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Ready-time partitioning algorithm for computation offloading of workflow applications in mobile cloud computing

机译:移动云计算中工作流应用的计算卸载的现代分区算法

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To augment the capabilities of mobile devices, application partitioning solutions in mobile cloud computing have emerged to decide the execution location of each application part between mobile device and cloud servers. To adapt to the network and server status changes during application execution, we propose a cloudlet-assisted ready-time partitioning technique, which partitions each task of the users' workflow exactly when it is ready to run. It aims at minimizing the energy consumption of each mobile user's device, while meeting user-defined deadlines. The proposed deadline distribution-ready-time partitioning algorithm has two phases: deadline distribution phase, which distributes each user deadline among its workflow tasks before application execution, and ready-time partitioning phase, which partitions each ready task by effectively considering the network and cloudlet status. Using real mobile applications, the experimental results prove its adaptability to environmental changes, its energy-efficiency, and its ability to satisfy the deadline over other methods.
机译:为了增加移动设备的功能,移动云计算中的应用分区解决方案已经出现以确定移动设备和云服务器之间的每个应用部分的执行位置。为了适应网络和服务器状态在应用程序执行期间更改,我们提出了一种Cloudlet辅助的现成时间分区技术,该方法将用户的工作流程的每个任务分区准备运行。它旨在最大限度地减少每个移动用户设备的能耗,同时满足用户定义的截止日期。所提出的截止日期分发 - 即时分区算法有两个阶段:截止日期分布阶段,它在应用程序执行之前分配其工作流任务的每个用户截止日期,以及通过有效地考虑网络和Cloudlet来分区每个就绪任务的时间分区阶段地位。使用真实的移动应用,实验结果证明其对环境变化的适应性,其能效,能力,以及其满足其他方法的截止日期。

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