WSNs中基于双层抑制数据冗余算法
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摘要
针对无线传感网络的海量数据的处理问题,提出基于双层抑制数据冗余算法;在第一层,传感节点引用皮尔森相关算法压缩数据,减少数据量;在第二层,由融合节点引用K均值聚类算法消除邻居节点间的数据冗余,进行数据聚类,降低数据间的冗余;实验数据表明:提出的TSDR算法有效地降低数据冗余。
For the issue of analyzing the big data in Wireless Sensor Networks( WSNs),the two-levelbased suppressing data redundancy( TSDR) algorithm was proposed. At the first level,the sensors use a data compressionmodel based on the Pearson coefficient in order to reducethe amount of data collected periodically in each sensor. The aim is to reduce the number of data. At the second level,the aggregator node had an objective to eliminate data redundancycollected by neighboring nodes by using an adapted version of K-means clustering method. Simulation on real data sensorsshows the effectiveness of our technique in reducing the big datacollected in WSNs.
For the issue of analyzing the big data in Wireless Sensor Networks( WSNs),the two-levelbased suppressing data redundancy( TSDR) algorithm was proposed. At the first level,the sensors use a data compressionmodel based on the Pearson coefficient in order to reducethe amount of data collected periodically in each sensor. The aim is to reduce the number of data. At the second level,the aggregator node had an objective to eliminate data redundancycollected by neighboring nodes by using an adapted version of K-means clustering method. Simulation on real data sensorsshows the effectiveness of our technique in reducing the big datacollected in WSNs.
引文
[1] NIAYESH G,ABU K. Collaborative Mobile Sink Sojourn Time Optimization Scheme for Cluster-based Wireless Sensor Networks[J]. IEEE Sensors Journal,2018,4(7):23-31.
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[10] IDREES A,HARB H,JABER A,et al. Abou Taam. Adaptive distributed energy-saving data gathering technique for wireless sensor networks,IEEE 13th International Conference on Wireless and Mobile[C]//Computing,Networking and Communications(Wi Mob),2017:55-62.
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[12] JACQUES B,ABDALLAH M,MAGUY M. A Two Tiers Data Aggregation Scheme for Periodic Sensor Networks[J]. Ad Hoc&Sensor Wireless Networks,2014,21(1/2):77-100.
[2]江禹生,冯砚毫,管芳,等.无线传感网非测距三维节点定位算法[J].西安电子科技大学学报(自然科学版),2016,39(5):140-148.
[3] TAREQ A,A Survey on Environmental Monitoring Systems using Wireless Sensor Networks[J]. Journal of Networks,2016,10(1):606-615.
[4] KOFI S A,CRISTIANO T,WENDI H. Water Quality Monitoring Using Wireless Sensor Networks:Current Trends and Future Research Directions[J]. ACM Transactions on Sensor Networks(TOSN),2017,13(1):23-32.
[5] JOSHI P P,KANADE S S,JOSHI S P. Wireless Sensor Network and Monitoring of Crop Field[J]. IOSR Journal of Electronics and Communication Engineering(IOSR-JECE),2017,12(1):23-28.
[6] DEEPIKA G,RAJAPIRIAN P. Wireless sensor network in precision agriculture:A survey[C]//International Conference on Emerging Trends in Engineering,Technology and Science(ICETETS),Pudukkottai,India,2016:24-26.
[7] JAHEDA S A,SUMEDHA S. Comparative Study of Optimal Clustering Techniques in Wireless Sensor Network:A Survey[C]//Proceedings of the ACM Symposium on Women in Research(WIR),Indore,India,2016:21-22.
[8] LIN Hongzhi,WEI Wei,ZHAO Ping. Energy-efficient compressed data aggregation in underwater acoustic sensor networks[J]. Wireless Networks Journal,2016,22(6):1985-1997.
[9] YIN Yihang,LIU Fengzheng,ZHOU Xiang. An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks[J]. Journal of Sensors,2015,15(2):19443-19465.
[10] IDREES A,HARB H,JABER A,et al. Abou Taam. Adaptive distributed energy-saving data gathering technique for wireless sensor networks,IEEE 13th International Conference on Wireless and Mobile[C]//Computing,Networking and Communications(Wi Mob),2017:55-62.
[11] LIANG Yao,LI Yimei. An Efficient and Robust Data Compression Algorithm in Wireless Sensor Networks[J]. IEEE Communications Letters,2014,18(3):439-442.
[12] JACQUES B,ABDALLAH M,MAGUY M. A Two Tiers Data Aggregation Scheme for Periodic Sensor Networks[J]. Ad Hoc&Sensor Wireless Networks,2014,21(1/2):77-100.