channel.
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. IoT interaction challenges . . . . . . . . . . . . . . . . . 5
2.1. Scale . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2. Independence . . . . . . . . . . . . . . . . . . . . . . 5
2.3. Resource limitations . . . . . . . . . . . . . . . . . . 5
2.4. Diversity . . . . . . . . . . . . . . . . . . . . . . . . 6
2.4.1. Radio and PHY . . . . . . . . . . . . . . . . . . . . 6
2.4.2. Network structures . . . . . . . . . . . . . . . . . 7
2.4.3. Protocols . . . . . . . . . . . . . . . . . . . . . . 7
3. Interaction behaviors . . . . . . . . . . . . . . . . . . . . 9
3.1. WiFi . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.2. IEEE 802.15.4 . . . . . . . . . . . . . . . . . . . . . . 10
3.3. Recent results in IoT networks . . . . . . . . . . . . . 10
3.4. Higher layer protocols . . . . . . . . . . . . . . . . . 11
4. Network coexistence in the IRTF/IETF context . . . . . . . . 11
4.1. Performance evaluation and protocol design . . . . . . . 12
4.2. Adaptive mitigation strategies . . . . . . . . . . . . . 13
4.3. Active mitigation strategies . . . . . . . . . . . . . . 14
4.4. Role of Spectrum Regulation . . . . . . . . . . . . . . . 15
5. Security Considerations . . . . . . . . . . . . . . . . . . . 16
6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 17
7. Informative References . . . . . . . . . . . . . . . . . . . 18
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 20
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 20
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1. Introduction
An IoT application is a set of wireless devices that act together to
perform some sensing and control function. Most applications also
have some connectivity to external resources, such as a mobile app or
cloud-based service. In general, each application is deployed
independently of any other applications that may be operating in the
area and is a physically and administratively separate network.
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. As a result, 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.
Many of these networks 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.
The PHY and MAC layers have primary responsibility for ensuring that
devices share the channel efficiently, while spectrum regulations
limit devices' output power and overall channel utilization. But the
MAC protocol can only explicitly coordinate devices within a single
network. It provides only limited protection from other networks,
some of which may have very different transmission footprints over
time, spectrum or physical space.
Network coexistence is mainly evaluated in terms of PHY layer and
radio hardware resilience to interference. This is generally based
on analytic modeling of the probability of successful packet
reception for varying SNIR conditions or on carefully controlled
measurements of interacting RF waveforms. (See e.g. [NIST] for a
discussion of relevant issues and [SKH11] for an example of such an
analysis for IEEE 802.15.4g.)
Analytic modeling of network interactions at the MAC layer is much
harder, because each network adapts its transmission parameters and
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timing in response to the others. The presence of interfering
networks is usually modeled as increasing the intensity of some
statistical process representing noise or loss. Testbed tools, such
as JamLab, have also been used to generate controlled interference.
Other studies are based on simulation or testbed measurements of
simple scenarios. The research literature contains a number of such
studies, especially for IEEE 802.11 and IEEE 802.15.4. (See [SURVEY]
and [SURVEY2] for an overview.)
In practice, currently deployed networks mostly rely on low IoT
traffic loads and careful channel selection to achieve adequate
performance. This may not be sustainable as rapid growth in IoT (and
mobile data offloading) lead to increasing pressure on unlicensed
spectrum. There are very few studies that evaluate complex,
heterogeneous IoT interference scenarios, particularly with regard to
protocol behavior and network-scale interactions. But as recent work
[WETZ17] demonstrates, real world instances of IoT interference do
occur and require considerable effort to diagnose.
This document explores key challenges for network coexistence in
future IoT environments and highlights some recent research results
([FF16], [F3G15], [YTB17]). These suggest that protocol level
interactions can significantly affect network performance, even in
simple scenarios where the channel is not heavily loaded. Higher
layer protocols will need to be aware of the potential impact of
inter-network interference and avoid contributing to adverse
interactions.
The community does not yet have a solid understanding of the
reliability and effectiveness of IoT protocols in the presence of
inter-network interference. In part, this is because the tools and
techniques for performance evaluation of network coexistence
scenarios are still immature. This document considers some of the
challenges and requirements for both simulation and testbed
approaches.
