A clustering method that uses lossy aggregation of data

  • Authors:
  • Apoorva Jindal;Konstantinos Psounis

  • Affiliations:
  • University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA

  • Venue:
  • SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
  • Year:
  • 2004

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Abstract

Wireless sensor networks are characterized by dense deployment of sensor nodes which collectively communicate sensed data to the sink. However, due to the spatial correlation between sensor observations, it is not necessary for every node to transmit its data. We propose a clustering method which exploits the above observation. We do not make any assumption on the nature of data, and hence the algorithm will be valid for a broad range of conditions. The paper shows how to calculate the optimal cluster size. We also discuss the structure of the complete architecture which is still under development.