Energy minimization in WSNs: Empirical study of multicast incremental power algorithm

Abstract

This paper studied the existing multicast incremental power algorithm (MIP) and proposes a new approach considering the data envelopment analysis (DEA) methodology to further reduce the multicast energy in wireless sensor networks (WSNs). In order to achieve this mission, an empirical model based on input-orientation with Banker, Chanes and Cooper (BCC) approach is developed. This research has shown how to evaluate efficiency ratings of WSNs and identify the inefficient WSNs with their magnitude at which they deviate from the best practice frontier. Furthermore, the results show how the inefficient WSNs can reduce their input energy so that they also become efficient. Thus our model is able to further reduce the multicast energy by 5% over MIP method if all the WSNs sampled were operating efficiently.