We also identify both concrete and speculative areas where T2TRG is
well-positioned to contribute: The former includes the development of
best practices for performance evaluation and informing the ongoing
development of IoT-related protocols being developed within the IETF.
The latter includes speculative research into the development of
protocols that allow independent networks to actively coordinate
their use of the shared wireless channel.
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2. IoT interaction challenges
Widespread deployment of diverse IoT applications presents four main
challenges: 1) scale 2) lack of a trust relationship between
independently deployed networks 3) resource limitations, especially
battery capacity 4) diversity of application requirements and channel
utilization behavior.
2.1. Scale
As IoT becomes pervasive, there will be many independent networks
operating in any given location. Devices will experience high levels
of both homogeneous and heterogeneous radio interference.
Since networks use different kinds of radios and have different
wireless coverage areas, their topologies will overlap with each
other in complex ways. Interference will therefore involve not just
individual wireless links, but also larger regions in the network and
protocols operating at network scale.
Interaction scenarios will also be highly dynamic, with mobility and
user activity leading to frequent changes in the set of interfering
devices.
2.2. Independence
In unlicensed spectrum, there is no obvious basis for an
administrative relationship between networks. Networks with
overlapping wireless coverage may well have been deployed by at
different times by unrelated actors. Nor is there any common
authority that has an administrative relationship with all of the
potentially interfering networks in any given location.
This means that there is no external entity that networks can trust
to coordinate access to the shared channel. Devices within any one
network will be able to authenticate themselves to each other and
their own administrator (usually a non-expert user). But there is no
way for them to authenticate themselves to each other - an IoT
network may not have any meaningful external identity. Even if two
networks can exchange this information, there is no obvious way for
each to determine whether the other will participate appropriately
with respect to some coexistence mechanism.
2.3. Resource limitations
IoT networks are severely resource constrained in many respects,
including channel capacity, energy, hardware capabilities and cost.
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The large number of devices sharing the wireless channel naturally
limits the capacity available to each device. In addition, many
devices use low bit-rate radios, which further reduces the
communication capacity. (Note, however, that adverse interactions
between networks can occur even in cases where the channel is only
lightly used.)
For energy-harvesting and battery-powered devices, maximizing
lifetime is essential. Protocol design is dominated by the need to
minimize device activity and especially by the need to keep the
energy-hungry radio turned off as much as possible, while still
maintaining necessary connectivity. Even sensing the channel
conditions is an extremely expensive operation. This limits
networks' ability to observe and adapt to the behavior of their
neighbors.
Finally, for many IoT applications, devices must be low cost and
easily deployed and managed by non-expert users. They often have
very limited memory and CPU resources. These factors constrain the
design space and limit the complexity of proposed solutions.
2.4. Diversity
Even networks that use the same radio hardware and protocols will
interfere with each other. But the diversity of IoT radios,
protocols and applications creates additional challenges. Even
characterizing the space of possible interactions may be challenging:
Protocols can be anything from freely available, to consortia-driven
standards such as ZigBee or WirelessHART, to completely proprietary.
This diversity is driven by the diversity of IoT applications.
Applications will differ significantly in their devices'
communication range and the overall network coverage area. They will
vary in the number of devices and traffic load. They will have
different requirements for latency and reliability. And they will
use different energy sources and have different requirements on
energy efficiency and lifetime. To meet these requirements,
applications will use a wide variety of radios, protocols and network
structures.
2.4.1. Radio and PHY
Different radio technologies divide the spectrum into channels
differently: In the 2.4GHz unlicensed band, for example, IEEE 802.11
has up to 14 overlapping channels, while IEEE 802.15.4 and
BluetoothLE have 16 and 40 non-overlapping ones. Radios also use a
variety of modulation techniques at the PHY layer to define how data
is encoded on the channel as RF energy.
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This means that there are many different ways that RF energy is
distributed over time and spectrum. As a result, it may not be
possible for channel sensing mechanisms to reliably detect the
presence of potentially interfering transmissions or identify the
source of interference and packet loss.
