Energy Efficient Data Processing in Sensor Networks

The sensor nodes in a Wireless Sensor Network(WSN) are tiny devices operating on batteries and employing low-power radio transceivers to enable communication. Minimizing energy consumption has been a major objective at all levels in sensor networks. In this paper, we present, a data processing scheme that maintains the user-specified quality of data requirement while significantly reducing the overall energy consumption. Specifically, since communication dominates power usage in sensor networks, it exploits end-user temporal coherency tolerances to reduce the amount of information transmitted by individual nodes. We compare our proposed scheme against an existing data aggregation scheme with a local sensor cache. We present experimental results measuring both power savings and also the quality of data for group-by queries. These results show that our method can reduce power consumption by up to 60 percent without any loss in the quality.