The cloud radio access network (Cloud-RAN) based mobile cloud computing (MCC) system offers a promising solution to offload computation-intensive tasks from battery and computation capability limited mobile devices to a cloud service provider via wireless transmission, thereby reducing the energy consumption and latency for mobile devices. However, the extra energy and latency caused by wireless transmission for offloading may offset the gains of computation offloading. In this paper, we focus on minimizing the network energy consumption while satisfying the delay requirements by jointly optimizing the communication resources (i.e., uplink and downlink beamforming design), computation resources (i.e., computation capability) and offloading decision (i.e., offload or not offload). Unfortunately, this problem turns out to be an NP-hard non-convex mixed integer non-linear programming (MINLP) problem. To resolve this challenge, the principle of uplink and downlink duality is exploited to aid efficient beamforming design. Furthermore, an effective iterative algorithm with polynomial time complexity is proposed in a holistic way to guide the offloading decision. Simulation results will demonstrate that the proposed iterative algorithm achieves near-optimal energy efficiency in Cloud-RAN based mobile cloud computing system.
['Jinkun Cheng', 'Yuanming Shi', 'Bo Bai', 'Wei Chen']
Computation offloading in cloud-RAN based mobile cloud computing system