一种改进的布谷鸟搜索移动信标节点定位方法
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摘要
针对未知节点静止,信标节点移动方式下的无线传感器网络定位问题进行了研究。为进一步提高无线传感器网络节点的定位覆盖率,提出了一种基于改进布谷鸟搜索算法(AF-CS)的多移动信标节点定位算法。通过RSSI定位和DV-Hop算法获取未知节点坐标的粗略值,采用改进布谷鸟搜索算法迭代求解信标节点移动的目标位置,最后对未知节点进行重新定位。仿真结果表明:多移动信标节点定位算法可有效提高对未知节点的定位覆盖率;AF-CS算法对比原始布谷鸟搜索算法(CS)提高了目标函数定位覆盖率,加快了算法收敛速度。在网络拓扑结构变化时,该算法可通过信标节点移动保持对未知节点较高的定位覆盖率。
The localization problem of wireless sensor networks with unknown nodes in stationary state and beacon nodes in mobile state is studied.In order to further improve the localization coverage of wireless sensor network nodes,a multi mobile beacon localization algorithm based on improved cuckoo search algorithm(AF-CS)is proposed.The algorithm obtains the rough value of the unknown node coordinates by RSSI localization and DV-Hop algorithm,and then uses improved cuckoo search algorithm to iteratively solve the target positions of the mobile beacon nodes,and relocate the unknown nodes at the end.The simulation results show that the multi-mobile beacon localization algorithm can effectively improve the localization coverage of the unknown nodes.The AF-CS algorithm improves the target function localization coverage compared with the original CS algorithm,and speeds up the convergence speed of the algorithm.The algorithm can maintain high localization coverage of unknown nodes through the mobility of beacon nodes when the topology of network changes.
The localization problem of wireless sensor networks with unknown nodes in stationary state and beacon nodes in mobile state is studied.In order to further improve the localization coverage of wireless sensor network nodes,a multi mobile beacon localization algorithm based on improved cuckoo search algorithm(AF-CS)is proposed.The algorithm obtains the rough value of the unknown node coordinates by RSSI localization and DV-Hop algorithm,and then uses improved cuckoo search algorithm to iteratively solve the target positions of the mobile beacon nodes,and relocate the unknown nodes at the end.The simulation results show that the multi-mobile beacon localization algorithm can effectively improve the localization coverage of the unknown nodes.The AF-CS algorithm improves the target function localization coverage compared with the original CS algorithm,and speeds up the convergence speed of the algorithm.The algorithm can maintain high localization coverage of unknown nodes through the mobility of beacon nodes when the topology of network changes.
引文
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[2]张伟平,郭亚红,王蒙,等.MR-MC无线传感器网络基于森林的数据收集研究[J].通信学报,2016,37(3):40-47.DOI:10.11959/j.issn.1000-436x.2016051.Zhang W P,Guo Y H,Wang M,et al.Research on Forest-based Data Collection for MR-MC Wireless Sensor Networks[J].Journal of Communications,2016,37(3):40-47.DOI:10.11959/j.issn.1000-436x.2016051.
[3]彭运桃,傅明,袁爱平.基于移动节点的DV-Hop算法优化[J].计算机工程与设计,2017,38(3):581-585.DOI:10.16208/j.issn1000-7024.2017.03.005.Peng Y T,Fu M,Yuan A P.DV-Hop Algorithm Optimization based on Mobile Nodes[J].Computer Engineering and Design,2017,38(3):581-585.DOI:10.16208/j.issn1000-7024.2017.03.005.
[4] Alomari A M.New Path Planning Models for Mobile Anchor-Assisted Localization in Wireless Sensor Networks[J].Wireless Networks,2018(24):2589-2607.DOI:10.1007/s11276-017-1493-2.
[5] Tsai R G,Tsai P H.An Obstacle-Tolerant Path Planning Algorithm for Mo-bile-Anchor-Node-Assisted Localization:[J].Sensors,2018,18(3).DOI:10.3390/s18030889.
[6] Srinath T V.Localization in Resourceconst Rained Sensor Networks Using a Mobile Beacon with In-Ranging[C]∥IFIP International Conference on Wireless and Optical Communication Net-works,2006:301-305.DOI:10.1109/WOCN.2006.1666591.
[7]陈娟,李长庚,宁新鲜,等.基于移动信标的无线传感器网络节点定位[J].传感器与微系统,2009,22(1):121-125.DOI:10.3969/j.issn.1004-1699.2009.01.025.Chen J,Li C G,Ning X X,et al.Wireless Sensor Network Node Localization Based on Mobile Beacons[J].Sensors and Microsystems,2009,22(1):121-125.DOI:10.3969/j.issn.1004-1699.2009.01.025.