Each PHY layer makes different tradeoffs between transmit power,
communication range, bit-rate, bandwidth, energy consumption and
resilience. In sub-GHz spectrum, for example, IEEE 802.15.4g/Wi-SUN
(smart utility network) provides 50-200 kbps bit-rates with ranges of
> 1000m. Very low power EnOcean devices provide similar bit-rates,
but ranges of < 100m. By contrast, LoRa provides bit-rates of at
most a few kbps, but can obtain 10km of range. Differences in bit-
rate and frame size mean that packet transmit times can range from <
10 ms to > 200 ms. Radios operating in 2.4GHz, such as IEEE
802.15.4, IEEE 802.11 and Bluetooth, show similar diversity.
2.4.2. Network structures
Along with different kinds of radios, different kinds of network
structures can be used to meet application requirements for density
and coverage area. The most common structure is the star topology,
where all devices communicate directly with a controller. Networks
can also cover larger areas or achieve higher reliability by using
multi-hop forwarding over various topologies, such as directed
acyclic graphs, cluster trees, and meshes.
These structures affect how transmissions within a network are
correlated with each other in time and space, such as forwarding a
frame across a mesh. It can also affect interactions between
networks, particularly networks whose radios have very different
coverage areas. For example, a long-range device belonging to one
network may be located in the midst of a mesh of short-range devices
belonging to another network.
2.4.3. Protocols
The MAC layer defines how senders coordinate their transmissions
within a network. Like the PHY layer, different MAC layers create
different distributions of RF energy in time and (for channel hopping
protocols) spectrum.
CSMA-based (channel sensing and backoff) protocols can provide some
protection from external transmissions, since they defer to any
ongoing transmission that they detect. Conflicts due to hidden
terminals can occur even within a single network, but differences
between radio technologies and network structures may exacerbate the
problem. In addition, MAC timing parameters, such as backoff times,
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are generally proportional to bit-rate and frame transmit times.
Timing incompatibilities between interfering senders can reduce the
effectiveness of backoff and retransmissions in heterogeneous
environments.
TDMA-based (transmission schedule) protocols can be more efficient in
their use of the channel and energy than CSMA protocols. But because
the networks define their slot structure and transmission schedules
independently, they may allocate transmission slots that conflict
with each other. Since senders rely on their assigned schedule, such
conflicts can be costly.
Minimizing energy consumption is often the absolute priority for IoT
design. It is necessary to keep radio turned off as much as
possible, while still ensuring connectivity. As with MAC protocols
(with which they are sometimes integrated), there are a variety of
approaches. With synchronous methods, devices wake up according to a
schedule that ensures that senders and receivers are awake at the
same time (as in IEEE 802.15.4 beacon-enabled PANs or TSCH).
Asynchronous methods allow devices to coordinate their wake up
schedules on-demand (as in ContikiMAC).
Coordinating the duty cycles of a sender and receiver imposes strict
timing constraints on radio operations. As with the PHY and MAC,
each power save protocol creates its own distribution of RF energy
over time. Depending on application requirements and tradeoffs for
latency and battery lifetime, duty cycles could be on timescale of <
1s to > 1000s.
Many IoT networks use IP(v6), but there is also considerable
diversity in higher layer protocols, both open and proprietary.
Routing protocols make different tradeoffs between latency,
reliability, energy efficiency and overhead, depending on the
application requirements. The operation of the routing protocol also
affects the distribution of RF energy in physical space, as frames
are forwarded toward a root or across a mesh. The routing protocol
may also react to the presence of interference by attempting to re-
route its traffic.
Higher layer protocols largely abstract away from the behavior of
individual wireless links. They use a variety of mechanisms to
maintain communication performance under conditions of loss and
delay, including retransmissions, multi-path communication, and
application-specific adaptations.
Finally, the variety of transport, transfer and application protocols
used in IoT networks reflects the diversity of use cases: The RESTful
model is central for IoT applications based on web services
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[I-D.keranen-t2trg-rest-iot]. Wireless sensing applications often
use in-network data processing and aggregation to reduce their
communication load. Industrial IoT applications emphasize low
latency and reliability. Wide-area IoT/SUN networks collect small
amounts of data from a very large number of devices. As a result,
applications may have very different priorities with respect to
packet loss, delay, and energy consumption.
