A Computation Task Offloading Scheme based on Mobile-Cloud and Edge Computing for WBANs

Abstract

The rapid development of Wireless Body Area Networks (WBANs) has brought revolutionary changes to the healthcare system. However, due to the shortcomings of the sink node with limited energy resource and computing capability, it is difficult to handle all computation tasks effectively and timely. The emergence of Mobile Cloud Computing (MCC) and Mobile Edge Computing (MEC) may provide a potential and efficient solution. Therefore, we devote this paper to developing a computation task offloading scheme based on MCC and MEC for WBANs. Technically, we first propose a three-tier system model with one Remote Cloud Server (RCS), several Mobile Edge Servers (MESs) and multiple WBAN users. Then, an optimization problem with the objective to minimize the total cost in terms of the energy consumption and the delay is formulated. In order to solve the problem, we next investigate a Computation Task Offloading Scheme based on Differential Evolution algorithm, called CTOS-DE. The simulation results demonstrate that our proposed CTOS-DE scheme can provide a best computation task offloading decision in terms of the total cost and load balancing.