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基于能量因素的无线传感器网络关键节点判定算法 被引量:10

Crucial Node Decision Algorithm Based on Energy in WSNs
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摘要 无线传感器网络中关键节点的判定对网络抗毁性研究具有重要作用。考虑到节点能量受限,该文综合节点剩余生命期和节点"移除"导致的网络能耗值增加,提出一种将能量因素作为衡量节点重要程度的关键节点判定算法(CNDBE),解决了能量受限的无线传感器网络关键节点判定问题。实验结果表明,在对基于CNDBE,最短路径树算法(SPT)和能量感知的关键节点生成树算法(ENCAST)判定得到的关键节点进行保护时,CNDBE具有更强的网络抗毁性和更长的网络生命期。 Crucial node decision plays an important role during the network survivability study. Taking into account the node energy is limited, this study consider both the remaining life of the network and the added value of network energy consumption due to the node failure. A Critical Node Decision algorithm Based on Energy (CNDBE) is proposed, the problem which crucial node decision algorithm based on energy is solved. Simulation results show that, when the node which is decided by crucial node decision algorithm based on energy is protected, the network with CNDBE has a better survivability performance and has a longer lifetime when compared with Shortest Path Tree (SPT) and Energy-Critical Node Aware Spanning Tree for sensor networks (ENCAST).
出处 《电子与信息学报》 EI CSCD 北大核心 2014年第7期1728-1734,共7页 Journal of Electronics & Information Technology
基金 河北省自然科学基金(F2012203179 F2014203239)资助课题
关键词 无线传感器网络 关键节点判定 剩余生命期 抗毁性 Wireless Sensor Networks (WSNs) Crucial Node Decision (CND) Remaining life Survivability
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  • 1齐小刚,张成才,刘立芳.WSN节点重要性和网络抗毁性的分析方法[J].系统工程理论与实践,2011,31(S2):33-37. 被引量:4
  • 2陈勇,胡爱群,胡啸.通信网中节点重要性的评价方法[J].通信学报,2004,25(8):129-134. 被引量:90
  • 3ALBERT R, JEONG H, BARABASF A L. Error and attack tolerance of complex networks[J]. Nature, 2000, 406(7):378-382.
  • 4SUN C C, RUAN S J, SHIE M C. et al. Dynamic contrast enhance- ment based on histogram specification[J]. IEEE Transactions on Con- sumer Electronics, 2005, 51(4):1300-1305.
  • 5CHEN D, LV L, SHANG M S, et al. Identifying influential nodes in complex networks[J]. Physica A: Statistical Mechanics and its Appli- cations, 2011, 391(4): 1777-1787.
  • 6ZHANG X, ZHU J, WANG Q, et al. Identifying influential nodes in complex networks with community structure[J]. Knowledge-Based Systems, 2013, 42: 74-84.
  • 7GAO C, LAN X, ZHANG X G; et al. A bio-inspired methodology of identifying influential nodes in complex networks[J]. PIoS One, 2013, 8(6): e66732.
  • 8WANG J S, WU X P, YAN B, et al. Improved method of node impor- tance evaluation based on node contraction in complex networks[J]. Proeedia Engineering, 2011, 15: 1600-1604.
  • 9TARAS A, JOSE L O, LEANDRO T, et al. An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector[J]. Applied Mathematics & Computation, 2012, 219(4):2186-2193.
  • 10CHEN D B, GAO H, LV L, et al. Identifying influential nodes in large-scale directed networks: the role of clustering[J]. PloS One, 2013, 8(10): e77455.

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