3. Interaction behaviors
All elements of network functionality - MAC, power saving, topology
and routing, congestion control, data transfer, application -
contribute patterns of channel utilization over time, frequency, and
physical space. At the same time, protocols adapt their behavior in
response to channel conditions; relying on channel sensing and frame
errors at low layers and on loss and delay at higher layers. Inter-
network interaction therefore occurs on multiple time- and spatial-
scales and involves all layers of the protocol stack.
Motivating scenarios include:
o How will sub-GHz LPWAN networks such as LoRa and SigFox, whose
base stations cover wide areas, interact with multiple shorter-
range networks using IEEE 802.15.4g/WiSUN, Z-Wave, or EnOcean
radios?
o What happens if two or more independent networks using
6LoWPAN+RPL+CoAP are operating in the same room? Or two 6TiSCH
networks, each using a different scheduling function? What if an
a beacon-enabled PAN interacts with a ZigBee- or ContikiMAC- or
Thread-based network? What if people wearing BluetoothLE-based
body-area networks are also moving around in the area? Especially
in a WiFi heavy environment, the value of channel hopping for
interference mitigation may be limited.
o More generally, can networks using protocols optimized for
different metrics (e.g. latency vs battery lifetime) operate
effectively in the same location?
To date, there have been very few studies that examine network
performance under realistic - dense, heterogeneous, dynamic -
interference scenarios. Some existing observations and results are
noted here.
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3.1. WiFi
Interference between WiFi networks is a long-standing problem,
particularly in dense residential and urban areas, where there are
many independently deployed networks and large amounts of traffic.
To some extent, this has been mitigated by expansion into 5GHz
unlicensed spectrum and by major improvements in WiFi, including
higher bit-rates and directional transmission (beamforming). The
WiFi environment also has some properties that are helpful for
coexistence: WiFi networks are largely homogeneous, consisting of an
AP and associated devices that communicate directly with their AP.
WiFi also uses a CSMA-based MAC, which means that senders inherently
defer to any ongoing WiFi transmission, regardless of its source.
And the dominant application is media streaming, which is supported
by adaptive mechanisms everywhere from the server to the user
application.
However, WiFi performance may come under increasing pressure, due not
only to the increasing number of IoT networks, but also to the
forthcoming deployment of LTE traffic into 5GHz unlicensed spectrum.
3.2. IEEE 802.15.4
A common scenario in 2.4GHz spectrum will involve high-power, high-
traffic WiFi networks impacting networks based on low power, low bit-
rate radios, such as IEEE 802.15.4.
Practical existing solutions are mostly based on IEEE 802.15.4
devices identifying and using the least interfered channels, either
statically or by channel hopping. But in areas where there is a lot
of WiFi traffic, there may be very few such channels. WiFi
conventionally uses non-overlapping WiFi channels 1, 6, and 11,
leaving just three minimally interfered IEEE 802.15.4 channels. As a
result, low power IoT networks operating in these areas may be
crowded into a small number of "good" channels. These may come under
increasing pressure as IoT deployment increases.
3.3. Recent results in IoT networks
Recent research suggests that protocol level interactions can lead to
severe performance degradation, even when the channel is not heavily
loaded. While these studies focus on various IEEE 802.15.4 MAC
layers, the results suggest broader implications for protocol design.
[F3G15] and [FF16] show that IEEE 802.15.4 beacon-enabled PANs can
experience episodes of severe disruption due to protocol level
interactions. This includes behaviors such as short-term
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oscillations in throughput and extended periods of disconnectivity -
even when the channel itself is only lightly loaded. Similarly,
[YTB17] shows that interfering IEEE 802.15.4 6TiSCH-based networks
experience packet loss and so-called blackout periods, as well as
increased energy consumption.
These behaviors appear to be due to a combination of timing
rigidities in the MAC protocol, periodicity in the radio duty cycle,
and clock drift between networks. Battery constraints force devices
to spend most of their time with their radios turned off. Senders
and receivers therefore need some way to coordinate their radio wake
up times so that they can exchange packets. These mechanisms often
depend heavily on careful timing of radio operations, instead of (or
in addition to) explicit control traffic. This timing dependence can
make networks more sensitive to disruption than might be expected
from just considering overall channel utilization and collision
probabilities. Periodicity can exacerbate these effects. In
addition, clock drift results in networks' synchronizing and
desynchronizing with each other. This can result in interaction
effects at timescales on the orders of minutes or even days.
