An Energy Effective Adaptive Spatial Sampling Algorithm for Wireless Sensor Networks

The objective of environmental observation with wireless sensor networks is to extract the synoptic structures (spatio-temporal sequence) of the phenomena of region of interest (ROI) in order to make effective predictive and analytical characterizations. Energy limitation is one of the main obstacles to the universal application of wireless sensor networks. Certainly, there are many researches concerned to energy efficient scheme in wireless sensor networks. In this paper, we dedicate to investigating how to schedule sensor nodes in spatial region by adaptive sampling so as to reduce energy consumption. Adaptive sampling strategy is regarded as a promising method for improving energy efficiency in recent years. The key idea of this paper is to schedule sensor nodes to achieve the desired level of accuracy by activating sensor system only for the time needed to acquire a new set of samples and then powering it off immediately afterwards. By adaptively sampling the region of interest (ROI), fewer sensors are activated at the same time. Moreover, the required communications are reduced, so as to achieve significant energy conservation. The algorithm proposed in this literature is named as Adaptive Spatial Sampling (ASS) algorithm.