NDLI: A Dynamic Cluster Formation Algorithm for Collaborative Information Processing in Wireless Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Chia-Yen Shih Jenks, S.F.
Copyright Year	2007
Description	Author affiliation: Univ. of California, Irvine (Chia-Yen Shih; Jenks, S.F.)
Abstract	Clustering of sensor nodes has been shown to be an effective approach for distributed collaborative information processing in resource constrained wireless sensor networks to keep network traffic local in order to reduce energy dissipation of long-distance transmissions. Defining the range and topology of clusters to reduce energy consumption and retransmissions due to collisions on shared radio channels is an ongoing research topic. One solution is to minimize overlapping cluster ranges to reduce signal contention, thus reducing the energy dissipation of collisions and retransmissions. In this paper, we propose a dynamic cluster formation (DCF) algorithm that dynamically groups a set of sensor nodes into a logical cluster-based sensing and processing unit, collaborative agent sensor team (CAST), to detect and track localized phenomena. Each cluster head is selected locally such that the total overlap between clusters in a CAST is low and the coverage of each cluster head is high. We compare our approach with optimal solutions, and simulation results show the effectiveness and scalability of our CAST DCF algorithm.
Starting Page	107
Ending Page	112
File Size	686179
Page Count	6
File Format	PDF
ISBN	9781424415014
DOI	10.1109/ISSNIP.2007.4496828
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-03
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Energy consumption Network topology Heuristic algorithms Energy dissipation Clustering algorithms Collaboration Information processing Telecommunication traffic Sensor phenomena and characterization
Content Type	Text
Resource Type	Article

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