An Efficient Method for Cleaning Dirty-Events over Uncertain Data in WSNs  

作　　者：陈默 于戈 谷峪 贾子熙 王艳秋 

机构地区：[1]CCF [2]ACM [3]Software College,Northeastern University [4]College of Information Science and Engineering,Northeastern University [5]IEEE

出　　处：《Journal of Computer Science & Technology》2011年第6期942-953,共12页计算机科学技术学报（英文版）

基　　金：supported by the National Basic Research 973 Program of China under Grant No.2012CB316201;the National Natural Science Foundation of China under Grant Nos.61003058,60933001;the Fundamental Research Funds for the Central Universities under Grant No.N090104001

摘　　要：Event detection in wireless sensor networks （WSNs） has attracted much attention due to its importance in many applications. The erroneous abnormal data generated during event detection are prone to lead to false detection results. Therefore, in order to improve the reliability of event detection, we propose a dirty-event cleaning method based on spatio-temporal correlations among sensor data. Unlike traditional fault-tolerant approaches, our method takes into account the inherent uncertainty of sensor measurements and focuses on the type of directional events. A probabilitybased mapping scheme is introduced, which maps uncertain sensor data into binary data. Moreover, we give formulated definitions of transient dirty-event （TDE） and permanent dirty-event （PDE）, which are cleaned by a novel fuzzy method and a collaborative cleaning scheme, respectively. Extensive experimental results show the effectiveness of our dirty-event cleaning method.Event detection in wireless sensor networks （WSNs） has attracted much attention due to its importance in many applications. The erroneous abnormal data generated during event detection are prone to lead to false detection results. Therefore, in order to improve the reliability of event detection, we propose a dirty-event cleaning method based on spatio-temporal correlations among sensor data. Unlike traditional fault-tolerant approaches, our method takes into account the inherent uncertainty of sensor measurements and focuses on the type of directional events. A probabilitybased mapping scheme is introduced, which maps uncertain sensor data into binary data. Moreover, we give formulated definitions of transient dirty-event （TDE） and permanent dirty-event （PDE）, which are cleaned by a novel fuzzy method and a collaborative cleaning scheme, respectively. Extensive experimental results show the effectiveness of our dirty-event cleaning method.

关 键 词：wireless sensor networks event detection dirty-event UNCERTAINTY CLEAN 

分 类 号：TN929.5[电子电信—通信与信息系统] TP212.9[电子电信—信息与通信工程]