GRAdient broadcast: a robust data delivery protocol for large scale sensor networks

  • Authors:

  • Fan Ye;Gary Zhong;Songwu Lu;Lixia Zhang

  • Affiliations:

  • Computer Science Department, University of California, Los Angeles, CA;Computer Science Department, University of California, Los Angeles, CA;Computer Science Department, University of California, Los Angeles, CA;Computer Science Department, University of California, Los Angeles, CA

  • Venue:
  • Wireless Networks
  • Year:
  • 2005

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Abstract

Although data forwarding algorithms and protocols have been among the first set of issues explored in sensor networking, how to reliably deliver sensing data through a vast field of small, vulnerable sensors remains a research challenge. In this paper we present GRAdient Broadcast (GRAB), a new set of mechanisms and protocols which is designed specifically for robust data delivery in face of unreliable nodes and fallible wireless links. Similar to previous work [12,13], GRAB builds and maintains a cost field, providing each sensor the direction to forward sensing data. Different from all the previous approaches, however, GRAB forwards data along a band of interleaved mesh from each source to the receiver. GRAB controls the width of the band by the amount of credit carried in each data message, allowing the sender to adjust the robustness of data delivery. GRAB design harnesses the advantage of large scale and relies on the collective efforts of multiple nodes to deliver data, without dependency on any individual ones. We have evaluated the GRAB performance through both analysis and extensive simulation. Our analysis shows quantitatively the advantage of interleaved mesh over multiple parallel paths. Our simulation further confirms the analysis results and shows that GRAB can successfully deliver over 90% of packets with relatively low energy cost, even under the adverse conditions of 30% node failures compounded with 15% link message losses.