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