Abstract：Concerning the problem of high energy consumption caused by data collision and cluster selection process in dynamic clustering target tracking of Wireless Sensor Network (WSN), a dynamic clustering method based on energy optimization for WSN was proposed. Firstly, a time division election transmission model was proposed, which avoided data collision actively to reduce energy consumption of nodes in a dynamic cluster. Secondly, based on energy information and tracking quality, the energy-balanced farthest node scheduling strategy was proposed, which optimized custer head node scheduling. Finally, according to the weighted centroid localization algorithm, the target tracking task was completed. Under the environment of random deployment of nodes, the experimental results show that, the average tracking accuracy of the proposed method for non-linear moving objects was 0.65 m, which is equivalent to that of Dynamic Cluster Member Selection method for multi-target tracking (DCMS), and improved by 45.8% compared to Distributed Event Localization and Tracking Algorithm (DELTA). Compared with DCMS and DELTA, the proposed algorithm can effectively reduce energy consumption of the dynamic tracking clusters by 61.1% and prolong the network lifetime.
[1] 王营冠,王智.无线传感器网络[M].北京:电子工业出版社,2012:12-17.(WANG Y G, WANG Z. Wireless Sensor Network[M]. Beijing:Publishing House of Electronics Industry, 2012:12-17.) [2] RAMYA K, KUMAR K P, RAO V S. A survey on target tracking techniques in wireless sensor networks[J]. International Journal of Computer Science & Engineering Survey, 2012, 3(4):93-108. [3] SOUZA É L, NAKAMURA E F, PAZZI R W. Target tracking for sensor networks:a survey[J]. ACM Computing Surveys, 2016, 49(2):Article No. 30. [4] ZHENG K, WANG H J, LI H, et al. Energy-efficient localization and tracking of mobile devices in wireless sensor networks[J]. IEEE Transactions on Vehicular Technology, 2016, 66(3):2714-2726. [5] ZHENG Y J, CAO N X, WIMALAJEEWA T, et al. Compressive sensing based probabilistic sensor management for target tracking in wireless sensor networks[J]. IEEE Transactions on Signal Processing, 2015, 63(22):6049-6060. [6] VASUHI S, VAIDEHI V. Target tracking using interactive multiple model for wireless sensor network[J]. Information Fusion, 2015, 27(C):41-53. [7] MAO D D, WANG C. Target tracking in wireless sensor networks[J]. Piezoelectrics & Acoustooptics, 2011, 1(4):251-262. [8] FENG J, LIAN B, ZHAO H. Coordinated and adaptive information collecting in target tracking wireless sensor networks[J]. IEEE Sensors Journal, 2015, 15(6):3436-3445. [9] WÄLCHLI M, SKOCZYLAS P, MEER M, et al. Distributed event localization and tracking with wireless sensors[C]//WWIC'07:Proceedings of the 5th International Conference on Wired/Wireless Internet Communications, LNCS 4517. Berlin:Springer, 2007:247-258. [10] 周红波,邢昌风,万福.面向目标跟踪的无线传感器网络动态分簇[J].电光与控制,2013,20(1):14-18.(ZHOU H B, XING C F, WAN F. Dynamic clustering of wireless sensor network for target tracking[J]. Electronics Optics & Control, 2013, 20(1):14-18.) [11] JIA D Y, ZHU H H, ZOU S X, et al. Dynamic cluster head selection method for wireless sensor network[J]. IEEE Sensors Journal, 2016,16(8):2746-2754. [12] 洪榛,俞立,张贵军.多级异构无线传感网高效动态聚簇策略研究[J].自动化学报,2013,39(4):454-460.(HONG Z, YU L, ZHANG G J. Efficient and dynamic clustering scheme for heterogeneous multi-level wireless sensor networks[J]. Acta Automatica Sinica, 2013, 39(4):454-460.) [13] CAI Z X, WEN S, LIU L J. Dynamic cluster member selection method for multi-target tracking in wireless sensor network[J]. Journal of Central South University, 2014, 21(2):636-645. [14] 冯林方,胥布工,刘永桂.WSNs下一种自适应多传感器协同目标跟踪策略[J].计算机应用研究,2010,27(11):4222-4225.(FENG L F, XU B G, LIU Y G. Adaptive multi-sensor collaborative strategy for target tracking in WSNs[J]. Application Research of Computers, 2010, 27(11):4222-4225.) [15] 肖胜,邢昌风,石章松.无线传感器网络中面向目标跟踪的动态分簇方法[J].计算机工程与应用,2012,48(35):88-92.(XIAO S, XING C F, SHI Z S. Dynamic clustering scheme for target tracking in wireless sensor networks[J]. Computer Engineering and Applications, 2012, 48(35):88-92.) [16] 陆娴,彭勇.基于能量高效动态分簇的目标跟踪算法[J].计算机工程,2014,40(10):98-103.(LU X, PENG Y. Target tracking algorithm based on energy-efficient dynamic clustering[J]. Computer Engineering, 2014, 40(10):98-103.) [17] 崔亚峰,史健芳.基于自适应动态簇和预测机制的WSN目标跟踪算法[J].传感技术学报,2015,28(7):1046-1050.(CUI Y F, SHI J F. Target tracking based on adaptive dynamic clusters and prediction mechanism in WSN[J]. Chinese Journal of Sensors and Actuators, 2015, 28(7):1046-1050.) [18] 向智,郭松涛.基于预测的动态分簇目标跟踪算法[J].计算机应用研究,2013,30(3):848-852.(XIANG Z, GUO S T. Prediction-based dynamic clustering target tracking[J]. Application Research of Computers, 2013, 30(3):848-852.) [19] PIVATO P, PALOPOLI L, PETRI D. Accuracy of RSS-based centroid localization algorithms in an indoor environment[J]. IEEE Transactions on Instrumentation and Measurement, 2011, 60(10):3451-3460.
2017, Vol. 37 
