Abstract-In mobile edge computing systems, mobile devices can offload compute-intensive tasks to a nearby cloudlet, so as to save energy and extend battery life. Unlike a fully-fledged cloud, a cloudlet is a small-scale datacenter deployed at a wireless access point, and thus is highly constrained by both radio and compute resources. We show in this paper that separately optimizing the allocation of either compute or radio resource -as most existing works did -is highly suboptimal: the congestion of compute resource leads to the waste of radio resource, and vice versa. To address this problem, we propose a joint scheduling algorithm that allocates both radio and compute resources coordinately. Specifically, we consider a cloudlet in an Orthogonal FrequencyDivision Multiplexing Access (OFDMA) system with multiple mobile devices, where we study subcarrier allocation for task offloading and CPU time allocation for task execution in the cloudlet. Simulation results show that the proposed algorithm significantly outperforms per-resource optimization, accommodating more offloading requests while achieving salient energy saving.
Yu et al. REF jointly selected the offloading SMDs and allocated subcharriers in an Orthogonal Frequency-Division Multiplexing Access (OFDMA) system and CPU time in the MEC server, to minimize the energy consumption on SMDs.
Joint Subcarrier and CPU Time Allocation for Mobile Edge Computing
2016 IEEE Global Communications Conference (GLOBECOM)
2016 IEEE Global Communications Conference (GLOBECOM)
Computer Science Mathematics