Collaboration Energy Efficiency with Mobile Edge Computing for Data Collection in IoT

Abstract

In this paper, we investigated collaboration energy efficiency with mobile edge computing (MEC) mechanism in internet of things (IoT), which is a challenge issue. In order to prolong the lifetime of IoT, we adopt dynamic clustering methods to improve energy efficiency while guaranteeing energy balance. We deign the sensor selection scheme for collecting data according to Pareto optimality. Concretely, by considering the reality of random deployment and introducing the definition of node density for IoT, we develop a Pareto optimality for sensor nodes selection in terms of energy efficiency. Furthermore, we recruit voluntary mobile devices as mobile edge computing servers to offload the data from selected sensor nodes in the cluster and process them to the estimate the data state. Simulations demonstrate the efficiency for the performance on energy balance in terms of efficiently prolonging the IoT lifetime.