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Topology Control Algorithms Based on Computational Geometry Graph

Author: ZhangZuoFeng
Tutor: LiuSanYang
School: Xi'an University of Electronic Science and Technology
Course: Applied Mathematics
Keywords: Wireless sensor networks Topology control algorithm MEDel algorithm ECR algorithm
CLC: TN929.5
Type: Master's thesis
Year: 2009
Downloads: 53
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Abstract


Wireless sensor networks in recent years, the rapid development and attaches great importance to the new network technology , network node to the volume of tiny embedded devices , the use of the limited energy of battery-powered . Due to the impact of environmental factors such as , basically impossible to replace the battery , so energy efficiency is the primary task facing wireless sensor networks . Reduce node energy consumption is a primary design goals of the topology control algorithm , topology control algorithm to become one of the core issues in the wireless sensor network research , and topology can improve the efficiency of the MAC and routing protocols , to extend the network lifetime , reducing communications interference . Mainly take into account the energy consumption of the sensor nodes in the wireless communication module , and the energy consumption of the n-th power of the communication distance is proportional to ( lt ; n lt ; 4 ) , the paper proposes a flat topology control algorithm . Computational geometry Delaunay graph has a good nature , to establish a Delaunay graph between wireless sensor nodes , based on the relationship between energy consumption and communication distance to simplify the figure , to retain the minimum energy path , and with the network model MG model combination thereby obtaining MEDel algorithm . The algorithm has the advantage of symmetry and average degree bounded . The clustering algorithm is more efficient than the the plane topology control algorithm . Insufficient for LEACH algorithm , a clustering algorithm -ECR algorithm . Clusters of the algorithm to improve the uniformity and structure as a starting point within the cluster , clustering under the premise based on residual energy , thereby extending the network lifetime , balanced distribution of first cluster , and improve the structure within the cluster .

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