An energy-aware spatial correlation mechanism to perform efficient data collection in WSNs

Dense sensor networks are typically deployed for fine-grain monitoring in a wide range of applications. Due to this high density of nodes, it is very likely that both spatially correlated information and redundant data be detected by several nearby nodes, which can be exploited to save energy by these nodes that are sensing an event. In this work, we propose an Energy-Aware Spatial Correlation mechanism (ESC) based on correlation regions to perform efficient data collection. The sensed information of a region is forwarded to the sink by only one node inside that region. Also, the area of a correlation region can be changed dynamically by the sink node to achieve the required accuracy of the sensed information. Simulation results show that using ESC, an event can be sensed with 97% of accuracy, and 75% of the nodes' residual energy can be saved within the phenomena area when compared with the classical approach for data collection.