Network Working Group L. Feeney
Internet-Draft Uppsala University
Intended status: Informational V. Fodor
Expires: November 3, 2018 KTH
May 02, 2018
Inter-network Coexistence in the Internet of Things
draft-feeney-t2trg-inter-network-02
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 defining how radios use the channel. But
higher layer protocols are also a party to adverse interactions
between networks. To date, there have been few performance studies
that fully reflect this aspect of the future IoT operating
environment, particularly with respect to protocol behavior and
network-scale interactions.
This document describes key challenges for coexistence and highlights
some recent research results showing the impact of protocol level
interactions on network performance. It identifies two opportunities
for the IRTF T2TRG community. The first is to define best practices
for performance evaluation and protocol design in the context of
network coexistence. The second is to investigate the use of higher
layer protocols to actively participate in managing network
coexistence.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/.
Feeney & Fodor Expires November 3, 2018 [Page 1]
Internet-Draft inter-network coexistence May 2018
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on November 3, 2018.
Copyright Notice
Copyright (c) 2018 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
(https://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. IoT interaction challenges . . . . . . . . . . . . . . . . . 4
2.1. Scale . . . . . . . . . . . . . . . . . . . . . . . . . . 4
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 . . . . . . . . . . . . . . . . . . . . 8
3.1. WiFi . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2. IEEE 802.15.4 . . . . . . . . . . . . . . . . . . . . . . 9
3.3. MAC layer interactions . . . . . . . . . . . . . . . . . 10
4. Network coexistence in the IRTF/IETF context . . . . . . . . 10
4.1. Protocol evaluation . . . . . . . . . . . . . . . . . . . 11
4.2. Adaptive mitigation strategies . . . . . . . . . . . . . 11
4.3. Active mitigation strategies . . . . . . . . . . . . . . 12
4.4. Role of Spectrum Regulation . . . . . . . . . . . . . . . 13
5. Security Considerations . . . . . . . . . . . . . . . . . . . 14
6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 15
7. Informative References . . . . . . . . . . . . . . . . . . . 16
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 17
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 17
Feeney & Fodor Expires November 3, 2018 [Page 2]
Internet-Draft inter-network coexistence May 2018
1. Introduction
An IoT application is a set of wireless devices that act together to
perform some sensing and control function. Most applications also
provide a user interface, via a mobile app, cloud-based service, or
some local hardware. This gives them (possibly limited or
intermittent) connectivity to the larger Internet. 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 layer can only explicitly coordinate devices within a single
network. It provides only limited protection from other networks,
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 and on carefully controlled
measurements of interacting RF waveforms. (See [NIST] for a
discussion of relevant issues and [SUM11] for an example of such an
analysis for IEEE 802.15.4g.)
Feeney & Fodor Expires November 3, 2018 [Page 3]
Internet-Draft inter-network coexistence May 2018
Analytic modeling of interactions between MAC layers is much harder,
because the MAC itself plays an active role in transmission timing
and parameters. Interfering networks are therefore usually modeled
as increasing the intensity of some statistical process representing
noise or loss. 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.)
But there are very few studies that evaluate complex, heterogeneous
interference scenarios, particularly with regard to protocol behavior
and network-scale interactions. Most existing solutions rely on low
IoT traffic loads and careful channel selection to achieve adequate
performance. But recent work [WETZ17] demonstrates that real world
instances of IoT interference require considerable effort to
diagnose.
This document explores key challenges for network coexistence in
future IoT environments and presents some recent research results.
These suggest that protocol level interactions can significantly
affect network performance, even when the channel is not heavily
loaded. Higher layer protocols will therefore need to be aware of
the potential impact of inter-network interference and avoid
contributing to adverse interactions. We argue that network
coexistence in future IoT environments is not yet well understood and
identify possible T2TRG roles in addressing this issue.
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 affect not only
individual wireless links, but also protocols operating at network
scale.
Feeney & Fodor Expires November 3, 2018 [Page 4]
Internet-Draft inter-network coexistence May 2018
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 not necessarily any basis for a
trust relationship between networks. Networks with overlapping
wireless coverage may well have been deployed by unrelated actors.
There is no single authority that has an administrative relationship
with all of the potentially interfering networks in any given
location. This means that there is no entity that all networks can
trust to coordinate their 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 the network itself may not have any meaningful
external identity. Even if two networks can exchange information,
there is no obvious way for each network 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.
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
ensuring needed connectivity. Even sensing the channel conditions is
an 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.
Feeney & Fodor Expires November 3, 2018 [Page 5]
Internet-Draft inter-network coexistence May 2018
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.
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.
Feeney & Fodor Expires November 3, 2018 [Page 6]
Internet-Draft inter-network coexistence May 2018
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 trees or
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,
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 the 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 to power saving. With synchronous methods, devices wake
Feeney & Fodor Expires November 3, 2018 [Page 7]
Internet-Draft inter-network coexistence May 2018
up according to a schedule that ensures that senders and receivers
are awake at the same time (as in IEEE 802.15.4 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 the 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, this could be on timescale of < 1s to >
1000s.
