A Suffix-Based Enhanced Technique for Data Aggregation in Periodic Sensor Networks

Data aggregation in wireless sensor networks (WSN) has been proven as an effective technique for eliminating redundancy and forwarding only the extracted information from the raw data. Furthermore, by doing so data aggregation can often reduce the communication cost and extend the whole network lifetime. In this paper we study a new prefix-suffix filtering technique for data aggregation in periodic sensor networks (PSN). We investigate the problem of finding all pair of nodes generating similar data sets. We added a new suffix frequency filter technique to the existing prefix frequency filtering. Our goal is to integrate additional filtering technique in order to decrease the latency of the aggregation phase. Our simulation results show that our technique outperforms existing prefix filtering technique in reducing energy consumption.