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GRAdient Broadcast: A Robust Data Delivery Protocol for Large Scale Sensor Networks

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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.

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Authors and Affiliations

  1. Computer Science Department, University of California, Los Angeles, CA, 90095-1596

    Fan Ye, Gary Zhong, Songwu Lu & Lixia Zhang

Authors
  1. Fan Ye
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  2. Gary Zhong
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  3. Songwu Lu
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  4. Lixia Zhang
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Correspondence to Fan Ye.

Additional information

Fan Ye received his B.E. in Automatic Control in 1996 and MS in Computer Science in 1999, both from Tsinghua University, Beijing, China. After that, he has been pursuing a Ph.D. degree at UCLA. His research interests are in network protocol design, with focus on data forwarding, power management and security in large scale sensor networks.

Gary Zhong is currently pursuing M.S. degree in computer science at University of California, Los Angeles. He received his B.S. degree in computer science and engineering from University of California, Davis. His research interests include wireless networking, mobile computing, and large scale sensor networks.

Songwu Lu received both his M.S. and Ph.D. from University of Illinois at Urbana-Champaign. He is currently an assistant professor at UCLA Computer Science. He received NSF CAREER award in 2001. His research interests include wireless networking, mobile computing, wireless security, and computer networks.

Lixia Zhang received her Ph.D in computer science from the Massachusetts Institute of Technology. She was a member of the research staff at the Xerox Palo Alto Research Center before joining the faculty of UCLA’s Computer Science Department in 1995. In the past she has served on the Internet Architecture Board, Co-Chair of IEEE Communication Society Internet Technical Committee, the editorial board for the IEEE/ACM Transactions on Networking, and technical program committees for many networking-related conferences including SIGCOMM and INFOCOM. Zhang is currently serving as the vice chair of ACM SIGCOMM.

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Ye, F., Zhong, G., Lu, S. et al. GRAdient Broadcast: A Robust Data Delivery Protocol for Large Scale Sensor Networks. Wireless Netw 11, 285–298 (2005). https://doi.org/10.1007/s11276-005-6612-9

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  • DOI: https://doi.org/10.1007/s11276-005-6612-9

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