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Energy efficiency is a crucial performance metric in sensor networks,directly determining the network lifetime. Consequently, a key factor in WSN isto improve overall energy efficiency to extend the network lifetime. Althoughmany algorithms have been presented to optimize the energy factor, energyefficiency is still one of the major problems of WSNs, especially when there isa need to sample an area with different types of loads. Unlike otherenergy-efficient schemes for hierarchical sampling, our hypothesis is that itis achievable, in terms of prolonging the network lifetime, to adaptivelyre-modify CHs sensing rates (the processing and transmitting stages inparticular) in some specific regions that are triggered significantly less thanother regions. In order to do so we introduce the Adaptive DistributedHierarchical Sensing (ADHS) algorithm. This algorithm employs a homogenoussensor network in a distributed fashion and changes the sampling rates of theCHs based on the variance of the sampled data without damaging significantlythe accuracy of the sensed area.

Adaptive Distributed Hierarchical Sensing Algorithm for Reduction of Wireless Sensor Network Cluster-Heads Energy Consumption