With the growing popularity of mobile applications, mobile cloud computing has been envisioned as a promising approach to help mobile devices enhance computation capability and reduce energy consumptions. In this paper, we investigate the problem of multi-user computation offloading for mobile cloud computing under dynamic environment, wherein mobile users may become active or inactive (i.e., silent) dynamically, and the wireless channels for users to offload computation vary randomly. Taking into account the mutual interference among different users when offloading computation to mobile could via wireless channels, we formulate the mobile users' offloading decision process as a stochastic game. We further prove that the formulated stochastic game is equivalent to a potential game which has at least one Nash Equilibrium (NE). At the NE, no single user will unilaterally change its computation offloading strategy. Furthermore, we propose a multi-agent stochastic learning algorithm to reach the NE with guaranteed convergence. Finally, we conduct simulations to validate the effectiveness of the proposed algorithm and evaluate its performance under dynamic environment.
Jianchao ZhengYueming CaiYuan WuXuemin Shen
Valeria CardelliniVittoria de Nitto PersonéValerio Di ValerioFrancisco FacchineiVincenzo GrassiFrancesco Lo PrestiVeronica Piccialli
An QinChengcheng CaiQin WangYiyang NiHongbo Zhu