[8]张强,张庆,张磊,等.无线传感器网络节点定位中移动信标的路径规划[J].兵器装备工程学报,2016,37(2):144-149.DOI:10.11809/scbgxb2016.02.035.Zhang Q,Zhang Q,Zhang L,et al.Path Planning of Mobile Beacons in Wireless Sensor Network Node Localization[J].Journal of Ordnance and Equipment Engineering,2016,37(2):144-149.DOI:10.11809/scbgxb 2016.02.035.
[9]毛永毅,陈鹏.WSN中基于多功率移动锚节点智能定位算法[J].西安邮电大学学报,2016,21(3):48-53.DOI:10.13682/j.issn.2095-6533.2016.03.007.Mao Y Y,Chen P.WSN Intelligent Location Algorithm based on Multi-power Mobile Anchor Node[J].Journal of Xi’an University of Posts and Telecommunications,2016,21(3):48-53.DOI:10.13682/j.issn.2095-6533.2016.03.007.
[10]明波,黄强,王义民,等.基于改进布谷鸟算法的梯级水库优化调度研究[J].水利学报,2015,46(3):341-349.DOI:10.13243/j.cnki.slxb.2015.03.011.Ming B,Huang QQ,Wang Y M,et al.Research on Cascade Reservoir Optimal Operation based on Improved Cuckoo Algorithm[J].Journal of Water Resources,2015,46(3):341-349.DOI:10.13243/j.cnki.slxb.2015.03.011.
[11]徐浩杰,刘济科,吕中荣.基于布谷鸟算法结构损伤识别[J].中山大学学报,2015,54(4):19-22.DOI:10.13471/j.cnki.acta.snus.2015.04.004.Xu H J,Liu J K,LüZ R.Structural Damage Identification based on Cuckoo Algorithm[J].Journal of Sun Yat-sen University,2015,54(4):19-22.DOI:10.13471/j.cnki.acta.snus.2015.04.004.
[12] Mardini W,Khamayseh Y,Almodawar A A,et al.Adaptive RSSI-Based Localization Scheme for Wireless Sensor Networks[J].Peer-to-Peer Networking and Applications,2016,9(6):991-1004.DOI:10.1007/s12083-015-0370-y.
[13] Tomic S,Mezei I.Improvements of DV-Hop Localization Algorithm for Wireless Sensor Net-works[J].Telecommunication Systems,2016,61(1):93-106.DOI:10.1007/s11235-015-0014-9.
[14] Yang X S,Deb S.Cuckoo Search via Levy Flights[J].Mathematics,2010:210-214.DOI:10.1109/NABIC.2009.5393690.
[15]肖晓丽,李旦江,谭柳斌.基于布谷鸟搜索算法的无线传感器网络节点定位[J].计算机工程与应用,2017,53(2):141-145.DOI:10.3778/j.issn.1002-8331.1504-0251.Xiao X L,Li D J,Tan L B.Location of Wireless Sensor Network Nodes based on Cuckoo Search Algorithm[J].Computer Engineering and Application,2017,53(2):141-145.DOI:10.3778/j.issn.1002-8331.1504-0251.
[16]潘浩,舒服华.基于改进布谷鸟算法的无线传感网络覆盖多目标优化[J].吉林师范大学学报,2017,38(2):125-129.DOI:10.16862/j.cnki.issn1674-3873.2017.02.026.Pan H,Shu F H.Multi-objective Optimization of Wireless Sensor Network Coverage based on Improved Cuckoo Algorithm[J].Journal of Jilin Normal University,2017,38(2):125-129.DOI:10.16862/j.cnki.issn1674-3873.2017.02.026.
[17]王明亮,闫新力,薛君志.基于改进人工鱼群算法的WSN覆盖优化策略[J].微电子学与计算机,2015(6):78-81.DOI:10.19304/j.cnki.issn1000-7180.2015.06.017.Wang M L,Yan X L,Xue J Z.WSN Coverage Optimization Strategy based on Improved Artificial Fish Wwarm Algorithm[J].Microelectronics and Computer,2015(6):78-81.DOI:10.19304/j.cnki.issn1000-7180.2015.06.017.
[18]樊友洪,邓韧,李生林,等.基于混沌遗传算子的人工鱼群算法[J].计算机系统应用,2017,26(3):214-218.DOI:10.15888/j.cnki.csa.005664.Fan Y H,Deng R,Li SL,et al.Artificial Fish Swarm Algorithms Based on Chaotic Genetic Operators[J].Computer System Applications,2017,26(3):214-218.DOI:10.15888/j.cnki.csa.005664.