Probabilistic protocols for fair communication in wireless sensor networks

Ioannis Chatzigiannakis, Lefteris Kirousis, Thodoris Stratiotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work we present three new distributed, probabilistic data propagation protocols for Wireless Sensor Networks which aim at maximizing the network's operational life and improve its performance. The keystone of these protocols' design is fairness which declares that fair portions of network's work load should be assigned to each node, depending on their role in the system. All the three protocols, EFPFR, MPFR and TWIST, emerged from the study of the rigorously analyzed protocol PFR. Its design elements were identified and improvements were suggested and incorporated into the introduced protocols. The experiments conducted show that our proposals manage to improve PFR's performance in terms of success rate, total amount of energy saved, number of alive sensors and standard deviation of the energy left. Indicatively we note that while PFR's success rate is 69.5%, TWIST is achieving 97.5% and its standard deviation of energy is almost half of that of PFR.

Original languageEnglish (US)
Title of host publicationAlgorithmic Aspects of Wireless Sensor Networks - Fourth International Workshop, ALGOSENSORS 2008, Revised Selected Papers
Pages100-110
Number of pages11
DOIs
StatePublished - 2008
Event4th International Workshop on Algorithmic Aspects of Wireless Sensor Networks, ALGOSENSORS 2008 - Reykjavik, Iceland
Duration: Jul 12 2008Jul 12 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5389 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Workshop on Algorithmic Aspects of Wireless Sensor Networks, ALGOSENSORS 2008
Country/TerritoryIceland
CityReykjavik
Period7/12/087/12/08

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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