Stochastic Programming and Buyer-seller Game Methods for Workload Distribution in an Ad-hoc Mobile Cloud
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摘要:
由于移动设备处理能力和能量的限制，近年来提出了一种新型移动云环境，通过Ad-hoc方式共享邻近设备的闲置资源完成数据处理、存储等需求。在此背景下，该文提出一个在源设备与邻近设备之间的任务卸载方案。考虑无线网络环境下移动设备的移动性导致连接时间随机性问题，采用随机规划方法补偿连接时间预测不精确对任务卸载带来的不利影响。同时，为了激励移动设备相互协作、最大化各自收益，提出基于买卖博弈的分布式多阶段随机买卖博弈任务卸载(SGWD)算法。仿真结果表明该算法在通信成本，时间延迟，能量消耗和收益性能上取得了有效提升。
Abstract: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.
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