Joint cloud and radio resource management for video transmissions in mobile cloud computing networks

Abstract

In mobile cloud computing (MCC) systems, the resource in both the cloud and the mobile network should be carefully managed. Cloud resource management and radio resource management have traditionally been addressed separately in previous works. In this paper, we propose to jointly study dynamic cloud and radio resource management so as to improve end-to-end performance of adaptive video transmissions in MCC systems. Video application quality of service performance, distortion, is adopted as the performance measure. An important video application layer parameter, intra-refreshing rate, is optimized to improve the video distortion performance. We formulate the problem as a stochastic restless bandits optimization problem, which facilitates the distributed MCC architecture and simplifies the computation and implementation due to its “indexibility” property. Simulation results are presented to show the effectivenes of the proposed scheme.