Generalizing these observations suggests that it will be necessary to
reconsider tradeoffs between energy consumption and resilience.
3.4. Higher layer protocols
To date, there have been few studies that address the performance of
high layer protocols, such as routing or data transfer, in network
coexistence. Certainly, extended outages at the link layer will
affect their operation and there is a risk that higher layer
protocols' reaction will exacerbate the impact of interference.
Conversely, it is possible that higher layer protocols may act to
mitigate the impact of interference, e.g. through congestion
avoidance.
4. Network coexistence in the IRTF/IETF context
The research literature contains a variety of proposals for improving
protocol performance in the presence of interference (see [SURVEY],
[SURVEY2] for an overview). In many cases, they assume rather
narrowly defined interaction scenarios and none seem to have been
deployed in practice.
Network coexistence in realistic IoT environments remains an open
issue, particularly with respect to protocol and network-scale
interactions. T2TRG is well-positioned to contribute to addressing
it by:
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o Developing and advocating best practices for performance
evaluation, focusing on realistic future wireless environments.
o Contributing to the ongoing development of IoT-related IETF
protocols, so that they are as resilient as possible to inter-
network interference.
o Supporting speculative research into the possibility of higher
layer protocols for active coordination between networks sharing
unlicensed spectrum.
4.1. Performance evaluation and protocol design
Performance evaluation of IoT protocols should take into account
their behavior in the presence of many diverse, administratively
independent networks operating in the same spectrum. To date, there
have been few studies that fully reflect this aspect of the future
IoT operating environment. This suggests that the community does not
yet have a complete understanding of effectiveness and reliability of
IoT protocols.
Given the community's limited experience with such evaluation, it is
unsurprising that there are not yet clear principles for designing
experiments that can provide meaningful results. Experiments must
reflect a realistic interference environment and capture behaviors
caused by interactions within the protocol stack, within a network,
and between networks - while still being both manageable and
informative for the the user. Best practices for designing such
experiments have not been established and existing simulation and
testbed tools have significant limitations.
Protocol-oriented network simulators (e.g. ns-2/3, OMNeT++, OPNET)
enable performance evaluation at scale: It is straightforward to
simulate an extremely large number of scenarios behavior over a long
period. Simulation also provides complete control and visibility
into the operation of the simulated system. However, these
advantages come at the cost of reduced fidelity, especially for
wireless propagation and reception. Modeling of interference between
different kinds of radios is particularly lacking.
By contrast, testbeds provide ground-truth about network performance
in a specific scenario. There are a number of open WSN/IoT testbeds
(e.g. [FINTEROP], [FITIOT]) that provide access to various
collections of hardware. However, the community has had little
experience using them for evaluating coexistence scenarios.
There are three main challenges: One is the logistics of deploying
long-running experiments involving multiple applications and many
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devices. Another practical challenge is instrumenting and collecting
data from the entire protocol stack and correlating the results
across networks, especially with resource-constrained devices. This
functionality is essential for obtaining data that allows users to
reason about the observed performance. Finally, there is a deeper
challenge in defining experiments that allow the user to
systematically explore the space of possible interactions, despite
the complexity and variability of the inter-network interference
environment.
In this context, T2TRG can contribute to the development of and
advocacy for best practices for performance evaluation. The results
of such studies can inform ongoing protocol development. This
includes protocols being developed in the IETF 6lo, 6TiSCH
(especially 6top), LPWAN, LWIG, ROLL and CoRe Working Groups. (It
is, of course, also necessary to take into account interactions with
protocols from other open and proprietary sources.)
4.2. Adaptive mitigation strategies
Network coexistence is likely to rely heavily on improving resilience
to interference in the MAC layer, which is ultimately responsible for
determining when a sender transmits.
