An Application-Specific Forecasting Algorithm for Extending WSN Lifetime2013 IEEE International Conference on Distributed Computing in Sensor Systems

Data reduction strategy is one of the schemesemployed to extend network lifetime. In this paper we present an implementation of a light-weight forecasting algorithm for sensed data which saves packet transmission in the network. The proposed Naive algorithm achieves high energy savings with a limited computational overhead on a node. Simulation results from realistic Building monitoring application of WSN are compared with well-known prediction algorithms such as ARIMA, LMS and WMA models. We implemented a real-world deployment using 32bit mote-class device. Overall, up to 96%transmission reduction is achieved using our Naive method, while still able to maintain a considerable level of accuracy at 0.5 degrees error bound and it is comparable in performance to the more complex models such as ARIMA, LMS and WMA.