A Top-Down Clustering and Cluster-Tree-Based Routing Scheme for Wireless Sensor Networks
Author(s) -
H. M. N. Dilum Bandara,
Anura P. Jayasumana,
Tissa H. Illangasekare
Publication year - 2011
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2011/940751
Subject(s) - computer science , hierarchical routing , computer network , distributed computing , wireless sensor network , network topology , cluster analysis , tree (set theory) , hierarchical clustering , cluster (spacecraft) , a priori and a posteriori , topology (electrical circuits) , routing protocol , routing (electronic design automation) , static routing , mathematics , artificial intelligence , mathematical analysis , philosophy , epistemology , combinatorics
Cluster-based organization of large sensor networks is the basis for many techniques aimed at enhancing power conservation and network management. A backbone network in the form of a cluster tree further enhances routing, broadcasting, and in-network processing. We propose a configurable top-down cluster and cluster-tree formation algorithm, a cluster-tree self-optimization phase, a hierarchical cluster addressing scheme, and a routing scheme. Such self-organization makes it possible to effectively deliver messages to a sink as well as within the network. For example, a circular sensor field with a sink in the center can establish cross-links and circular-paths within the cluster tree to deliver messages through shorter routes while reducing hotspots and consequently increasing network lifetime. Cluster and cluster-tree formation algorithm is independent of physical topology, and does not require a priori neighborhood information, location awareness, or time synchronization. Algorithm parameters allow for formation of cluster trees with desirable properties such as controlled breadth/depth, uniform cluster size, and circular clusters. Characteristics of clusters, cluster tree, and routing are used to demonstrate the effectiveness of the schemes over existing techniques.
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