Abstract
As one of the key concepts in the 5G network, MEC can support the latency-sensitive and compute-intensive services by widely deploying computing and storage capacity to the base stations at the network edge. Because these services are sensitive to latency, the joint optimization problem of task offloading and resource allocation needs to be solved in a short time. In this paper, we propose a Fast AI-assistant Solution for Task Offloading and Resource Allocation in MEC (FAST-RAM), which can directly solve the joint optimization problem leveraging a deep neural network. FAST-RAM can produce the offloading policy and resource allocation scheme in milliseconds. Meantime, our solution has near-optimal performance and sufficient feasibility under different network environments.
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