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Energy-aware task assignment for mobile cyber-enabled applications in heterogeneous cloud computing

机译:异构云计算中支持移动网络的应用程序的能源感知任务分配

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Recent remarkable growth of mobile computing has led to an exceptional hardware upgrade, including the adoption of the multiple core processors. Along with this trend, energy consumptions are becoming greater when the computation capacity or workload grows. As one of the solutions, using cloud computing can mitigate energy costs due to the centralized computation. However, simply offloading the workloads to the remote side cannot efficiently reduce the energy consumptions when the energy costs caused by wireless communications are greater than that of on mobile devices. In this paper, we focus on the energy-saving problem and consider the energy wastes when tasks are assigned to remote cloud servers or heterogeneous core processors. Our solution aims to reduce the total energy cost of the mobile heterogeneous embedded systems by a novel task assignment to heterogeneous cores and mobile clouds. The proposed model is called Energy-Aware Heterogeneous Cloud Management (EA-HCM) model and the main algorithm is Heterogeneous Task Assignment Algorithm (HTA2). Our experimental evaluations have proved that our approach is effective to save energy when deploying heterogeneous embedded systems in mobile cloud systems.
机译:最近移动计算的显着增长导致了卓越的硬件升级,包括采用了多核处理器。随着这种趋势,随着计算能力或工作量的增长,能耗也越来越大。作为解决方案之一,使用云计算可以减轻由于集中计算而产生的能源成本。但是,当无线通信引起的能源成本大于移动设备上的能源成本时,仅将工作负载卸载到远程端并不能有效地减少能源消耗。在本文中,我们关注节能问题,并考虑将任​​务分配给远程云服务器或异构核心处理器时的能源浪费。我们的解决方案旨在通过将新颖的任务分配给异构核心和移动云来降低移动异构嵌入式系统的总能源成本。提出的模型称为能量感知异构云管理(EA-HCM)模型,主要算法为异构任务分配算法(HTA2)。我们的实验评估证明,当在移动云系统中部署异构嵌入式系统时,我们的方法可有效节省能源。

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