Node localization of wireless sensor networks based on hybrid bat-quasi-Newton algorithm
YU Quan1, SUN Shunyuan1,2, XU Baoguo1, CHEN Shujuan3, HUANG Yanli4
1. School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China;
2. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, (Jiangnan University), Wuxi Jiangsu 214122, China;
3. Henrich Electronic (Suzhou) Company Limited, Suzhou Jiangsu 215000, China;
4. School of Communication, Shandong Normal University, Jinan Shandong 250000, China
Concerning the problem that the least square method in the third stage of DV-Hop algorithm has low positioning accuracy, a localization algorithm was proposed which is the fusion of hybrid bat-quasi-Newton algorithm and DV-Hop algorithm. First of all, the Bat Algorithm (BA) was improved from two aspects: firstly, the random vector β was adjusted adaptively according to bats' fitness so that the pulse frequency had the adaptive ability. Secondly, bats were guided to move by the average position of all the best individuals before the current iteration so that the speed had variable performance; Then in the third stage of DV-Hop algorithm the improved bat algorithm was used to estimate node location and then quasi-Newton algorithm was used to continue searching for the node location from the estimated location as the initial searching point. The simulation results show that, compared with the traditional DV-Hop algorithm and the improved algorithm of DV-Hop based on bat algorithm(BADV-Hop), positioning precision of the proposed algorithm increases about 16.5% and 5.18%, and the algorithm has better stability, it is suitable for high positioning precision and stability situation.
ESTRIN D,GOVINDAN R,HEIDEMANN J. Next century challenges: scalable coordination in sensor network[C]// Proceedings of the 5th ACM/IEEE International Conference on Mobile Computing and Networks. Washington, DC: IEEE Computer Society,1999: 263-270.
[2]
MA Z,SUN Y,MEI T. Survey on wireless sensor network[J]. Journal on Communications, 2004,25(4):114-124.(马祖长,孙怡宁,梅涛. 无线传感器网络综述[J].通信学报,2004,25(4):114-124.)
[3]
ZHAO Y, QIAN Z, SHANG X, et al. PSO localization algorithm for WSN nodes based on modifying average hop distance[J]. Journal on Communications, 2013,34(9):105-114.(赵雁航,钱志鸿,尚小航,等.基于跳距修正粒子群优化的WSN定位算法[J].通信学报,2013,34(9):105-114.)
[4]
HONG Y, SEZAKI K, DENG P, et al. An improved DV-Hop localization algorithm with reduced node location error for wireless sensor networks[J].IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008,91(8):2232-2236.
[5]
CHEN H, SEZAKI K,DENG P, et al. An improved DV-Hop localization algorithm for wireless sensor networks[C]// Proceedings of the 3rd IEEE Conference on Industrial Electronics and Applications. Piscataway: IEEE, 2008: 1557-1561.
[6]
TIAN S, ZHANG X, LIU P, et al.A RSSI-based DV-Hop algorithm for wireless sensor networks[C]// Proceedings of the 2007 International Conference on Wireless Communications, Networking and Mobile Computing. Piscataway: IEEE,2007: 2555-2558.
[7]
ZHOU Z,XIAO M,LIU L,et al. An improved DV-HOP Localization algorithm[C]// Proceedings of the 2009 2nd International Symposium on Information Science and Engineering. Piscataway: IEEE,2009: 598-602.
[8]
YANG X, PAN W. DV-Hop localization algorithm based on RSSI ratio correction in wireless sensor network[J]. Transducer and Microsystem Technologies, 2013,32(7):126-135.(杨祥,潘玮.基于RSSI比值修正的无线传感器网络DV-Hop定位算法[J].传感器与微系统,2013,32(7):126-135.)
[9]
WEN J,FAN X,WU,X. DV-Hop localization algorithm based on the RSSI hop correction[J].Chinese Journal of Sensors and Actuators, 2014,27(1):113-117.(温江涛,范学敏,吴希军.基于RSSI 跳数修正的DV-Hop改进算法[J].传感技术学报,2014,27(1):113-117.)
[10]
ZHAO J,FU Y,MEI J. An improved DV-Hop localisation algorithm based on particle swarm optimisation[J].Computer Applications and Software, 2012,29(12):69-76. (赵吉,傅毅,梅娟. 基于粒子群算法的改进DV-Hop定位算法[J].计算机应用与软件,2012,29(12):69-76.)
[11]
LI M,XIONG W,GUO L. Improvement of DV-Hop localization based on artificial bee colony algorithm[J].Computer Science, 2013,40(1):33-36.(李牧东,熊伟,郭龙.基于人工蜂群算法的DV-Hop定位改进[J].计算机科学,2013,40(1):33-36.)
[12]
LIU Y,LYU X,WANG X. Application of hybrid genetic algorithm in WSNs localization[J].Transducer and Microsystem Technologies,2014,33(2):150-153.(刘彦隆,吕显朋,王相国.混合遗传算法在WSNs定位中的应用[J].传感器与微系统,2014,33(2):150-154.)
[13]
ZHAO S,SUN M,TANG Y.GASA-based localization algorithm for wireless sensor networks[J].Computer Applications and Software, 2009,26(10):189-192.(赵仕俊,孙美玲,唐懿芳. 基于遗传模拟退火算法的无线传感器网络定位算法[J]. 计算机应用与软件,2009,26(10):189-192.)
[14]
ZHAO W,LI F,ZHENG H, et al. Node localization method of WSNs based on BADV-Hop[J].Transducer and Microsystem Technologies, 2014,33(10):118-124.(白伟,李凤英,郑海洋,等.基于BADV-Hop的无线传感器网络节点定位方法[J].传感器与微系统,2014,33(10):118-124.)
[15]
YANG X S,GANDOMI A H. Bat algorithm: a novel approach for global engineering optimization[J].Engineering Computations,2012,29(5): 464-483.
2015, Vol. 35 
