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In mobile edge computing systems, mobile devices can offloadcompute-intensive tasks to a nearby cloudlet,so as to save energy and extendbattery life. Unlike a fully-fledged cloud, a cloudlet is a small-scaledatacenter deployed at a wireless access point, and thus is highly constrainedby both radio and compute resources. We show in this paper that separatelyoptimizing the allocation of either compute or radio resource, as most existingworks did, is highly suboptimal: the congestion of compute resource leads tothe waste of radio resource, and vice versa. To address this problem, wepropose a joint scheduling algorithm that allocates both radio and computeresources coordinately. Specifically, we consider a cloudlet in an OrthogonalFrequency-Division Multiplexing Access (OFDMA) system with multiple mobiledevices, where we study subcarrier allocation for task offloading and CPU timeallocation for task execution in the cloudlet. Simulation results show that theproposed algorithm significantly outperforms per-resource optimization,accommodating more offloading requests while achieving salient energy saving.

Joint Subcarrier and CPU Time Allocation for Mobile Edge Computing