A Hierarchical Data Dissemination Protocol Using Probability-Based Clustering for Wireless Sensor Networks

  • Authors:

  • Moonseong Kim;Matt W. Mutka;Hyunseung Choo

  • Affiliations:

  • Department of Computer Science and Engineering, Michigan State University, East Lansing, USA MI 48824;Department of Computer Science and Engineering, Michigan State University, East Lansing, USA MI 48824;School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea 440-746

  • Venue:
  • Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009
  • Year:
  • 2009

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Abstract

A major challenge for designing a dissemination protocol for Wireless Sensor Networks (WSNs) is energy efficiency. Recently, researchers have studied this issue, and SPMS, a representative protocol, outperforms the well-known protocol SPIN. One of the characteristics of SPMS uses the shortest path to minimize energy consumption. However, since it repeatedly uses the same shortest path, maximizing network lifetime is impossible, although it reduces the energy consumption. In this paper, we propose a Hi erarchical data dissemination protocol using Pro bability-based c lustering, called HiProc . It guarantees energy-efficient data transmission and maximizes network lifetime. HiProc solves the network lifetime problem by a novel probability function, which is related to the residual energy and the distance to a neighbor. The simulation results show that HiProc guarantees energy-efficient transmission and moreover increases the network lifetime by approximately 78% than that of SPMS.