Efficient Model for Minimizing Energy in Wireless Sensor Network for Internet of Things

Abstract

Background & Objective: The main aim of this paper is to development of efficient model of minimize the energy for wireless sensor networks. In this paper we have proposed the dual probability based energy estimation model in wireless sensor network. Methods: We proposed dual probability based function measure the expected value of energy for the transmission of data. This function creates subgroup of networks based on energy function and will change the operation of energy management in scenario of sensor node data processing. This function also integrates the cloud based services with sensor network. The benefit of this function is that it increases the throughput of network and quality of service. Results: The proposed model is simulated in MATLAB R-2014a environment and the results are obtained using different scenario of network density. Finally, we analyze the performance of our proposed work with respect to following metrics: Data Utility, Energy Consumptions, and Data Reconstruction Error. Conclusion: The dual probability based function reduces the level value of sensors node grouping of data according to their design model. So the overall performance of proposed model is better instead of CP model.