IoT networks usually 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 are largely abstracted 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
[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 networks collect small
amounts of data from a very large number of devices.
3. Interaction behaviors
Radios using the same spectrum can differ by two orders of magnitude
in terms of communication range, bit-rate, bandwidth and transmit
power. Different PHY and MAC layers create different distributions
of RF energy over time, spectrum, and physical space. The variety of
possible interactions between them may lead to patterns of loss and
delay that are difficult for higher layer protocols to predict or
manage. In addition, higher layer protocols for power saving,
routing and data communication create their own distributions of
network activity over time and space. Interactions between networks
Feeney & Fodor Expires November 3, 2018 [Page 8]
Internet-Draft inter-network coexistence May 2018
therefore occur at multiple scales. This suggests that inter-network
interactions are a potential issue at all layers of the protocol
stack.
How will sub-GHz LPWAN networks such as LoRa and SigFox, whose base
stations cover wide areas, interact with possibly large numbers of
smaller networks using IEEE 802.15.4g/WiSUN or EnOCean radios? What
happens if two or more independent networks using CoAP over RPL over
6LowPAN (or 6TiSCH) are operating in the same room? What happens if
a beacon-enabled PAN (or a ZigBee or ContikiMAC network) is thrown
into the mix? And some BluetoothLE? Especially in a WiFi heavy
environment, the value of channel hopping for interference mitigation
in IEEE 802.15.4 networks may be limited.
To date, there have been very few studies that examine network
performance under realistic - dense, heterogeneous - interference
scenarios. Some existing observations and results are noted here.
3.1. WiFi
Interference between WiFi networks is widely observed, especially in
2.4GHz spectrum in dense residential and urban areas, where there are
many independently deployed networks and large amounts of traffic.
WiFi presents a strongly homogeneous interference environment. WiFi
networks consist of an AP and associated devices that communicate
directly with their AP. WiFi also uses a CSMA-based MAC, which means
that senders to defer to any ongoing WiFi transmission, regardless of
its source. Traffic is dominated by media streaming, which is
supported by adaptive mechanisms at the client and server, as well as
throughout the protocol stack.
Despite these simplifying factors, poor WiFi performance is a problem
in dense urban and residential areas, even noted by the general
public. This does not bode well for the much large number of
heterogeneous networks deployed in the future IoT environment.
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. The research literature includes
a range of mitigation strategies directed to specific cases. (See
[SURVEY] and [SURVEY2] for an overview.)
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
Feeney & Fodor Expires November 3, 2018 [Page 9]
Internet-Draft inter-network coexistence May 2018
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 very small number of "good" channels.
3.3. MAC layer interactions
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 severe disruptions due to protocol level interactions.
This includes behaviors such as short-term 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 extended blackout periods, as well as increased energy
consumption. Such outages are likely to affect the operation of
higher layer protocols.
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. More generally, 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 makes networks more sensitive to
disruption than might be expected from just considering overall
channel utilization and collision probabilities. In addition, clock
drift results in networks' synchronizing and desynchronizing with
each other, which creates dynamic effects.
4. Network coexistence in the IRTF/IETF context
Network coexistence remains an open research problem, particularly
with respect to protocol behavior and network-scale interactions. We
identify several areas of relevance for IETF/IRTF activities. In
particular, we highlight a role for T2TRG in 1) developing and
advocating best practices for performance evaluation and protocol
design 2) speculative research into the possibility of higher layer
protocols actively contributing to network coexistence.
Feeney & Fodor Expires November 3, 2018 [Page 10]
Internet-Draft inter-network coexistence May 2018
4.1. Protocol evaluation
Performance evaluation of IoT protocols should consider whether they
will perform acceptably in the presence of diverse networks operating
in the same spectrum. In the IETF/IRTF context, this includes
protocols from the 6lo, LPWAN and 6TiSCH working groups, as well as
routing, transfer and application protocols, such as RPL and CoAP.
Moreover, networks using IETF protocols will share spectrum with
networks using protocols from a variety of other open and proprietary
sources.
To date, there have been few performance studies that fully reflect
the complexity of the future IoT operating environment. This
suggests that the community does not yet have a sufficient
understanding of performance and reliability of IoT protocols.
In practical terms, there is also a lack of both simulation and
testbed tools that support the necessary scale and diversity of
protocols and hardware to facilitate such work. Simulation provides
complete control and visibility into the behavior of a wireless
system, but only at the cost of fidelity. Testbeds must reflect the
salient characteristics of wireless environments with many different
IoT networks operating simultaneously, while still remaining
manageable and informative. It is important to consider these
tradeoffs in describing what a useful performance evaluation setup
would look like.
In this context, T2TRG can contribute to the development of and
advocacy for best practices for performance evaluation.
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
defining the channel access policy. 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 (encrypted, authenticated) control traffic. It can only
indirectly adapt to their presence, based on channel sensing and
frame loss. This is a significant challenge in dynamic,
heterogeneous interference environments, especially for battery-
powered devices, which must aggressively minimize the time spent
listening to the channel. While the MAC layer itself is outside
IETF/IRTF scope, these topics are relevant to several IETF protocols,
most notably 6top.
