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Multi-sink Deployment Strategy for Wireless Sensor Networks Based on Improved Particle Swarm Clustering Optimization Algorithm
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作者 李芳 丁永生 +1 位作者 郝矿荣 姚光顺 《Journal of Donghua University(English Edition)》 EI CAS 2016年第5期689-693,共5页
In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deployi... In wireless sensor networks(WSNs) with single sink,the nodes close to the sink consume their energy too fast due to transferring a large number of data packages,resulting in the "energy hole" problem.Deploying multiple sink nodes in WSNs is an effective strategy to solve this problem.A multi-sink deployment strategy based on improved particle swarm clustering optimization(IPSCO) algorithm for WSNs is proposed in this paper.The IPSCO algorithm is a combination of the improved particle swarm optimization(PSO) algorithm and K-means clustering algorithm.According to the sink nodes number K,the IPSCO algorithm divides the sensor nodes in the whole network area into K clusters based on the distance between them,making the total within-class scatter to minimum,and outputs the center of each cluster.Then,multiple sink nodes in the center of each cluster can be deployed,to achieve the effects of partition network reasonably and deploy multi-sink nodes optimally.The simulation results show that the deployment strategy can prolong the network lifetime. 展开更多
关键词 clustering deployment partition scatter rotation reasonably lifetime recognize Recognition coordinates
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Identification Method of Urban Road Traffic Conditions in the Internet of Vehicles Environment
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作者 王建强 李世威 张玉召 《Journal of Donghua University(English Edition)》 EI CAS 2015年第2期264-267,共4页
In accordance with the specific deployment way of infrastructure and data exchanging technology in the Internet of vehicles(IoV),the acquiring and calculating method for three basic traffic flow parameters in IoV scen... In accordance with the specific deployment way of infrastructure and data exchanging technology in the Internet of vehicles(IoV),the acquiring and calculating method for three basic traffic flow parameters in IoV scenarios,including traffic flow,speed and density,was researched.Considering the complexity of traffic flow and fuzziness of human thinking,fuzzy c-means clustering algorithm based on the genetic algorithm(GA-FCM) was adopted in soft classification of urban road traffic conditions.Genetic algorithm(GA) introduced into fuzzy clustering could avoid fuzzy c-means(FCM) algorithm converging to the local infinitesimal point,which made the cluster result more precise.By means of computer simulation,data exchanging environment in IoV was imitated,and then test data set was divided into four parts.The simulation indicates that the identification method is feasible and effective for urban road traffic conditions in IoV scenarios. 展开更多
关键词 traffic scenarios clustering deployment infrastructure congestion calculating exchanging thinking accordance
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