But a MAC protocol cannot explicitly coordinate with devices in other
networks; it may not even be able to identify what kinds of networks
are sharing the channel, much less exchange (authenticated) control
traffic. The MAC layer must instead adapt to the presence of other
networks based on channel sensing and frame loss. This is a
significant challenge in complex interference environments,
especially for battery-powered devices, which must avoid the high
energy cost of listening to the channel as much as possible. While
the MAC layer and power saving protocols are themselves largely
outside IETF scope, these topics are relevant to the work of IETF
WG's such as 6lo, 6TiSCH, LPWAN and LWIG.
Like the MAC layer, higher layer protocols also adapt their behavior,
using packet loss and delay. But complex interactions such as those
described above can lead to disruptions that are difficult for higher
layer protocols to predict or adapt to in an effective way. It is
therefore important to ensure that protocol behaviors, such as route
selection, congestion control or keep-alive mechanisms, contribute to
(or at least do not hurt) resilience to inter-network interference.
These topics are particularly relevant to IETF protocols such as RPL
and CoAP.
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4.3. Active mitigation strategies
More speculatively, there may be opportunities for higher layer
protocols to actively participate in interference mitigation, by
sharing information about their operation and even by explicit
coordination between networks.
When two networks use the same PHY layer, it is possible for frames
transmitted by devices in one network to be successfully received by
devices in other networks. These frames are usually discarded
immediately, since they fail a MAC layer authentication check. But
if they are not discarded (and are not encrypted), the networks can
observe each others' control traffic or even explicitly exchange
information. Such a mechanism could allow them to announce their
expected channel utilization patterns, for example. MAC layer or
even IPv6 frames could be used for this purpose.
Alternatively, many IoT applications have some administrative
component that is connected to the Internet infrastructure, such as
mobile app-based user interface or cloud-based data collection. Even
limited connectivity opens possibilities for making use of a rich
array of resources. For example, this may be a way to provide access
to additional computing power or to allow networks make use of
external services with which they have an administrative
relationship. This might enable a coordination mechanism based on
negotiation via some trusted cloud-based service.
The inspiration here is from several different approaches: Cognitive
radio solutions where secondary users obtain information about
activity of primary users from trusted sources; Citizens Broadband
Radio Service (CBRS) and its spectrum allocation service; and
research into distributed coordination services e.g. [SEMCK14].
However, all of these approaches rely on either strict spectrum
regulation or a strong assumption of compatibility and cooperative
behavior among networks.
Even more speculatively, a secure distributed ledger could be used to
allow networks to announce themselves in a location, to provide
information about their channel utilization, and to obtain
information about co-located networks. Such a ledger could further
act as a reputation management system or as a resource broker. This
is potentially related to distributed infrastructure work in the IRTF
DINRG.
However, these are very much an open research area and there are
substantial challenges in developing such mechanisms:
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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 and memory
resources continue to be significant limitations. In particular, the
radio duty cycle is highly constrained, limiting both sensing and
communication.
3) Any cooperative mechanism must operate effectively in the absence
of any administrative or trust relationship between networks.
Alternatively, there must be some way to establish an appropriate
level of trust. This presents a significant challenge to the
practical implementation of cooperative mechanisms proposed in the
literature. (See Security Considerations below.)
4) The privacy implications of networks sharing information about
their activity must be carefully considered. (See Security
Considerations below.)
Despite the challenges, this topic seems particularly amenable to
standards and interoperability-oriented approaches enabled by IRTF
T2TRG. There may be synergy with IRTF T2TRG work in IoT semantic
interoperability: Can IoT networks describe not only the 'things'
they connect, but also themselves? In addition, the IRTF DIN
research group is active in the area of secure distributed Internet
infrastructure.
4.4. Role of Spectrum Regulation
Network coexistence is ultimately a problem of spectrum regulation.
Regulation of unlicensed spectrum has historically focused on output
power and overall spectrum utilization. For example, in 868 MHz
spectrum, LoRa relies on transmit duty cycle (DC) limits (which range
from 0.1% to 1%, depending on sub-band) to ensure efficient channel
utilization.
In some cases, listen-before-talk (LBT) has been mandated for
unlicensed bands, including (optionally) 868MHz. This results in a
more complex regulatory structures, due to the need to specify
detection thresholds, listening intervals, and backoff behaviors.
