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The comparative estimation of workload relocation approaches in the fog- and edge- computing environments

机译:雾和边缘计算环境中工作负载重定位方法的比较估计

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In the current paper the issues of the workload relocation in the fog- and edgecomputing environments are in-question. The workload relocation problem is closely connected to the scheduling problems, yet, outside the cloud there is almost unlimited number of nodes to place the computational tasks. So the search space for the optimization problem grows, and the time of the workload relocation degrades. We emphasize the techniques to limit the set of candidate nodes for the tasks distribution. In the paper two approaches are proposed and considered in terms of time consumption. The simple models are developed with the following simulation. Also the distributed-ledger-based modifications of the techniques are proposed and examined.
机译:在本文中,雾和EDGecomputing环境中的工作负载重定位问题是内部的。 工作负载重定位问题与调度问题紧密相连,但在云之外存在几乎无限数量的节点来放置计算任务。 因此,优化问题的搜索空间增长,并且工作负载重定位的时间降低。 我们强调了限制任务分发的候选节点集的技术。 本文在时间消耗方面提出了两种方法。 简单的模型是通过以下模拟开发的。 还提出和检查了该技术的分布式基因仪的修改。

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