高效实时的无线传感器网络数据融合算法研究
The Research of High Efficient and Real Time Data Aggregation Method Applied in WSNs
摘要: 本文分析了现有的路由及数据融合算法的优势与缺陷，提出了采用n阶移动平均的数据融合算法，充分利用节点间的数据黏性，使算法不仅可以跟踪环境变化，而且能够迅速捕捉到不符合趋势的环境变动。算法借鉴了半静态聚簇路由机制在节点管理机制的优点，使得WSN可以以较高的效率队簇内节点进行管理，使能耗更加均衡。最后设计了多个模拟场景的实验方案，将本文提出的算法进行各方面的可行性分析，阐释了本文方案在过滤冗余信息、延长网络寿命上的有效性。
Abstract: In this paper, the advantages and detects of routing and data fusion algorithm are analyzed, and a new method based on n-average value of split is proposed. By using data viscosity, this algorithm could not only sense the changing of environment, but also find the abnormal change. Using the advantages of semi-static clustering in managing sensor nodes, the efficiency of routing is obviously improved, and the energy consumption is more balanced. At last, a series of experiments are designed to prove the performance of this algorithm, and based on the experiment results, the ef-ficiency in data filtering and prolonging networks’ lifetime is analyzed.
文章引用：刘凯强, 杜韬, 曲守宁. 高效实时的无线传感器网络数据融合算法研究[J]. 传感器技术与应用, 2015, 3(3): 33-46. https://dx.doi.org/10.12677/JSTA.2015.33005

参考文献

[1] 陈正宇, 杨庚, 陈蕾, 许建 (2011) 无线传感器网络数据融合研究综述. 计算机应用研究, 5, 1601-1604+1613.
[2] 黄春燕 (2013) 无线传感器网络下的数据融合研究. 硕士论文, 湖南工业大学, 株洲.
[3] 王金萍 (2013) 传感网异构数据采集及数据融合技术的研究与实现. 硕士论文, 南京邮电大学, 南京.
[4] 傅海波 (2013) 无线传感网中数据融合算法的研究. 硕士论文, 南京邮电大学, 南京.
[5] 郭新 (2013) 无线传感器网络路由协议及数据融合技术研究. 博士论文, 华南理工大学, 广州.
[6] Rehman, A., et al. (2011) A review of wireless sensors and networks’ applications in agriculture. Computer Standards & Interfaces.
[7] Villas, L.A., et al. (2011) A spatial corre-lation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Network, 12, 10-30.
[8] Villas, L.A., et al. (2013) An energy-aware spatio-temporal correlation mechanism to perform efficient data collection in wireless sensor networks. Computer Communications, 36, 1054-1066. http://dx.doi.org/10.1016/j.comcom.2012.04.007 [Google Scholar] [CrossRef] 
[9] Ozdemire, S. (2008) Functional reputation based reliable data aggregation and transmission for wireless sensor networks. Computer Communications, 31, 3941-3953. http://dx.doi.org/10.1016/j.comcom.2008.07.017 [Google Scholar] [CrossRef] 
[10] J.N. Al-Karaki, Ul-Mustafa, R. and Kamal, A.E. (2009) Data ag-gregation and routing in wireless sensor networks: Optimal and heuristic algorithms. Computer Networks, 53, 945-960. http://dx.doi.org/10.1016/j.comnet.2008.12.001 [Google Scholar] [CrossRef] 
[11] Bagaa, M., et al. (2012) Efficient data aggregation with in-network integrity control for WSN. Journal of Parallel and Distributed Computing, 72, 1157-1170. http://dx.doi.org/10.1016/j.jpdc.2012.06.006 [Google Scholar] [CrossRef] 
[12] Fateh, B. and Govindarasu, M. (2013) Energy minimization by ex-ploiting data redundancy in real-time wireless sensor networks. Ad Hoc Network, 11, 1715-1731. http://dx.doi.org/10.1016/j.adhoc.2013.03.009 [Google Scholar] [CrossRef] 
[13] Yu, X., Wu, P., Han, W. and Zhang, Z. (2013) A survey on wireless sensor network infrastructure for agriculture. Computer Standards & Interfaces, 35, 59-64. http://dx.doi.org/10.1016/j.csi.2012.05.001 [Google Scholar] [CrossRef] 
[14] Heinzelman, W.R., Chandrakasan, A. and Balakrishnan, H. (2000) Energy efficient communication protocol for wireless microsensor networks. 2000 Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 4-7 January 2000. http://dx.doi.org/10.1109/hicss.2000.926982 [Google Scholar] [CrossRef] 
[15] Lindsey, S. and Raghavendra, C.S. (2002) PEGASIS: Power efficient gathering in sensor information systems. 2002 IEEE Aerospace Conference Proceedings, 3, 1125-1130. http://dx.doi.org/10.1109/aero.2002.1035242 [Google Scholar] [CrossRef] 
[16] Zhang, J. and Jia, C.-F. (2009) A routing algorithm based on minimal dominating set with weight for wireless sensor networks. Chinese Journal of Sensors and Actuators, 22, 1784-1788.
[17] 许建, 杨庚, 陈正宇, 王海勇, 杨震 (2014) 基于二次独立集的数据融合调度算法. 通信学报, 1, 62-71.
[18] 杜韬 (2014) 能量有效的无线传感器网络路由算法研究. 硕士论文, 山东师范大学, 济南.

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