A CSMA-based approach for detecting composite data aggregate events with collaborative sensors in WSN

Nowadays, wireless sensor networks are widely used to monitor real time events and answer the ad hoc queries from a certain member node. However, computing and maintaining the information of aggregate queries in event monitoring wireless sensor networks incurs high spatial and temporal overhead for storage and transmission where potentially high volumes of unnecessary data may run through with changing time. Failure of processing that data can lead to unsuccessful event detection which can be very dangerous and costly in real world application. In order to reduce the overhead caused by unnecessary data for aggregate, suppression techniques such as data fusion, data sharing, data prediction, lossless data compression and base station side query rewriting are widely discussed in the WSN research community. In this paper, a technique which makes use of the spatial data relationship of local sensor nodes collaboratively is proposed to rein the detection of composite events with data aggregate. An empirical study is carried out to show the efficiency of the new technique. In addition, the new algorithm is compared to the previous event detection algorithms without spatial data suppression technique to demonstrate the significant performance gains.