计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 319-321.doi: 10.11896/j.issn.1002-137X.2017.6A.073
熊志利,瞿少成
XIONG Zhi-li and QU Shao-cheng
摘要: 首先, 总结和分析 无线传感网络节点自定位的基本原理、分类,得到自定位技术的本质是一个优化最优问题;其次,在该基础上,以遗传算法、模拟退火算法、进化策略和差分进化算法作为研究对象,针对这4种典型定位算法的优缺点展开讨论;然后,结合GA算法和SA算法各自的优势,提出一种遗传-模拟退火算法,从而增加初始种群的多样性,避免在传感器节点选择中陷入局部最优解的问题;最后,将上述改进方法应用到无线传感器网络节点定位中,用MATLAB分别对GA算法、SA算法和GSA算法进行仿真比较,验证了GSA算法的优势,为无线传感节点自定位技术提供新的参考。
[1] SAVARESE C,RABAEY J M,BEUTEL J.Locationing in Distributed Ad-hoc Wireless Sensor Network[C]∥Proceedings of IEEE International Conference on Acoustics,Speech and Signal.(ICASSP).IEEE Computer Society,2001:2037-2040. [2] WANT R,HOPPER A,FALCAO V,et al.The Active Badge Location System[J].Journal of ACM Transactions on Information Systems(TOIS),1992,10(1):91-102. [3] DUCKETT T.A Genetic Algorithm for Simultaneous Localization and Mapping[C]∥Proceedings of the 2003 IEEE International Conference on Robotics & Automation.2003:434-439. [4] KANNAN A A,MAO G Q,VUCETIC B.Simulated Annealing Based Localization in Wireless Sensor Network[C]∥Procee-dings of the 30th IEEE Conference on Local Computer Networks.2005:513-514. [5] TERWILLIGER M,GUPTA A,KHOKHAR A,et al.Localization Using Evolution Strategies in Sensornets[C]∥The 2005 IEEE Congress on Evolutionary Computation 2005.2005:322-327. [6] TAM V,CHENG K Y,LUI K S.Using Micro-genetic Algorithms to Improve Localizationin Wireless Sensor Networks[J].Journal of Communications,2006,V1(4):1-10. [7] CHEHRI A,FORTIER P,TARDIF P M.Geo-location with Wi-reless Sensor Networks using Non-linear Optimization[J].International Journal of Computer Science and Network Security(IJCSNS),2008,8(1):145-154. [8] 黄仑.无线传感器网络定位算法研究[D].上海:上海交通大学,2006. [9] 刘利姣.无线传感器网络节点自定位研究[D].武汉:华中师范大学,2007. [10] ZHANG Q G,WANG J H,JIN C.Genetic Algorithm Based Wi-reless Sensor Network Localization[C]∥Fourth International Conference on Natural Computation.2008:608-613. |
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