摘要
现存的多媒体传感器网络优化算法,都存在着容易陷入局部最优解的问题.布谷鸟算法利用长距离的搜索可以有效地跳出局部最优解,基于多媒体传感器网络三维感知模型,提出了改进布谷鸟搜索的覆盖增强算法,该算法通过引入精英机制、多维度优化和学习反馈策略来优化多媒体传感器节点的旋转角度以降低覆盖重叠,优化网络覆盖,这是首次利用改进布谷鸟搜索算法来优化网络覆盖.最后,利用仿真实验证明了该算法可以快速有效地优化网络覆盖.
Existing optimization algorithms of wireless multimedia sensor networks（ WMSMs） are easy to fall into local optimal solutions. The cuckoo search algorithm,by using a long distance search,can jump out of local optima effectively. This algorithm is based on the 3 D perception model. The ratio of coverage is improved by introducing elite mechanism,multi-dimensional optimization and learning-feedback strategy to optimize the angle of rotation and reduce overlap.The improved cuckoo search made the first attempt to optimize the network coverage in MSNs.Finally,the simulation results showthat the ratio of coverage is improved by the proposed algorithm.
作者
庄曜铭
吴成东
张云洲
ZHUANG Yao-ming;WU Cheng-dong;ZHANG Yun-zhou(School of Information Science ＆Engineering,Northeastern University,Shenyang 110819,China;School of Robot Science and Engineering,Northeastern University, Shenyang 110819,China)
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2018年第5期609-612,618,共5页
Journal of Northeastern University(Natural Science)
基金
国家留学基金委资助项目
国家自然科学基金资助项目(U1713216)
国家机器人重点专项(2017YBF1300900)
沈阳市科研基金资助项目(17-87-0-00)
关键词
多媒体传感器网络
三维感知模型
覆盖优化
改进布谷鸟搜索
莱维飞行
multimedia sensor networks（MSNs）
3D perception model
coverage optim ization
improved cuckoo search
Levy f l ight
