ICN Research Group C. Gundogan
Internet-Draft TC. Schmidt
Intended status: Experimental HAW Hamburg
Expires: September 29, 2019 M. Waehlisch
link-lab & FU Berlin
M. Frey
F. Shzu-Juraschek
Safety IO
J. Pfender
VUW
March 28, 2019
Quality of Service for ICN in the IoT
draft-gundogan-icnrg-iotqos-00
Abstract
This document describes manageable resources in ICN IoT deployments
and a lightweight traffic classification method for mapping
priorities to resources. Management methods are further derived for
controlling latency and reliability of traffic flows in constrained
environments.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Manageable Resources in the IoT . . . . . . . . . . . . . . . 3
3.1. Link Layer . . . . . . . . . . . . . . . . . . . . . . . 3
3.2. Pending Interest Table . . . . . . . . . . . . . . . . . 4
3.3. Content Store . . . . . . . . . . . . . . . . . . . . . . 4
4. Traffic Flow Classification . . . . . . . . . . . . . . . . . 4
5. Priority Handling . . . . . . . . . . . . . . . . . . . . . . 5
5.1. Link Layer . . . . . . . . . . . . . . . . . . . . . . . 5
5.2. Pending Interest Table . . . . . . . . . . . . . . . . . 5
5.3. Content Store . . . . . . . . . . . . . . . . . . . . . . 6
6. Security Considerations . . . . . . . . . . . . . . . . . . . 6
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 6
8. Informative References . . . . . . . . . . . . . . . . . . . 6
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 8
1. Introduction
The performance of networked systems is largely determined by the
resources available for forwarding messages between components. In
addition to link capacities and buffer queues, Information-centric
Networks rely on additional resources that shape its overall
performance, namely Pending Interest Table space, and caching
capacity.
Typical IoT deployments add tight resource constraints to this
picture [RFC7228]: Nodes have processing and memory limitations, the
underlying link layer technologies are lossy and restricted in
bandwidth. Particularly in multi-hop networks, such constraints
affect the overall performance, create bottlenecks, but may lead to
cascading packet loss or energy depletion when PIT resources are
independently evicted and forwarding states decorrelate
[DECORRELATION]. Overprovisioning to counter performance flaws is
infeasible for many IoT scenarios as it inflicts with use cases and
increases deployment costs. Quality of Service (QoS) is a method to
enhance overall performance by redistributing resources to a subset
of messages, and - in the constrained IoT use case - to coordinate
operations under resource scarcity.
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IoT applications follow various use cases, of which different QoS
requirements can be derived. While periodic sensor readings often
comply with unmanaged performance, industrial control messaging or
security alerts require (very) low latency, and safety-critical
environmental recording or network management need (highly) reliable
network services. Both quality levels can only be assured by
appropriate resource reservations.
In order to achieve a QoS-aware information-centric IoT deployment,
this document describes manageable resources in Section 3, defines a
flow classification method in Section 4, and specifies priorities and
their mappings in Section 5.
2. Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
The use of the term, "silently ignore" is not defined in RFC 2119.
However, the term is used in this document and can be similarly
construed.
This document uses the terminology of [RFC7476], [RFC7927], and
[RFC7945] for ICN entities.
The following terms are used in the document and defined as follows:
Traffic Flow A traffic flow is a sequence of messages (Interest and
data) that belong to one specific communication
context. Due to in-network caching, ICN flows may be
delocalized. A flow may also relate to several
requesters in the presence of Interest aggregation.
3. Manageable Resources in the IoT
The following resources contribute to the overall network performance
in Information-Centric IoT Networking and need management for QoS
control.
3.1. Link Layer
The link layer manages access to the media and provides space to
buffer packets. Low latency applications require that requests are
prioritized compared to regular priority data. Based on the request
response pattern of ICN, link layer resources can be preallocated for
data packets.
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3.2. Pending Interest Table
The Pending Interest Table (PIT) stores open requests at each hop.
PIT resources are allocated when requests are forwarded, and they are
released on returning responses.
