Cost-Efficient Resource Provisioning in Cloud Assisted Mobile Edge Computing

Abstract

Mobile edge computing (MEC) is emerging as an effective computing paradigm which alleviates the conflict between computation-intensive mobile applications and resource-constrained mobile devices. In this paper, a Cloud Assisted Mobile Edge computing (CAME) framework is adopted to enhance the adaptability of MEC to time-varying mobile requests. The resource provisioning problem is investigated to provide guaranteed quality of service (QoS) with minimum system cost. By exploiting the piecewise convexity of the problem, the Optimal Resource Provisioning (ORP) algorithm is developed, which determines the computation capacity at mobile edge and dynamically tunes the usage of cloud resources. Extensive simulations demonstrate that the ORP algorithm yields the minimum system cost, compared with the local-first and the cloud-first algorithms. In addition, the ORP algorithm can flexibly adapt to the time-varying mobile requests.