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基于新型局域世界的无线传感器网络模型研究 被引量:1

Study of Wireless Sensor Network Model Based on Novel Local World Networks
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摘要 现有的无线传感器网络模型较少考虑能量异构和负载均衡问题,并且对模型的评价方法有限。提出了基于新型局域世界的无线传感器网络模型,充分考虑能量异构、节点局域性以及加入负载调整因子,构建基于能量感知局域世界的无线传感器网络模型和基于负载调整局域世界的无线传感器网络模型,完善原有模型。利用MATLAB进行仿真,研究模型度分布等,提出用复杂网络的特征参数对模型进行评价,引入社会网络的中心性,更深入地评价网络节点重要性。理论分析和实验证明,该模型可以较好地描述无线传感器网络,可进一步优化网络和提高通信能力,同时复杂网络的研究思想对无线传感器研发具有指导作用。 The existing wireless sensor network model seldom considers heterogeneous and load balance.And evaluation method of the model is limited.This paper proposed a wireless sensor network model based on novel local world network and took heterogeneous as well as node localization and local adjustment factor into account.The new model concludes wireless sensor network model based on energy aware local world network and wireless sensor network model based on load regulation local world network,which perfects the original model.By using MATLAB to simulate,this paper studied the degree distribution of the model and proposed an evaluation method of the model by comparing the characteristic parameters of complex networks.It introduces centrality in social network field to evaluate the importance of network node more deeply.Both theoretical analysis and experiment show that new model can describe the wireless sensor network well and can further optimize the network as well as improving communication ability.The idea of complex network used in this paper has positive effect on the research of wireless networks.
出处 《计算机科学》 CSCD 北大核心 2015年第S1期279-284,共6页 Computer Science
基金 国家自然科学基金(71901194 91324203 11131009) 中财121青年博士发展基金(QBJ1410)资助
关键词 无线传感器网络 局域世界 能量感知 负载调整 度分布 Wireless sensor network,Local world,Energy aware,Load regulation,Degree distribution
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  • 1Watts DJ,Strogatz SH.Collective dynamics of small-world networks. Nature . 1998 被引量:9
  • 2Barabasi A L,Albert R.Emergence of scaling in random networks. Science . 1999 被引量:4
  • 3Ravasz E,Barabasi A-L.Hierarchical organization in complex networks. Physical Review . 2003 被引量:1
  • 4Martin Rosvall,Carl T. Bergstrom.Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences of the United States of America . 2008 被引量:2
  • 5Gross D,Shortle J F,Thompson J M, et al.Fundamentals of queueing theory. . 2013 被引量:1
  • 6Intel Lab Data. http://db.csail.mit.edu/labdata/labdata.html . 2004 被引量:1
  • 7Blondel VD,Guillaume J L,Lambiotte R,et al.Fast Unfolding ofCommunities in Large Networks. Journal ofStatistical Mechan-ics:Theory and Experiment . 2008 被引量:1
  • 8Baras J S,Hovareshti P.Efficient and robust communication topologies for distributed decision making in networked systems. Proceedings of 47th IEEE Conference on Decision and Control . 2008 被引量:1
  • 9Li Hui-Jia,Xu Bing-Ying,Zheng Liang,Yan Jia.Integrating attributes of nodes solves the community structure partition effectively. Modern Physics Letters A . 2014 被引量:1
  • 10Freeman L C.Centrality in social networks: conceptual clarification. Social Networks . 1979 被引量:6

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