Placement and replacement strategies of PIT entries directly
influence the latency and reliability properties of traffic flows and
thus should consider prioritization schemes. If the PIT is not
saturated new PIT entries can be added. If the PIT is saturated,
requests with higher priority should replace requests with lower
priority to prevent higher latencies due to retransmissions.
3.3. Content Store
Content stores (CS) enable transparent in-network caching and thus
improve the transport in wireless and lossy environments by reducing
hop traversals for content requests [NDN-EXP].
Placement and replacement strategies of data in content stores can
affect the latency and reliability properties of traffic flows. The
latency can be reduced by placing data closer to the consumers.
Reliability can be improved by replicating data in multiple content
stores to be resilient to node failures.
4. Traffic Flow Classification
This document defines a traffic flow classification mechanism that
aggregates names into equivalence classes in order to apply resource
allocation decisions on messages of particular traffic flows.
A traffic class is a name prefix and each device maintains a list of
valid classes. The actual distribution of traffic classes is out of
scope of this document. The classes for request and response
messages are derived by performing a longest prefix match (LPM) with
the list of valid traffic classes and the Name TLV of the message.
Examples are given in Figure 1.
list =
["/org", "/org /Hamburg", "/org /Berlin", "/org /Berlin /sensor" ]
LPM("/com" ,list) = ""
LPM("/org /Germany" ,list) = "/org"
LPM("/org /Hamburg" ,list) = "/org /Hamburg"
LPM("/org /Berlin /sensor /temp",list) = "/org /Berlin /sensor"
Figure 1: Example traffic flow class matches.
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The empty traffic class "" is the default class for messages that do
not match any valid traffic classes in the class list.
5. Priority Handling
We define two priority levels to set the priorities for traffic flows
in regards to latency and reliability.
o Latency:
* EXPEDITED
* REGULAR
o Reliability:
* RELIABLE
* REGULAR
Each list entry of the traffic class list from Section 4 has an
associated priority tuple which distinctly specifies priority levels
for the resources in Section 3. The tuple is of the following form:
priority tuple = < LATENCY_PRIORITY, RELIABILITY_PRIORITY >
Figure 2: Schema of the priority tuple.
5.1. Link Layer
As described above, the link layer provides space to buffer outgoing
packets. For the two latency priorities, this space can be allocated
into the following two queues:
o EXPEDITED_FORWARDING_QUEUE
o REGULAR_FORWARDING_QUEUE
Packets will be appended to the queue corresponding to their priority
level.
5.2. Pending Interest Table
In unsatured PITs, requests are added as new entries regardless of
the priority level. In saturated PITs, EXPEDITED traffic replaces
PIT entries of REGULAR traffic. If all entries in a saturated PIT
are of a higher priority than the incoming request, then we RECOMMEND
to drop the incoming request. If a saturated PIT contains entries of
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the same priority as the incoming request, we RECOMMEND to drop the
incoming request to avoid cancelling active but incomplete ICN
operations.
5.3. Content Store
Nodes MAY implement a caching decision strategy instead of always
caching all incoming content objects [ICN-CACHING]. If they do, the
caching decision strategy MUST take the content object priority into
account, such that lower priority content is not cached if the cache
is saturated with higher priority content.
In unsaturated content stores, all content objects are passed to the
cache decision strategy.
In saturated content stores, reliable traffic flows MUST be passed to
the cache replacement strategy. Content objects with regular
reliability requirements MUST be evicted first to make room for
higher reliability content objects. Traffic flows with regular
latency and regular reliability requirements MUST be passed to the
cache replacement strategy. The cache replacement strategy MUST NOT
evict content objects of higher reliability. Expedited traffic flows
with regular reliability MUST be passed to the cache replacement
strategy. Content objects with regular latency and regular
reliability requirements MUST be evicted first, if an open PIT state
is available. Otherwise, if no PIT state is available, then the
cache replacement strategy MAY replace content objects of expedited
or regular latency requirements and with regular reliability
requirements.
