Improving the data processing in WSNs through combination of a distributed approach and statistical techniques

Wireless sensor networks (WSNs) have received a lot of attentions from both academic and industrial communities due to the wide range of applications they can provide. In this sort of network, maximizing the lifetime of sensor nodes as well as providing valid data in real-time are essential issues due to the real-time requirement of data and the resource limitation of sensor nodes. The distributed database approach has proven to be an effective approach to manage the large amount of sensed data in an energy-efficient manner and to reduce the response time of data processing. This work proposes a new query processing algorithm, which relies on a combination of a distributed database architecture with statistical techniques for improving the data processing in WSNs. The proposed query processing algorithm and the architecture were evaluated based on the temperature measures of an environment as a case study.