基于模糊小波聚类混合的多目标覆盖质量评估方法
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摘要
面向双层无线传感器网络覆盖质量评估,设计出基于模糊小波聚类混合的多目标覆盖质量评估方法。建立网络单元概念和双层网络模型,在各汇聚节点开展各子目标预处理。集中建立二次预警机制:设计基于模糊小波神经网络的分析融合子系统,实现一次预警,选出显著低效覆盖单元;构建决策输出子系统,设计基于k均值聚类算法的多等级网络单元评价体系,实现二次预警,并呈现全部低效覆盖单元。实验表明,该方法从覆盖面积、能耗均衡、传输便利等方面综合评估,能够精确判定低效覆盖单元,有助于及时重部署,维护网络健康运行。
For resolving the problem about coverage quality evaluation of wireless sensor networks(WSNs)with 2 layers,a multi-objective evaluation method of coverage quality based on hybrid algorithm of fuzzy wavelet and clustering is proposed.Firstly,the conception of network unit is proposed,and a model of wireless sensor networks with 2 layers is established.Secondly,every sub-objective is pre-processed at the gathing endnodes.Thirdly,twice-alarmed mechanism is introduced,which includes two parts.One part is analysis and fusion sub-system based on fuzzy wavelet neural network.It realizes the first alarm,which checks out the ultra-inefficient coverage units.The other part is decision and output sub-system.In this part,multi-degree evaluation architecture for network units is proposed,which is based on k-means clustering algorithm.Meantime,it achieves the second alarm and shows all of inefficient coverage units.The experimental results validate the proposed method from comprehensive evaluation about coverage,consumption,and transmission.This method can determine inefficient coverage units accurately.Also,it conduces to redeployment timely for healthy running WSNs.
For resolving the problem about coverage quality evaluation of wireless sensor networks(WSNs)with 2 layers,a multi-objective evaluation method of coverage quality based on hybrid algorithm of fuzzy wavelet and clustering is proposed.Firstly,the conception of network unit is proposed,and a model of wireless sensor networks with 2 layers is established.Secondly,every sub-objective is pre-processed at the gathing endnodes.Thirdly,twice-alarmed mechanism is introduced,which includes two parts.One part is analysis and fusion sub-system based on fuzzy wavelet neural network.It realizes the first alarm,which checks out the ultra-inefficient coverage units.The other part is decision and output sub-system.In this part,multi-degree evaluation architecture for network units is proposed,which is based on k-means clustering algorithm.Meantime,it achieves the second alarm and shows all of inefficient coverage units.The experimental results validate the proposed method from comprehensive evaluation about coverage,consumption,and transmission.This method can determine inefficient coverage units accurately.Also,it conduces to redeployment timely for healthy running WSNs.
引文
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[14]谭晓衡,褚国星,张雪静,等.基于高阶累积量和小波变换的调制识别算法[J].系统工程与电子技术,2018,40(1):171-177.TAN X H,CHU G X,ZHANG X J,et al.Modulation recognition algorithm based on high-order cumulants and wavelet transform[J].Systems Engineering and Electronics,2018,40(3):563-570.
[15]张秀杰,高肖霞,张虎,等.基于聚类的新型多目标分布估计算法及其应用[J].系统工程与电子技术,2018,40(1):198-208.ZHANG X J,GAO X X,ZHANG H,et al.Clustering-based multi-objective estimation of distribution algorithm and its application[J].Systems Engineering and Electronics,2018,40(1):198-208.
[16]WEN X,LI X.Observer design based on self-recurrent consequent-part fuzzy wavelet neural network[J].Tsinghua Science and Technology,2016,21(5):544-551.
[17]LI L,WANG W L,XU X L.Multi-objective particle swarm optimization based on global margin ranking[J].Information Sciences,2017,375(1):30-47.
[18]RAJAN G,SUNIL K M,SAIBAL K P.Fuzzy c-means clustering and particle swarm optimization based scheme for common service center location allocation[J].Applied Intelligence,2017,47(10):624-643.
[2]AL-KARAKI J N,GAWANMEH A.The optimal deployment,coverage,and connectivity problems in wireless sensor networks:revisited[J].IEEE Access,2017,5(8):18051-18065.
