Quality of Service for ICN in the IoT
draft-gundogan-icnrg-iotqos-00

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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.

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
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   This Internet-Draft will expire on September 29, 2019.

Copyright Notice

   Copyright (c) 2019 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

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Internet-Draft           QoS for ICN in the IoT               March 2019

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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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