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Lifetime optimized methods of correlated data gathering on sensor networks

  • School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

This paper presented two methods of correlated data gathering on sensor networks, LOMFC and LOMSC, based on two types of correlation model, Foreign-Coding and Self-Coding. The goal of the methods is to maximize the lifetime of the network. They perform a series of adjustments over a built data gathering topology and improved the lifetime of the network. The methods in this paper overcame the energy consumption imbalance of some previous methods of correlated data gathering and are highly distributed. The stimulations proved that the two methods outperform previous algorithms in lifetime and are always reliable.

Original languageEnglish
Title of host publicationProceedings - SNPD 2007
Subtitle of host publicationEighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Pages3-8
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
EventSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Qingdao, China
Duration: 30 Jul 20071 Aug 2007

Publication series

NameProceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Volume2

Conference

ConferenceSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Country/TerritoryChina
CityQingdao
Period30/07/071/08/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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