Energy Map Construction using Adaptive Alpha Grey Prediction Model in WSNs

Wireless Sensor Networks can be used to monitor the physical phenomenon in such areas where human appro ach is nearly impossible. Hence the limited power supply is the m ajor constraint of the WSNs due to the use of non-rechargeable batteri es in sensor nodes. A lot of researches are going on to reduce t he energy consumption of sensor nodes. Energy map can be used with clustering, data dissemination and routing techniqu es to reduce the power consumption of WSNs. Energy map can also be u sed to know which part of the network is going to fail in near future. In this paper, Energy map is constructed using the prediction base d approach. Adaptive alpha GM(1,1) model is used as the predict ion model. GM(1,1) is being used worldwide in many application s for predicting future values of time series using some past values due to its high computational efficiency and accuracy. Keywords—Adaptive Alpha GM(1,1) Model, Energy Map, Prediction Based Data Reduction, Wireless Sensor Ne tworks