Collection Tree Protocol

Collection Tree Protocol

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by Omprakash Gnawali , Rodrigo Fonseca , Kyle Jamieson , David Moss , Philip Levis

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BibTeX

@MISC{Gnawali_collectiontree,
    author = {Omprakash Gnawali and Rodrigo Fonseca and Kyle Jamieson and David Moss and Philip Levis},
    title = {Collection Tree Protocol},
    year = {}
}

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Abstract

This paper presents and evaluates two principles for designing robust, reliable, and efficient collection protocols. These principles allow a protocol to benefit from accurate and agile link estimators by handling the dynamism such estimators introduce to routing tables. The first is datapath validation: a protocol can use data traffic as active topology probes, quickly discovering and fixing routing loops. The second is adaptive beaconing: by extending the Trickle code propagation algorithm to routing control traffic, a protocol sends fewer beacons while simultaneously reducing its route repair latency. We study these mechanisms in an implementation called Collection Tree Protocol (CTP) and evaluate their contributions to its performance. We evaluate CTP on 12 different testbeds ranging in size from 20–310 nodes and comprising 7 hardware platforms, on 6 different link layers, and on interference-free and interference-prone channels. In all cases, CTP delivers> 90 % of packets. Many experiments achieve 99.9%. Compared to standard beaconing, CTP sends 73 % fewer beacons while reducing topology repair latency by 99.8%. Finally, when using low-power link layers, CTP has duty cycles of 3 % while supporting aggregate loads of 30 packets/minute.

Keyphrases

collection tree protocol hardware platform duty cycle many experiment control traffic adaptive beaconing interference-prone channel different testbeds efficient collection protocol agile link estimator datapath validation different link layer topology repair latency aggregate load active topology probe data traffic route repair latency dynamism estimator trickle code propagation algorithm link layer