On the optimal blacklisting threshold for link selection in wireless sensor networks

Flavio Fabbri*, Marco Zuniga, Daniele Puccinelli, Pedro Marrón

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

Empirical studies on link blacklisting show that the delivery rate is sensitive to the calibration of the blacklisting threshold. If the calibration is too restrictive (the threshold is too high), all neighbors get blacklisted. On the other hand, if the calibration is too loose (the threshold is too low), unreliable links get selected. This paper investigates blacklisting analytically. We derive a model that accounts for the joint effect of the wireless channel (signal strength variance and coherence time) and the network (node density). The model, validated empirically with mote-class hardware, shows that blacklisting does not help if the wireless channel is stable or if the network is relatively sparse. In fact, blacklisting is most beneficial when the network is relatively dense and the channel is unstable with long coherence times.

Original languageEnglish
Title of host publicationWireless Sensor Networks - 9th European Conference, EWSN 2012, Proceedings
Pages147-162
Number of pages16
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event9th European Conference on Wireless Sensor Networks, EWSN 2012 - Trento, Italy
Duration: 15 Feb 201117 Feb 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7158 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th European Conference on Wireless Sensor Networks, EWSN 2012
Country/TerritoryItaly
CityTrento
Period15/02/1117/02/11

Bibliographical note

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

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