The regulations specify minimum requirements, rather than a mechanism
that is common to all networks. This can lead to networks with
different backoff behaviors sharing a channel. Issues of
compatibility and fairness between various LBT strategies are an
active topic of study, notably with regard to WiFi and LTE
coexistence in 5GHz spectrum (e.g. [KYK16]).
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The IETF community has a strong interest in ensuring that spectrum
regulation not only enables efficient use of unlicensed spectrum for
IoT applications, but also avoids overly prescriptive mandates that
constrain diversity and innovation.
5. Security Considerations
An overview of security challenges in IoT environments is given in
[I-D.irtf-t2trg-iot-seccons]. The current document focuses on
coexistence between independently administrated networks operating in
the same location. The biggest security challenge for managing
network interactions is that such networks do not necessarily have
any basis for a trust relationship.
Regulations concerning unlicensed spectrum only control radio
behaviors such as transmit power and overall channel utilization.
Regulations do not mandate the use of any specific protocol. It is
therefore not possible to externally enforce that networks
participate in some specific coexistence protocol (as long as they
otherwise comply with regulations).
Most wireless protocols adapt their behavior to channel conditions to
some extent, such as contention backoff, channel blacklisting, or re-
routing. But the more a network changes its behavior in response to
small amounts of information from an untrusted source, the more
leverage an attacker has to disrupt it. Similarly, the more
information about its future behavior a network provides to an
untrusted destination, the easier it is for an attacker to disrupt
it. The risk is further exacerbated in energy-constrained networks,
because a device may be forced to spend energy unnecessarily. In
addition, the high energy cost of listening to the channel makes it
expensive to build trust by observing the behavior of other networks.
Any proposed solution will therefore need to be resilient to the
possibility of incompatible, oblivious, selfish, or even hostile
networks when designing a coexistence mechanism. This is especially
true for methods in which two 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.
In addition, 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 application or its level of activity may reveal
sensitive data. Ideally, it should be possible for a network to both
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obfuscate its communication patterns (if needed) and act
cooperatively.
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.
6. Conclusion
The future IoT operating environment will contain many diverse,
administratively independent networks sharing unlicensed spectrum.
Ensuring network coexistence is essential for avoiding the "tragedy
of the commons" and enabling practical deployment of IoT solutions.
The community currently lacks a good understanding of the impact of
inter-network interactions, particularly with regard to protocol
behavior and network-scale interactions. However, recent results for
both IEEE 802.15.4 PANs and 6TiSCH + RPL networks suggest that inter-
network interactions can lead to episodes of significant disruption,
even when the channel itself is not overloaded. More research is
needed into both the causes of adverse interactions and ways to
mitigate them, particularly with regard to the role of higher layer
protocols.
Network coexistence is and will continue to be largely driven by
spectrum regulation and the PHY and MAC layers. However, this issue
are also relevant to the work of IETF Working Groups, such as 6lo,
6TiSCH, LPWAN, ROLL, CoRE, and LWIG. We identify three areas where
T2TRG can play a significant role:
o Performance evaluation should reflect that the IoT wireless
environment will contain diverse interfering networks. Tools and
techniques for investigating inter-network interaction are still
immature. The community could benefit substantially from the
development and documentation of best practices in this area.
o The results of such performance evaluation can assist IETF Working
Groups in improving the resilience of IoT-related protocols.
o There may also be a role for novel network coexistence mechanisms
based on information sharing or explicit coordination between
networks. This is a speculative research topic that seems
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particularly amenable to standards and interoperability oriented
approaches. However, there are substantial challenges.
7. Informative References
[F3G15] Feeney, L., Frey, M., Fodor, V., and M. Gunes, "Modes of
inter-network interaction in beacon-enabled IEEE 802.15.4
networks", 2015 14th Annual Mediterranean Ad Hoc
Networking Workshop (MED-HOC-NET),
DOI 10.1109/medhocnet.2015.7173294, June 2015.
[FF16] 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.
[FINTEROP]
Kim, E. and S. Ziegler, "Towards an open framework of
online interoperability and performance tests for the
Internet of Things", 2017 Global Internet of Things
Summit (GIoTS), DOI 10.1109/giots.2017.8016248, June 2017.
