期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2015
卷号：8
期号：3
页码：53-64
DOI：10.14257/ijgdc.2015.8.3.06
出版社：SERSC
摘要：Wireless Sensor Networks (WSNs) have characteristics of large size, limited resources, large amount of transmission data, and so on. In order to reduce the redundancy of sensed data and decrease network data traffic. We applied CS to clustered structure, proposed Low-Latency Compressed Sensing model (LLCS) which is based on the spatial- temporal correlation of sensed data, the model is also capable of processing sparse abnormal events which is a crucial feature in WSNs. We analyzed the relationship between compression ratio and sampling rounds and verified the abnormal event processing method. The results of simulation experiments using the real data show that LLCS could reduce data transfer volume significantly and process abnormal readings effectively.
