An Energy Effective Adaptive Spatial Sampling Algorithm for WSNs

Abstract

The objective of environmental observation with WSNs (wireless sensor networks) is to extract the synoptic structures (spatio-temporal sequence) of the phenomena of ROI (region of interest) in order to make effective predictive and analytical characterizations. Energy limitation is one of the main obstacles to the universal application of WSNs and therefore there are a large mass of researches on energy conservation for WSNs. Among them, adaptive sampling strategy is regarded as a promising method to improve energy efficiency in recent years, therefore, many researches are concerning to different kinds of energy efficient sampling scheme for WSNs. In this paper, we dedicate to investigating how to schedule sensor nodes in the spatial region domain by our adaptive sampling scheme so as to reduce energy consumption of sensor nodes. The key idea of this paper is to schedule sensor nodes to achieve the desired level of accuracy by activating sensor system only when necessary to acquire a new set of samples and then prepare to power it off immediately afterwards. By adaptively sampling the region of interest, fewer sensors are activated at the same time. Moreover, only the necessary communications are remaining with this algorithm, so as to achieve significant energy conservation than before. The algorithm proposed in this literature is named as Adaptive Spatial Sampling (ASS) algorithm in short. The simulation results verified that ASS algorithm can outperform traditional fixed sampling strategy.

Keywords

• WSNs (Wireless Sensor Networks)
• Adaptive Sampling
• Spatial Sampling
• Energy Effective.