Energy Efficient and Devices Priority Aware Computation Offloading to a Mobile Edge Computing Server

Abstract

Mobile edge computing (MEC) provides remote computation capacity at the edge of mobile networks in close proximity to smart mobile devices (SMDs). These devices generally possess limited processing capacity and battery power. Hence, heavy tasks that require a lot of computation and are energy consuming must be offloaded to a MEC server. Actually, it must consider the wireless network state, the number of SMDs requesting the computation offloading, and the available radio resources. In this paper, we consider a multi-mobile users MEC system, where multiple SMDs demand computation offloading to a MEC server, and we take into account the presence of particular subscribers having priority for computation offloading services. The purpose of this paper is to jointly optimize task offloading decisions and the allocation of critical radio resources while maintaining the priority of certain mobile device users and minimizing overall power consumption. Therefore, we have formulated a bi-objective optimization problem which is NP-Hard. Accordingly, with the use of the weighted aggregation approach, we propose and evaluate a heuristic that, in addition to minimizing the overall energy, minimizes the number of penalized SMDs in case where the radio resources are critical. The obtained results in terms of energy and satisfaction of the SMDs are very encouraging.