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On generating backbone trees through robust multi-hop clusters in wireless sensor networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The unbalanced power consumption among sensor nodes may cause a network partition and failures. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 58.6% and 79.42% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively.

Original languageEnglish
Title of host publicationComputer-Human Interaction - 8th Asia-Pacific Conference, APCHI 2008, Proceedings
Pages30-39
Number of pages10
DOIs
StatePublished - 2008
Event8th Asia-Pacific Conference on Computer-Human Interaction, APCHI 2008 - Seoul, Korea, Republic of
Duration: 6 Jul 20089 Jul 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5068 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Asia-Pacific Conference on Computer-Human Interaction, APCHI 2008
Country/TerritoryKorea, Republic of
CitySeoul
Period6/07/089/07/08

Keywords

  • Backbone
  • Clustering
  • Energy efficient
  • Load balancing
  • Robustness
  • Wireless sensor networks

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