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Heuristic offloading of concurrent tasks for computation-intensive applications in mobile cloud computing

机译:移动云计算中计算密集型应用程序的并发任务的启发式卸载

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Mobile applications are becoming increasingly computation-intensive, while the computing capacity of mobile devices is limited. A powerful way to reduce completion time of an application is to offload tasks to the cloud for execution. However, online offloading an application with general taskgraph is a difficult task. In this paper we present an online task offloading algorithm that minimizes the completion time of the application on the mobile device. We take cloud service time into account when making an offloading decision and we consider general taskgraphs for offloading. In our algorithm, for sequential tasks (i.e., line topology taskgraphs) we find the optimal offloading of tasks to the cloud. For concurrent tasks (i.e., general topology taskgraphs) we use a load-balancing heuristic to offload tasks to the cloud, such that the parallelism between the mobile and the cloud is maximized. Simulation results show that our algorithm has a performance of at least 85% of the optimal solution, and is significantly better than other existing algorithms.
机译:移动应用程序变得越来越计算密集,而移动设备的计算能力却受到限制。减少应用程序完成时间的一种有效方法是将任务卸载到云中以执行。但是,使用常规任务图在线卸载应用程序是一项艰巨的任务。在本文中,我们提出了一种在线任务卸载算法,该算法可最大程度地减少移动设备上应用程序的完成时间。在做出卸载决策时,我们会考虑云服务时间,并考虑用于卸载的一般任务图。在我们的算法中,对于顺序任务(即线拓扑任务图),我们找到了将任务最佳地卸载到云中的方法。对于并发任务(即一般拓扑任务图),我们使用负载平衡启发式方法将任务卸载到云中,从而最大程度地提高了移动设备和云之间的并行度。仿真结果表明,该算法的性能至少为最优解的85%,明显优于其他现有算法。

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