6. Security Considerations
TODO
7. IANA Considerations
TODO
8. Informative References
[DECORRELATION]
Waehlisch, M., Schmidt, TC., and M. Vahlenkamp,
"Backscatter from the Data Plane - Threats to Stability
and Security in Information-Centric Network
Infrastructure", Computer Networks Vol 57, No. 16, pp.
3192-3206, November 2013.
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[I-D.moiseenko-icnrg-flowclass]
Moiseenko, I. and D. Oran, "Flow Classification in
Information Centric Networking", draft-moiseenko-icnrg-
flowclass-03 (work in progress), January 2019.
[ICN-CACHING]
Chai, W., He, D., Psaras, I., and G. Pavlou, "Cache 'Less
for More' in Information-Centric Networks (Extended
Version)", Computer Communications 36, 7 (2013) pp.
758-770, February 2013, .
[NDN-EXP] Gundogan, C., Kietzmann, P., Lenders, M., Petersen, H.,
Schmidt, TC., and M. Waehlisch, "NDN, CoAP, and MQTT: A
Comparative Measurement Study in the IoT", Proc. of 5th
ACM Conf. on Information-Centric Networking (ICN-2018) ACM
DL, pp. , September 2018, .
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
.
[RFC7228] Bormann, C., Ersue, M., and A. Keranen, "Terminology for
Constrained-Node Networks", RFC 7228,
DOI 10.17487/RFC7228, May 2014,
.
[RFC7476] Pentikousis, K., Ed., Ohlman, B., Corujo, D., Boggia, G.,
Tyson, G., Davies, E., Molinaro, A., and S. Eum,
"Information-Centric Networking: Baseline Scenarios",
RFC 7476, DOI 10.17487/RFC7476, March 2015,
.
[RFC7927] Kutscher, D., Ed., Eum, S., Pentikousis, K., Psaras, I.,
Corujo, D., Saucez, D., Schmidt, T., and M. Waehlisch,
"Information-Centric Networking (ICN) Research
Challenges", RFC 7927, DOI 10.17487/RFC7927, July 2016,
.
[RFC7945] Pentikousis, K., Ed., Ohlman, B., Davies, E., Spirou, S.,
and G. Boggia, "Information-Centric Networking: Evaluation
and Security Considerations", RFC 7945,
DOI 10.17487/RFC7945, September 2016,
.
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Acknowledgments
This work was stimulated by fruitful discussions in the ICNRG
research group. We would like to thank all active members for
constructive thoughts and feedback. In particular, the authors would
like to thank Ilya Moiseenko and Dave Oran for their work provided in
[I-D.moiseenko-icnrg-flowclass]. This work was supported in part by
the German Federal Ministry of Research and Education within the I3
project.
Authors' Addresses
Cenk Gundogan
HAW Hamburg
Berliner Tor 7
Hamburg D-20099
Germany
Phone: +4940428758067
EMail: cenk.guendogan@haw-hamburg.de
URI: http://inet.haw-hamburg.de/members/cenk-gundogan
Thomas C. Schmidt
HAW Hamburg
Berliner Tor 7
Hamburg D-20099
Germany
EMail: t.schmidt@haw-hamburg.de
URI: http://inet.haw-hamburg.de/members/schmidt
Matthias Waehlisch
link-lab & FU Berlin
Hoenower Str. 35
Berlin D-10318
Germany
EMail: mw@link-lab.net
URI: http://www.inf.fu-berlin.de/~waehl
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Michael Frey
Safety IO
Franz-Ehrlich-Strasse 9
Berlin D-12489
Germany
EMail: michael.frey@safetyio.com
Felix Shzu-Juraschek
Safety IO
Franz-Ehrlich-Strasse 9
Berlin D-12489
Germany
EMail: felix.juraschek@safetyio.com
Jakob Pfender
Victoria University of Wellington
Kelburn Parade
Wellington NZ-6012
New Zealand
EMail: jpfender@ecs.vuw.ac.nz
URI: https://ecs.victoria.ac.nz/Main/GradJakobPfender
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