ARM: An Accelerator for Resource Allocation in Mobile Edge Computing

Mobile edge computing (MEC) is an emerging paradigm which has drawn much attention from the academy and industry. Leveraging 5G technique, MEC provisions the ability to support the latency-sensitive and compute-intensive services by deploying computing and storage capacity at the network edge. As one of the critical problems in MEC, resource allocation problem needs to be solved within a very short time to satisfy the low latency requirement of services. In this paper, we propose an Accelerator for Resource allocation in MEC (ARM), which can directly solve the resource allocation problem based on deep neural network. With the aid of our scale-free representation scheme and feasible guarantee algorithm, ARM can solve the problem in milliseconds. Meanwhile, our algorithm achieves near 2-factor approximation to the optimal solution.