Tasks scheduling and resource allocation in heterogeneous cloud for delay-bounded mobile edge computing

摘要

Mobile edge computing is a novel technique in which mobile devices offload computation-intensive tasks with stringent delay requirements to the edge cloud. However, the limited computational resource in the edge cloud may result in the Quality of Service degradation. In this paper, we address this issue by coordinating the heterogeneous cloud which includes the edge cloud and the remote cloud. Considering the offloading of delay-bounded tasks, we study into the scheduling of heterogeneous cloud in order to maximize the probability that tasks can have the delay requirements met. The problem formulation is proved to be concave, and an optimal algorithm is proposed accordingly. The optimal policy with heterogeneous cloud is notably different from the policy merely using the edge cloud. With only the edge cloud, the system serves tasks with loose delay bounds and drops tasks with stringent delay bounds when the traffic load is heavy. However, with the heterogeneous cloud, tasks with stringent delay bounds are offloaded to the edge cloud and tasks with loose delay bounds are offloaded to the remote cloud. In numerical results, the probability that the delay bounds of tasks are satisfied can be improved by about 40% with the assistance of the remote cloud.