The Trickle Algorithm
RFC 6206
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RFC - Proposed Standard
(March 2011; No errata)
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Last updated |
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2015-10-14
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draft-levis-roll-trickle
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IETF
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plain text
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IESG state |
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RFC 6206 (Proposed Standard)
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Consensus Boilerplate |
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Unknown
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Responsible AD |
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Adrian Farrel
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Internet Engineering Task Force (IETF) P. Levis
Request for Comments: 6206 Stanford University
Category: Standards Track T. Clausen
ISSN: 2070-1721 LIX, Ecole Polytechnique
J. Hui
Arch Rock Corporation
O. Gnawali
Stanford University
J. Ko
Johns Hopkins University
March 2011
The Trickle Algorithm
Abstract
The Trickle algorithm allows nodes in a lossy shared medium (e.g.,
low-power and lossy networks) to exchange information in a highly
robust, energy efficient, simple, and scalable manner. Dynamically
adjusting transmission windows allows Trickle to spread new
information on the scale of link-layer transmission times while
sending only a few messages per hour when information does not
change. A simple suppression mechanism and transmission point
selection allow Trickle's communication rate to scale logarithmically
with density. This document describes the Trickle algorithm and
considerations in its use.
Status of This Memo
This is an Internet Standards Track document.
This document is a product of the Internet Engineering Task Force
(IETF). It represents the consensus of the IETF community. It has
received public review and has been approved for publication by the
Internet Engineering Steering Group (IESG). Further information on
Internet Standards is available in Section 2 of RFC 5741.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc6206.
Levis, et al. Standards Track [Page 1]
RFC 6206 Trickle Algorithm March 2011
Copyright Notice
Copyright (c) 2011 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
(http://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 ....................................................2
2. Terminology .....................................................3
3. Trickle Algorithm Overview ......................................3
4. Trickle Algorithm ...............................................5
4.1. Parameters and Variables ...................................5
4.2. Algorithm Description ......................................5
5. Using Trickle ...................................................6
6. Operational Considerations ......................................7
6.1. Mismatched Redundancy Constants ............................7
6.2. Mismatched Imin ............................................7
6.3. Mismatched Imax ............................................8
6.4. Mismatched Definitions .....................................8
6.5. Specifying the Constant k ..................................8
6.6. Relationship between k and Imin ............................8
6.7. Tweaks and Improvements to Trickle .........................9
6.8. Uses of Trickle ............................................9
7. Acknowledgements ...............................................10
8. Security Considerations ........................................10
9. References .....................................................11
9.1. Normative References ......................................11
9.2. Informative References ....................................11
1. Introduction
The Trickle algorithm establishes a density-aware local communication
primitive with an underlying consistency model that guides when a
node transmits. When a node's data does not agree with its
neighbors, that node communicates quickly to resolve the
inconsistency (e.g., in milliseconds). When nodes agree, they slow
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