Ad-hoc移动云环境下采取随机规划和买卖博弈的任务卸载方法  

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

作　　者：张龙[1] 曹傧[1] ZHANG Long;CAO Bin(Chongqing Key Laboratory of Mobile Communications Technology, Chongqing University of Post and Communications, Chongqing 400065, Chin)

机构地区：[1]重庆邮电大学移动通信技术重庆市重点实验室,重庆400065

出　　处：《电子与信息学报》2018年第7期1731-1737,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61701059);重庆市教委科学技术研究项目(KJ1500406;KJ1500408);重庆邮电大学博士启动基金(A2014-92);重庆市研究生科研创新项目(CYS17218)~~

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。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.

关 键 词：移动云 任务卸载 随机规划 博弈论 

分 类 号：TN92[电子电信—通信与信息系统]