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Trickle++: A Context‐Aware Trickle Algorithm

B. Djamaa M. R. Senouci A. Mellouk 1
1 CIR
LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
Abstract : We propose to augment the Trickle algorithm with contextual information freely and locally available in low-power wireless networking technologies. The aim is to equip Trickle with hints and heuristics allowing it to propagate updates faster using link indicators such as received signal strength and link quality indicators along with available neighbourhood and network state information. The proposed augmentations are carefully designed so to preserve Trickle strengths in terms of simplicity, reliability, scalability, and load balancing while minimising its latency. Extensive simulation evaluations, conducted under TinyOS, show that the resulting algorithm, dubbed Trickle++, propagates updates more than twice faster than Trickle. Obtained results also show that Trickle++ preserves Trickle performance regarding overhead, load balancing, and code footprint.
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https://hal.archives-ouvertes.fr/hal-01676575
Contributor : Yacine Amirat <>
Submitted on : Friday, January 5, 2018 - 5:44:21 PM
Last modification on : Friday, October 4, 2019 - 1:26:51 AM

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  • HAL Id : hal-01676575, version 1

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B. Djamaa, M. R. Senouci, A. Mellouk. Trickle++: A Context‐Aware Trickle Algorithm. Proc. Of the IEEE International Conference on Global Communications, GlobeCom 2017, 2017, Singapour, Singapore. pp.1-6. ⟨hal-01676575⟩

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