Bulk data dissemination in wireless sensor networks: Modeling and analysis

  • Authors:

  • Wei Dong;Chun Chen;Xue Liu;Guodong Teng;Jiajun Bu;Yunhao Liu

  • Affiliations:

  • Zhejiang Provincial Key Laboratory of Service Robot, College of Computer Science, Zhejiang University, Hangzhou 310027, PR China;Zhejiang Provincial Key Laboratory of Service Robot, College of Computer Science, Zhejiang University, Hangzhou 310027, PR China;School of Computer Science, McGill University, Montreal, Quebec, Canada H3A 0E9;Zhejiang Provincial Key Laboratory of Service Robot, College of Computer Science, Zhejiang University, Hangzhou 310027, PR China and Institute of Service Engineering, Hangzhou Normal University, H ...;Zhejiang Provincial Key Laboratory of Service Robot, College of Computer Science, Zhejiang University, Hangzhou 310027, PR China;School of Software and TNLIST, Tsinghua University, PR China

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2012

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Abstract

Wireless sensor networks (WSNs) have recently gained a great deal of attention as a topic of research, with a wide range of applications being explored. Bulk data dissemination is a basic building block for sensor network applications. The problem of designing efficient bulk data dissemination protocols has been addressed in a number of recent studies. The problem of accurately analyzing the performance of these protocols, however, has not been addressed sufficiently in the literature. In this work, we show a way of accurately analyzing the performance of bulk data dissemination protocols in WSNs. Our model can be applied to practical network topologies by use of the shortest propagation path. Our model is accurate by considering topological information, impact of contention, and impact of pipelining. We validate the analytical results through testbeds and detailed simulations. Results show that the analytical results fit well with the testbed results and simulation results. Further, we demonstrate that the analytical results can be used to aid protocol design for performance optimizations, e.g., page size tuning for shortening the completion time.