期刊文献+

基于LEACH协议的多因子可靠数据融合优化策略 被引量:3

Reliable Data Aggregation Strategy of Multi-optimized Factors Based on LEACH Algorithm
下载PDF
导出
摘要 针对无线传感网中节点部署密度大、数据冗余度高、能量有限和易遭攻击等问题,提出基于LEACH算法的多因子可靠数据融合优化策略。该策略对LEACH算法做出3方面优化改进:在数据融合的相似度计算中增加两个可靠性优化因子MN-LEACH和LF-LEACH;在数据传输中采用多路径传输优化因子MT-LEACH。在敌对环境中,为避免大量恶意节点干扰真实数据,提高数据融合精确度,首先对突发的非线性噪声数据采用拉普拉斯函数而非高斯函数进行过滤,然后采用MN-LEACH优化因子计算相似度,通过加权平均进行数据融合,最后采用LF-LEACH优化因子对链路传输进行检测,并在传输时采用MT-LEACH优化因子,从而使链路负载更加均衡。实验结果表明,该策略与传统LEACH算法相比,在数据融合精确度、信噪比及能耗等方面有明显的优势。 Owing to the deployment of nodes in high density and limited energy,the wireless sensor nodes have the problems of high data redundancy and are vulnerable to be attacked,and so on.We proposed a reliable data aggregation strategy of multi-optimized factors based on LEACH algorithm in wireless sensor networks.The strategy makes some improvements to optimize the LEACH algorithm in three aspects:two reliable optimizing factors MN-LEACH and LFLEACH are adopted during the calculation of data fusion in the similarity;the optimization of multi-path transmission factor MT-LEACH is used for data transmission.Firstly,in a hostile environment,Laplace is used instead of Gauss function to filter the emergent and nonlinear noise data in order to avoid a large number of malicious nodes interfering with real data and improve the accuracy of data fusion,and then we used MN-LEACH optimizing factor to calculate similarity and average the weight for data aggregation.Finally,we used optimization of LF-LEACH factor to detect the link transmission,and adopted the MT-LEACH optimizing factor in the process of transmission as well,so that the load of links will be balanced.The experimental results show that the strategy outperforms the traditional LEACH strategy,in terms of accuracy of data aggregation,signal-to-noise ratio and energy consumption,and so on.
出处 《计算机科学》 CSCD 北大核心 2014年第B11期162-167,共6页 Computer Science
基金 国家自然科学基金项目(61379079)资助
关键词 无线传感网 LEACH算法 数据融合 链路故障 精确度 Wireless sensor networks LEACH algorithm Data aggregation Link fault Accuracy
  • 相关文献

参考文献15

  • 1Renjith P N, Baburaj E. An analysis on data aggregation in wire- less sensor networks[C]//Proceedings of International Confe- rence on Radar, Communication and Computing(ICRCC). Tiru- vannamalai, India, 2012 : 62-71.
  • 2Yuan Fei,Zhan Yi-Ju,Wang Yong-Hua. Data density correlation degree clustering method for data aggregation in WSN[J]. IEEE Sensors Journal, 2014,14 (4) : 1089-] 098.
  • 3Fan Xiang-ning, Song Yu-lin. Improvement on LEACH protocol of wireless sensor network[C]//Proceedings of International Conference on Sensor Technologies and Applications(ICSTA). Valencia, Spain, 2007 .. 260-264.
  • 4Jain A,Chang E Y, Wang Y-F. Adaptive stream resource man- agement using Kalman filters[C]//Proceedings of ACM SIG- MOD International Conference on Management of Data. New York, USA, 2004 .. 11-12.
  • 5Kim J, Jung K, Kim J, et al. Positioning accuracy improvement of laser navigation using unscented Kalman filter[J]. Intelligent Autonomous Systems, Springer, 2013,193 ( 1 ) : 807-816.
  • 6Chan Fu-kai, Wen Chih-yu. Adaptive AOA/TOA localization u- sing fuzzy particle filter for mobile WSNs-[C]//Proceedings of the 73rd IEEE Vehicular-Technology Conference(VTC). Buda- pest, Hungary, 2011 : 1-5.
  • 7Wei G, Ling Y, Guo B, et al. Prediction-based data aggregation in wireless sensor networks:Combining grey model and Kalman filter[J]. Computer Communications, 2011,56 (3) : 359-370.
  • 8Chen Z, Shin K G. OPAG: Opportunistic data aggregation in wireless sensor networks[C]/f/Proceedings of Real-Time Sys- tem Symposium. Barcelona, Spain, 2008 : 345-354.
  • 9Li H, Lin K, Li K. Energy-efficient and high-accuracy secure da- ta aggregation in wireless sensor networks[J]. Computer Com- munication, 2011,34(4) .. 591-597.
  • 10杨庚,李森,陈正宇,许建,杨震.传感器网络中面向隐私保护的高精确度数据融合算法[J].计算机学报,2013,36(1):189-200. 被引量:44

二级参考文献19

  • 1史忠植,高级人工智能,1997年
  • 2Wong S K M,Proc 8th Annual ACMSIGIR Int Conf Research and Development in Information Retrieval,1985年,18页
  • 3冯嘉礼,董占球.基于属性整合的知觉模式生成与识别模型[J].计算机研究与发展,1997,34(7):481-486. 被引量:30
  • 4Madden S, Franklin M J, Hellerstein J M. TAG: A tiny ag gregation service [or ad hoc sensor networks//Proceedings o the 5th Symposium on Operating Systems Design and lmple mentation. New York, USA, 2002:131 146.
  • 5Yi Y Wang X R, Zhu S C, Cao G H. SDAP= A secure hop-by hop data aggregation protocol for sensor networks// Proceedings of the ACM Transactions on Information and System Security. New York, USA, 2008:143.
  • 6Eschenauer L, Gligor V. A key management scheme for distributed sensor networks//Proceedings of the 9th ACMConference on Computer and Communications Security. Washington, DC, USA, 2002:41 47.
  • 7Liu D G, Ning P. Establishing pairwise keys in distributed sensor networks//Proceedings of ACM Transactions on Information and System Security. New York, USA, 2005: 41 77.
  • 8Ruj S, Nayak A, Stojmenovic I. Fully secure pairwise and triple key distribution in wireless sensor networks using corn binatorial designs//Proceedings o[ the 30th IEEE Interna- tional Conference on Computer Communications. Shanghai, China, 2011:326-330.
  • 9Castelluccia C, Mykletun E, Tsudik G. Efficient aggregation of encrypted data in wireless sensor networks//Proeeedings of the 2nd Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services. San Diego, USA, 2005:109-117.
  • 10He W B, Liu X, Nguyen H, Nahrstedt K, Abdelzaher T. PDA: Privacy preserving data aggregation in wireless sensor networks//Proceedings of the 26th IEEE International Conference on Computer Communications. Anchorage, AK, 2007, 2045-2053.

共引文献105

同被引文献20

引证文献3

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部