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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78536


    Title: EEGRA: Energy Efficient Geographic Routing Algorithms for Wireless Sensor Network
    Authors: Chen, Tseng-yi;Wei, Hsin-wen;Lee, Che-rung;Hsu, Tsan-sheng;Shih, Wei-kuan
    Contributors: 淡江大學資訊管理學系
    Keywords: Geographic routing;Energy-efficiency;Wireless sensor network;SINR;Distributed routing algorithm
    Date: 2012-12-13
    Issue Date: 2012-10-11 11:53:19 (UTC+8)
    Abstract: Energy efficiency is critical in wireless sensor networks (WSN) for system reliability and deployment cost. The power consumption of the communication in multi-hop WSN is primarily decided by three factors: routing distance, signal
    interference, and computation cost of routing. Several routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or specialized for certain
    WSN architectures. In this paper, we propose two energy efficient geographic routing algorithms (EEGRA) for wireless sensor networks, which are based on existing geographic routing algorithms and take all three factors into account.
    The first algorithm combines the interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained
    optimization problem, and solves it by searching the optimal discretized interference level. We integrate four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, to both EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The results of our experiments show both algorithms conserve sensor’s routing energy 30% ~ 50% comparing to general geographic routing algorithms. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.
    Relation: 2012 International Symposium on Pervasive Systems, Algorithms, and Networks (ISPAN), 11p.
    Appears in Collections:[資訊管理學系暨研究所] 會議論文

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