基于可视化的森林火灾监测节点优化部署策略
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摘要
由于森林防火传感器节点成本高、部署区域大,优化部署效率是其应用时所面临的主要问题。为使节点部署成本与覆盖效率之间相互协调,提出一种基于可视化的森林火灾监测节点优化部署策略。以实际森林环境为基础,对预置节点做可视域分析;通过建立节点可视域面积关联矩阵,使用互信息算法贪婪地选择覆盖效率最高的预置节点;在预算受限时利用子模算法预估最佳的节点部署数量。该策略既保证了覆盖效率,又减少了部署成本,是一种高性价比的森林火灾监测节点部署策略。
Because of the high cost of forest fire monitoring sensor nodes and large deployment area,the optimization of the deployment efficiency was the main problem in application.In order to coordinate the deployment cost and coverage efficiency of nodes,a visualization-based optimal monitoring nodes deployment strategy was proposed.This strategy was based on a practical dataset from the forest environment,and made viewshed analysis of the candidate nodes.The mutual information algorithm was used to greedily select the location with the highest coverage efficiency by using the viewshed area association matrix of the nodes.The optimal number of nodes was calculated under the cost constraints by the submodular algorithm.This strategy ensured coverage efficiency,and reduced deployment cost.It was a cost-effective deployment strategy for forest fire monitoring nodes.
Because of the high cost of forest fire monitoring sensor nodes and large deployment area,the optimization of the deployment efficiency was the main problem in application.In order to coordinate the deployment cost and coverage efficiency of nodes,a visualization-based optimal monitoring nodes deployment strategy was proposed.This strategy was based on a practical dataset from the forest environment,and made viewshed analysis of the candidate nodes.The mutual information algorithm was used to greedily select the location with the highest coverage efficiency by using the viewshed area association matrix of the nodes.The optimal number of nodes was calculated under the cost constraints by the submodular algorithm.This strategy ensured coverage efficiency,and reduced deployment cost.It was a cost-effective deployment strategy for forest fire monitoring nodes.
引文
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[2]CULLER D E,HILL J L.System architecture for wireless sensor networks[J].Computer Science University of California,Berkeley,2003:11-17.
[3]刘陈,蔡婷.一种基于RSSI向量的传感器网络定位算法[J].山东大学学报(工学版),2016,46(3):23-30.LIU Chen,CAI Ting.A localization algorithm based on RSSI vector for wireless sensor networks[J].Journal of Shandong University(Engineering Science),2016,46(3):23-30.
[4]符修文,李文锋,段莹.分簇无线传感器网络级联失效抗毁性研究[J].计算机研究与发展,2016,53(12):2882-2892.FU Xiuwen,LI Wenfeng,DUAN Ying.Invulnerability of clustering wireless sensor network towards cascading failures[J].Journal of Computer Research and Development,2016,53(12):2882-2892.
[5]张长森,胡宇鹏,陈鹏鹏.基于Quorum的低占空比WSNs最优延迟可靠路由算法[J].计算机应用与软件,2016,33(11):79-83.ZHANG Changsen,HU Yupeng,CHEN Pengpeng.Optimalreliable delay routing algorithm for low duty cycle wsns based on quorum[J].Computer Applications and Software,2016,33(11):79-83.
[6]HUANG C F,TSENG Y C.The coverage problem in a wireless sensor network[J].Mobile Networks&Applications,2005,10(4):519-528.
[7]HEO N,VARSHNEY P K.A distributed self spreading algorithm for mobile wireless sensor networks[C]//Wireless Communications and Networking.NewYork,USA:IEEE,2003:1597-1602.
[8]O'ROURKE J.Art gallery theorems and algorithms[M].Oxfordshire:Oxford University Press,1987:1-10.
[9]SLIJEOCEVIC S,POTKONJAK M.Power efficient organization of wireless sensor networks[J].Proceedings of Icc Jun,2001,2:472-476.
[10]赵璠,舒立福,周汝良.林火行为蔓延模型研究进展[J].世界林业研究,2017,30(2):46-50.ZHAO Fan,SHU Lifu,ZHOU Ruliang,Areview of wildland fire spread modelling[J].World Forestry Research,2017,30(2):46-50.
[11]LU G.Design of low power wsn node in wild environment[J].American Journal of Network and Communications,2017,6(2):47-53.
[12]KIM Y H,RANA S,WISE S.Exploring multipleviewshed analysis using terrain features and optimisation techniques[J].Computers&Geosciences,2004,30(9):1019-1032.
[13]BAO S,XIAO N,LAI Z,et al.Optimizing watchtower locations for forest fire monitoring using location models[J].Fire Safety Journal,2015,71:100-109.
[14]REVELLE C.Review,extension and prediction in emergency service siting models[J].European Journal of Operational Research,1989,40(1):58-69.
[15]SCHILLING D,ELZINGA D J,COHON J,et al.The team-fleet models for simultaneous facility and equipment Siting[J].Transportation Science,1979,13(2):163-175.35
[16]LIU Q F,LI Y E.Improved sample method for medical image registration based on mutual information:improved sample method for medical image registration based on mutual information[J].Journal of Computer Applications,2010,30(4):947-949
[17]KRAUSE A,GUESTRIN C.Near-optimal observation selection using submodular functions[C]//AAAI Conference on Artificial Intelligence.Vancouver,Canada:DBLP,2007:1650-1654.
[18]GUESTRIN C,KRAUSE A,SINGH A P.Near optimal sensor placements in Gaussian processes[C]//International Conference on Machine Learning.Bonn,Germany:ACM,2005:265-272.
[19]NEMHAUSER G L,WOLSEY L A,FISHER M L.An analysis of approximations for maximizing submodular set functions[J].Mathematical Programming,1978,14(1):265-294.
[20]KRAUSE A,LESKOVEC J,GUESTRIN C,et al.Efficient sensor placement optimization for securing large waterdistribution networks[J].Journal of Water Resources Planning&Management,2008,134(6):516-526.