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An energy-efficient task scheduling for mobile devices based on cloud assistant

机译:基于云助手的移动设备节能任务调度

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Mobile cloud computing is an emerging service model to extend the capability and the battery life of mobile devices. Mostly one network application can be decomposed into fine-grained tasks which consist of sequential tasks and parallel tasks. With the assistance of mobile cloud computing, some tasks could be offloaded to the cloud for speeding up executions and saving energy. However, the task offloading results in some additional cost during the communication between cloud and mobile devices. Therefore, this paper proposes an energy-efficient scheduling of tasks, in which the mobile device offloads appropriate tasks to the cloud via a Wi-Fi access point. The scheduling aims to minimize the energy consumption of mobile device for one application under the constraint of total completion time. This task scheduling problem is reconstructed into a constrained shortest path problem and the LARAC method is applied to get the approximate optimal solution. The proposed energy-efficient strategy decreases 81.93% of energy consumption and 25.70% of time at most, compared with the local strategy. Moreover, the applicability and performance of the proposed strategy are verified in different patterns of applications, where the time constraint, the workload ratio between communication and computation are various.
机译:移动云计算是一种新兴的服务模型,可以扩展移动设备的功能和电池寿命。大多数情况下,一个网络应用程序可以分解为细粒度的任务,其中包括顺序任务和并行任务。借助移动云计算,可以将某些任务转移到云中,以加快执行速度并节省能源。但是,任务卸载会导致云与移动设备之间的通信过程中产生一些额外的成本。因此,本文提出了一种节能的任务调度,其中移动设备通过Wi-Fi接入点将适当的任务卸载到云中。该调度旨在在总完成时间的约束下将一种应用的移动设备的能耗降至最低。将该任务调度问题重构为约束最短路径问题,并使用LARAC方法获得近似最优解。与本地策略相比,拟议的节能策略最多可减少81.93%的能耗和25.70%的时间。此外,在时间约束,通信与计算之间的工作量比各不相同的不同应用模式下,验证了所提出策略的适用性和性能。

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