Abstract
With the development of autonomous driving, the demand of downloading large files experiences the explosive growth. However, the limited capacity of local computing leads to a high-latency and inefficient resource scheduling for large-scale file request. The cloud platform has powerful computing capacity and storage resources, which has been proved to be suitable for processing this kind of scheduling. In this paper, we investigate the issue of resource scheduling mechanism using cloud computing. We first establish system reward model with dynamic greedy algorithm in Device-to-Device (D2D) scenario. Based on the model, we propose a Maximum Reward System based on Priority Resource Scheduling (MRPRS), which integrates the priority of request demand, request data volume and user tolerance factors. In the end, the simulation result reveals the effectiveness of the mechanism and we can get the best scheduling policy for the resource allocation of virtual machine.
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