[3]吴煜玮.无线传感器网络覆盖质量评价与优化方法研究[D].成都:电子科技大学,2015.WU Y W.Research on coverage evaluation and optimization technology for wireless sensor networks[D].Chengdu:University of Electronic Science and Technology of China,2015.
[4]GONZLEZ A V,BRISOLARA L,FERREIRA P R.Efficiency evaluation of strategies for dynamic management of wireless sensor networks[J].Wireless Communications and Mobile Computing,2017:1-13.
[5]KHAN K,LOBIYAL D K.Performance evaluation of different optimization techniques for coverage and connectivity control in backbone based wireless networks[J].Wireless Personal Communications,2017,96(3):4329-4345.
[6]CHENG C F,WANG C W.The target-barrier coverage problem in wireless sensor networks[J].IEEE Trans.on Mobile Computing,2018,17(9):1216-1232.
[7]BENATIA M A,SAHNOUN M,BAUDRY D,et al.Multi-objective WSN deployment using genetic algorithms under cost,coverage,and connectivity constraints[J].Wireless Personal Communications,2017,94(6):2739-2768.
[8]张侃,刘宝平,黄栋.精英遗传改进的非线性灰色神经网络算子与军费开支多目标组合预测应用[J].系统工程与电子技术,2018,40(5):1070-1078.ZHANG K,LIU B P,HUANG D.Elite genetic improved nonlinear gray neural network operator and military expenditure multi-objective combination forecasting application[J].Systems Engineering and Electronics,2018,40(5):1070-1078.
[9]ZDEMIR S,ATTEA B A,KHALILA.Multi-objective evolutionary algorithm based on decomposition for energy efficient coverage in wireless sensor networks[J].Wireless Personal Communications,2013,71(1):195-215.
[10]耿峰,祝小平.一种改进的多传感器多目标跟踪联合概率数据关联算法研究[J].系统仿真学报,2007,19(10):4671-4675.GENG F,ZHU X P.Research of improved joint probabilistic data association algorithm for multisensor-multitarget tracking[J].Journal of System Simulation,2007,19(10):4671-4675.
[11]郭一楠,王春,刘海媛,等.基于区间多目标量子文化算法的无线传感器网络覆盖能效优化[J].控制与决策,2015,30(3):425-432.GUO Y N,WANG C,LIU H Y,et al.Energy-efficient coverage optimization of wireless sensor networks based on interval multi-objective quantum-inspired cultural algorithm[J].Control and Decision,2015,30(3):425-432.
[12]SONG X Y,WEN T,ZHANG D Q,et al.A coverage-aware unequal clustering protocol with load separation for ambient assisted living based on wireless sensor networks[J].China Communications,2016,13(5):47-55.
[13]徐浩,邢清华,王伟.基于模糊多目标规划的防空反导火力分配[J].系统工程与电子技术,2018,40(3):563-570.XU H,XING Q H,WANG W.WTA for air and missile defense based on fuzzy multi-objective programming[J].Systems Engineering and Electronics,2018,40(3):563-570.
[14]谭晓衡,褚国星,张雪静,等.基于高阶累积量和小波变换的调制识别算法[J].系统工程与电子技术,2018,40(1):171-177.TAN X H,CHU G X,ZHANG X J,et al.Modulation recognition algorithm based on high-order cumulants and wavelet transform[J].Systems Engineering and Electronics,2018,40(3):563-570.
[15]张秀杰,高肖霞,张虎,等.基于聚类的新型多目标分布估计算法及其应用[J].系统工程与电子技术,2018,40(1):198-208.ZHANG X J,GAO X X,ZHANG H,et al.Clustering-based multi-objective estimation of distribution algorithm and its application[J].Systems Engineering and Electronics,2018,40(1):198-208.
[16]WEN X,LI X.Observer design based on self-recurrent consequent-part fuzzy wavelet neural network[J].Tsinghua Science and Technology,2016,21(5):544-551.
[17]LI L,WANG W L,XU X L.Multi-objective particle swarm optimization based on global margin ranking[J].Information Sciences,2017,375(1):30-47.
[18]RAJAN G,SUNIL K M,SAIBAL K P.Fuzzy c-means clustering and particle swarm optimization based scheme for common service center location allocation[J].Applied Intelligence,2017,47(10):624-643.