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Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks

Published:03 November 2004Publication History

ABSTRACT

Recent experimental studies have shown that wireless links in real sensor networks can be extremely unreliable, deviating to a large extent from the idealized perfect-reception-within-range models used in common network simulation tools. Previously proposed geographic routing protocols commonly employ a maximum-distance greedy forwarding technique that works well in ideal conditions. However, such a forwarding technique performs poorly in realistic conditions as it tends to forward packets on lossy links. We identify and illustrate this weak-link problem and the related distance-hop trade-off, whereby energy efficient geographic forwarding must strike a balance between shorter, high-quality links, and longer lossy links. The study is done for scenarios with and without automatic repeat request (ARQ).

Based on an analytical link loss model, we study the distance-hop trade-off via mathematical analysis and extensive simulations of a wide array of blacklisting/link-selection strategies; we also validate some strategies using a set of real experiments on motes. Our analysis, simulations and experiments all show that the product of the packet reception rate (PRR) and the distance traversed towards destination is the optimal forwarding metric for the ARQ case, and is a good metric even without ARQ. Nodes using this metric often take advantage of neighbors in the transitional region (high-variance links). Our results also show that reception-based forwarding strategies are more efficient than purely distance-based strategies; relative blacklisting schemes reduce disconnections and achieve higher delivery rates than absolute blacklisting schemes; and that ARQ schemes become more important in larger networks.

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            cover image ACM Conferences
            SenSys '04: Proceedings of the 2nd international conference on Embedded networked sensor systems
            November 2004
            338 pages
            ISBN:1581138792
            DOI:10.1145/1031495

            Copyright © 2004 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 3 November 2004

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            Overall Acceptance Rate174of867submissions,20%

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