Abstract: Wireless Sensor Networks can be used to monitor the
physical phenomenon in such areas where human approach is nearly
impossible. Hence the limited power supply is the major constraint of
the WSNs due to the use of non-rechargeable batteries in sensor
nodes. A lot of researches are going on to reduce the energy
consumption of sensor nodes. Energy map can be used with
clustering, data dissemination and routing techniques to reduce the
power consumption of WSNs. Energy map can also be used to know
which part of the network is going to fail in near future. In this paper,
Energy map is constructed using the prediction based approach.
Adaptive alpha GM(1,1) model is used as the prediction model.
GM(1,1) is being used worldwide in many applications for predicting
future values of time series using some past values due to its high
computational efficiency and accuracy.