As noted earlier, higher layer protocols also contribute to patterns
of channel utilization that affect inter-network interactions. These
Feeney & Fodor Expires November 3, 2018 [Page 11]
Internet-Draft inter-network coexistence May 2018
protocols also adapt their behavior in response to observed packet
loss and delay. It is therefore important to ensure that protocol
behaviors, such as route selection, congestion control or application
keep-alive, 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.
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 cannot be authenticated and
are usually discarded at the MAC layer. But they might provide a way
for networks to exchange signaling information that can be handled as
IP packets at the network layer, even if they have very different
protocol stacks otherwise. Such a mechanism could allow devices to
describe their expected channel utilization patterns, for example.
Alternatively, many applications have some form of connectivity to
the Internet infrastructure, often as part of the user interface.
This might be a way to provide access to additional computing
resources or to establish a trust relationship. A coordination
mechanism could be based on information exchange via some trusted
cloud-based service, for example. The inspiration here is from
cognitive radio solutions where secondary users obtain information
about activity of primary users from trusted sources.
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.
However, these are very much an open research area and there are
substantial challenges in developing such mechanisms:
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
Feeney & Fodor Expires November 3, 2018 [Page 12]
Internet-Draft inter-network coexistence May 2018
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.)
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 additionm, the IRTF DIN
research group is active in the area of secure distributed Internet
infrastructure. There may also be synergy with IETF activities
(PLUS) in making signaling information available within encrypted
flows.
4.4. Role of Spectrum Regulation
Network coexistence is fundamentally a problem of spectrum
regulation. Regulation of unlicensed spectrum has historically
focused on radio output power and overall spectrum utilization.
Perhaps the simplest such structure is the transmit duty cycle limit.
In 868 MHz spectrum for example, LoRa relies mainly on duty cycle
limits (which range from 0.1% to 1%, depending on sub-band) to
coordinate channel access.
Listen-before-talk (LBT) has been mandated for some unlicensed bands.
This results in a more complex regulatory structures, due to the need
to specify detection sensitivity thresholds, listening intervals, and
backoff responses. Issues of compatibility and fairness between
various LBT strategies are an active topic of study, particularly
with regard to WiFi and LTE-U coexistence in 5GHz spectrum (e.g.
[LBT]).
The IETF community has a vested interest in ensuring that spectrum
regulation not only averts a 'tragedy of the commons' in the use of
unlicensed spectrum for IoT applications, but also overly
prescriptive mandates that constrain innovation.
Feeney & Fodor Expires November 3, 2018 [Page 13]
Internet-Draft inter-network coexistence May 2018
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 CSMA backoff or channel blacklisting. 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
by the high energy cost of listening to the channel to directly
observe 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
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
Feeney & Fodor Expires November 3, 2018 [Page 14]
Internet-Draft inter-network coexistence May 2018
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 wireless
spectrum. Ensuring network coexistence is essential for avoiding the
"tragedy of the commons" and enabling practical deployment of IoT
solutions.
Network coexistence is and will continue to be largely the domain of
spectrum regulation and of the PHY and MAC layers. But the operation
of protocols throughout the network stack affects the distribution of
RF energy over time, spectrum and physical space at many different
scales. This suggests that higher layer protocols are also a party
to adverse interactions between networks.
The community currently lacks a good understanding of the impact of
inter-network interference, particularly with regard to protocol
behavior and network-scale interactions. Recent results suggest that
inter-network interactions can significantly affect performance, even
when the channel itself is not overloaded. Periodic behaviors and
timing-sensitive energy saving mechanisms appear to be key factors,
though more research is needed.
These issues are relevant to IETF/IRTF, most obviously with respect
to the performance of protocols such as LPWAN, 6LowPAN, 6TiSCH, RPL,
and CoAP. We also identify two topics as especially relevant to
T2TRG:
1) Performance evaluation should reflect the complexity and
heterogeneity of future IoT environments. The community could
benefit substantially from the development and documentation of best
practices in this regard. The results of such performance evaluation
can inform the work of IETF Working Groups addressing IoT-related
protocols.
2) There may be a role for network coexistence mechanisms based on
information sharing or explicit coordination between networks. This
topic seems particularly amenable to standards and interoperability
oriented approaches. However, there are substantial open research
challenges.
Feeney & Fodor Expires November 3, 2018 [Page 15]
Internet-Draft inter-network coexistence May 2018
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.
[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-14 (work in
progress), April 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.
[LBT] 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.
[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.
[SUM11] 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.
Feeney & Fodor Expires November 3, 2018 [Page 16]
Internet-Draft inter-network coexistence May 2018
[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.
[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
Feeney & Fodor Expires November 3, 2018 [Page 17]
Internet-Draft inter-network coexistence May 2018
Viktoria Fodor
KTH
Osquldas vaeg 10
Stockholm SE-100 44
Sweden
Email: vjfodor@kth.se
Feeney & Fodor Expires November 3, 2018 [Page 18]