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A Dynamic Application-Partitioning Algorithm with Improved Offloading Mechanism for Fog Cloud Networks

机译:具有改进的卸载机制的雾云网络动态应用分区算法

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This paper aims to propose a new fog cloud architecture that performs a joint energy-efficient task assignment (JEETA). The proposed JEETA architecture utilizes the dynamic application-partitioning algorithm (DAPTS), a novel algorithm that efficiently decides and switches the task to be offloaded or not in heterogeneous environments with minimal energy consumption. The proposed scheme outperforms baseline approaches such as MAUI, Think Air and Clone Cloud in many performance aspects. Results show that for the execution of 1000 Tasks on fog, mobile offloaded nodes, JEETA consumes the leas, i.e., 23% of the total energy whereas other baseline approaches consume in between 50–100% of the total energy. Results are validated via real test-bed experiments and trice are driven efficient simulations.
机译:本文旨在提出一种新的雾云架构,该架构执行联合节能任务分配(JEETA)。提出的JEETA体系结构利用了动态应用程序分区算法(DAPTS),这是一种新颖的算法,可以在能耗最小的情况下有效地决定和切换要在异构环境中卸载或不卸载的任务。所提出的方案在许多性能方面都优于诸如MAUI,Think Air和Clone Cloud之类的基准方法。结果表明,对于在雾霾,移动卸载节点上执行1000个任务,JEETA消耗了lea,即占总能量的23%,而其他基准方法消耗了总能量的50-100%。通过真实的试验台实验验证了结果,并通过有效的仿真进行了三次。

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