A clustering-based approximation scheme for in-network aggregation over sensor networks

  • Authors:
  • Lei Xie;Lijun Chen;Daoxu Chen;Li Xie

  • Affiliations:
  • State Key Laboratory of Novel Software Technology, NJU-POLYU Cooperative Laboratory for Wireless Sensor Network, Nanjing University, Nanjing, China;State Key Laboratory of Novel Software Technology, NJU-POLYU Cooperative Laboratory for Wireless Sensor Network, Nanjing University, Nanjing, China;State Key Laboratory of Novel Software Technology, NJU-POLYU Cooperative Laboratory for Wireless Sensor Network, Nanjing University, Nanjing, China;State Key Laboratory of Novel Software Technology, NJU-POLYU Cooperative Laboratory for Wireless Sensor Network, Nanjing University, Nanjing, China

  • Venue:
  • UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 in-network 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.