[FITIOT] Adjih, C., Baccelli, E., Fleury, E., Harter, G., Mitton,
N., Noel, T., Pissard-Gibollet, R., Saint-Marcel, F.,
Schreiner, G., Vandaele, J., and T. Watteyne, "FIT IoT-
LAB: A large scale open experimental IoT testbed", 2015
IEEE 2nd World Forum on Internet of Things (WF-IoT), DOI
10.1109/wf-iot.2015.7389098, December 2015.
[I-D.irtf-t2trg-iot-seccons]
Garcia-Morchon, O., Kumar, S., and M. Sethi, "State-of-
the-Art and Challenges for the Internet of Things
Security", draft-irtf-t2trg-iot-seccons-15 (work in
progress), May 2018.
[I-D.keranen-t2trg-rest-iot]
Keranen, A., Kovatsch, M., and K. Hartke, "RESTful Design
for Internet of Things Systems", draft-keranen-t2trg-rest-
iot-05 (work in progress), September 2017.
[KYK16] Kim, C., Yang, C., and C. Kang, "Adaptive Listen-Before-
Talk (LBT) scheme for LTE and Wi-Fi systems coexisting in
unlicensed band", 2016 13th IEEE Annual Consumer
Communications & Networking Conference (CCNC),
DOI 10.1109/ccnc.2016.7444845, January 2016.
Feeney & Fodor Expires November 26, 2018 [Page 18]
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[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.
[SEMCK14] Skjegstad, M., Ellingsater, B., Maseng, T., Crowcroft, J.,
and O. Kure, "Large-scale distributed Internet-based
discovery mechanism for dynamic spectrum allocation", 2014
IEEE International Symposium on Dynamic Spectrum Access
Networks (DYSPAN), DOI 10.1109/dyspan.2014.6817824, April
2014.
[SKH11] Sum, C., Kojima, F., and H. Harada, "Coexistence of
homogeneous and heterogeneous systems for IEEE 802.15.4g
smart utility networks", 2011 IEEE International Symposium
on Dynamic Spectrum Access Networks (DySPAN),
DOI 10.1109/dyspan.2011.5936241, May 2011.
[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.
[SURVEY2] Baccour, N., Puccinelli, D., Voigt, T., Koubaa, A., Noda,
C., Fotouhi, H., Alves, M., Youssef, H., Zuniga, M.,
Boano, C., and K. Roemer, "External Radio Interference",
SpringerBriefs in Electrical and Computer Engineering pp.
21-63, DOI 10.1007/978-3-319-00774-8_2, 2013.
[TCG316] Tinnirello, I., Croce, D., Galioto, N., Garlisi, D., and
F. Giuliano, "Cross-Technology WiFi/ZigBee Communications:
Dealing With Channel Insertions and Deletions", IEEE
Communications Letters Vol. 20, pp. 2300-2303,
DOI 10.1109/lcomm.2016.2603978, November 2016.
[WETZ17] Wetzker, U., Splitt, I., Zimmerling, M., Boano, C., and K.
Romer, "Troubleshooting Wireless Coexistence Problems in
the Industrial Internet of Things", 2016 IEEE Intl
Conference on Computational Science and Engineering (CSE)
and IEEE Intl Conference on Embedded and Ubiquitous
Computing (EUC) and 15th Intl Symposium on Distributed
Computing and Applications for Business
Engineering (DCABES), DOI 10.1109/cse-euc-dcabes.2016.167,
August 2016.
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[YTB17] Ben Yaala, S., Theoleyre, F., and R. Bouallegue,
"Cooperative resynchronization to improve the reliability
of colocated IEEE 802.15.4 -TSCH networks in dense
deployments", Ad Hoc Networks Vol. 64, pp. 112-126,
DOI 10.1016/j.adhoc.2017.07.002, September 2017.
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. David Oran's detailed
comments on the text are also much appreciated.
Authors' Addresses
Laura Marie Feeney
Uppsala University
Box 337
Uppsala SE-751 05
Sweden
Email: lmfeeney@it.uu.se
Viktoria Fodor
KTH
Osquldas vaeg 10
Stockholm SE-100 44
Sweden
Email: vjfodor@kth.se
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