Stochastic Programming and Buyer-seller Game Methods for Workload Distribution in an Ad-hoc Mobile Cloud

In order to solve the limitation of processing capacity and energy of single mobile equipment, the conception of Ad-hoc mobile cloud is proposed recently, in which a mobile device can use the idle resources at other neighboring devices for processing data and storage in Ad-hoc manner. To this end, this paper designs a workload distribution for offloading among mobile equipment. Considering the random and intermittent connections between mobile equipment caused by the movement in wireless network, a stochastic programming method is adopted to take posterior recourse actions to compensate for inaccurate predictions. Moreover, in order to motivate the available mobile equipment for offloading while maximizing their utilities, a distributed multi-stage Stochastic buyer/seller Game for Workload Distribution (SGWD) is formulated. Numerical results show the effectiveness of SGWD compared with the benchmark method in terms of communication cost, the delay, energy consumption and the payoff.