Recently in-network aggregation has gained much attention for effectively reducing energy consumption over sensor networks. In this paper, we present CASA, a clustering-based approximation scheme for innetwork aggregation, which significantly reduces the overall energy consumption while maintaining user-specified data quality. We explore two ideas to support the approximation scheme. First, we propose a clusteringbased framework to effectively utilize temporal coherency tolerance (tct) in conjunction with in-network aggregation to save communication cost over sensor network. Secondly, we propose an adaptive tct-reallocating technique to further reduce communication cost and maintain load balance. Our experiment results indicate that significant benefits can be achieved by using our CASA approximation scheme. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Xie, L., Chen, L., Chen, D., & Xie, L. (2007). A clustering-based approximation scheme for in-network aggregation over sensor networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4611 LNCS, pp. 503–513). Springer Verlag. https://doi.org/10.1007/978-3-540-73549-6_50
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