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GRAdient Broadcast: A Robust Data Delivery Protocol for Large Scale Sensor Networks (0)
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| Venue: | ACM Wireless Networks (WINET |
| Citations: | 168 - 5 self |
BibTeX
@ARTICLE{Ye_gradientbroadcast:,
author = {Fan Ye and Gary Zhong and Songwu Lu and Lixia Zhang and Fan Ye Gary Zhong},
title = {GRAdient Broadcast: A Robust Data Delivery Protocol for Large Scale Sensor Networks},
journal = {ACM Wireless Networks (WINET},
year = {},
volume = {11},
pages = {285--298}
}
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Abstract
Although data forwarding algorithms and protocols have been among the rst set of issues explored in sensor networking, how to reliably deliver sensing data through a vast eld of small, vulnerable sensors remains a research challenge. In this paper we present GRAdient Broadcast (GRAB), a new set of mechanisms and protocols which is designed specifically for robust data delivery in face of unreliable nodes and fallible wireless links. Similar to previous work [13, 14], GRAB builds and maintains a cost eld, providing each sensor the direction to forward sensing data. Dierent from all the previous approaches, however, GRAB forwards data along a band of interleaved mesh from each source to the receiver. GRAB controls the width of the band by the amount of credit carried in each data message, allowing the sender to adjust the robustness of data delivery. GRAB design harnesses the advantage of large scale and relies on the collective eorts of multiple nodes to deliver data, without dependency on any individual ones. We have evaluated the GRAB performance through both analysis and extensive simulation. Our analysis shows quantitatively the advantage of interleaved mesh over multiple parallel paths. Our simulation further con rms the analysis results and shows that GRAB can successfully deliver over 90% of packets with relatively low energy cost, even under the adverse conditions of 30% node failures compounded with 15% link message losses.
Keyphrases
gradient broadcast large scale sensor network robust data delivery protocol interleaved mesh adverse condition collective eorts vast eld multiple node grab performance vulnerable sensor present gradient broadcast grab build previous work analysis result link message loss extensive simulation data delivery grab forward data unreliable node individual one data message robust data delivery sensor networking multiple parallel path research challenge node failure large scale fallible wireless link previous approach low energy cost new set cost eld grab design rst set
