Flow Classification in Information Centric Networking
draft-moiseenko-icnrg-flowclass-07
ICNRG I. Moiseenko
Internet-Draft Apple Computer
Intended status: Informational D. Oran
Expires: July 17, 2021 Network Systems Research and Design
January 13, 2021
Flow Classification in Information Centric Networking
draft-moiseenko-icnrg-flowclass-07
Abstract
For the ubiquitous and highly important Internet protocols (TCP, UDP,
IP), flows are conventionally identified by the "5-tuple" of source
and destination IP addresses, source and destination port, and
protocol type in an IP packet. Information Centric Networking (ICN)
is a new paradigm where network communications are accomplished by
requesting named content, instead of sending packets to destination
addresses. This document describes mechanisms allowing ICN
forwarders, consumers, producers and other ICN nodes to encode,
decode, and process equivalence class identifiers (flows) at any
desired granularity of a routable name prefix and beyond the routable
name prefix. This document is a product of the IRTF Information-
Centric Networking Research Group (ICNRG).
Status of This Memo
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This Internet-Draft will expire on July 17, 2021.
Copyright Notice
Copyright (c) 2021 IETF Trust and the persons identified as the
document authors. All rights reserved.
I. Moiseenko & D. Oran Expires July 17, 2021 [Page 1]
Internet-Draft Flow Classification in ICN January 2021
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 3
2. Flow Identification Challenges and Opportunities in ICN . . . 3
3. Flow Encoding Schemes . . . . . . . . . . . . . . . . . . . . 4
3.1. Equivalence class component count (EC3) . . . . . . . . . 5
3.2. Equivalence class name component type (ECNCT) . . . . . . 6
4. Producer operation . . . . . . . . . . . . . . . . . . . . . 7
5. Consumer operation . . . . . . . . . . . . . . . . . . . . . 8
6. Forwarder operation . . . . . . . . . . . . . . . . . . . . . 8
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
8. Security Considerations . . . . . . . . . . . . . . . . . . . 9
9. Normative References . . . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 10
1. Introduction
The problem of identifying groups of packets that get consistent
treatment in a network and allowing that treatment to be independent
and isolated from the treatment of other groups of packets, is
ubiquitous and long-standing. The purposes to which this
identification can be put is highly varied, including such functions
are providing differentiated quality of service, traffic engineering,
traffic filtering for security functions like intrusion detection and
firewalling, etc.
Providing the capability to apply different functions to groupings
(formally equivalence classes) of packets is generally known as the
"flow identification problem" where the definition of what
constitutes a "flow" is highly dependent on the particular protocol
or protocols carrying the packets. Some of the above uses of flows
also bring a mechanism requirement that the flow identification
technique be useful to have not just equivalence classes, but the
ability to apply some useful notion of fairness among the instances
of each equivalence class. There are many possible flow
identification techniques that are either too granular (spatially or
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