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Towards user-centric, switching cost-aware fog node selection strategies

机译:向用户以用户为中心,切换成本感知的雾节点选择策略

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In order to address high latency issues that may arise when executing time-critical applications at the cloud side, the novel fog computing paradigm has emerged, thus enabling the execution of such applications within computation nodes present at the edge of the network. While executing such applications, a user may be moving in an area where a high number of heterogeneous fog nodes (FNs) co-exist. This makes the problem of selecting the most appropriate fog node to execute the user's tasks challenging, especially since the set of visible FNs dynamically changes. Therefore, to deal with the uncertain and dynamic nature of such a fog computing environment, we model the FN selection problem using multi-armed bandits. However, standard solutions for the bandit problem are not tailored for scenarios with changing FN availabilities. In addition, since switching from one FN to the other causes a switching cost, such solutions lead to accumulating a high switching cost. Therefore, to address these issues, we first propose a block-based FN selection scheme, where switching among FNs is not allowed during a block of timeslots. We also propose a greedy approach, where FNs having a sufficiently good delay performance are selected in a greedy manner. Simulation results reveal that both approaches significantly improve the FN selection performance. In particular, we found that the block-based selection results in the lowest switching costs, whereas the greedy selection achieves the best overall performance.
机译:为了解决在在云端执行时间关键应用时可能出现的高延迟问题,新颖的雾计算范例已经出现,从而能够在存在于网络边缘存在的计算节点内执行此类应用。在执行此类应用时,用户可以在共存大量异构雾节点(FNS)的区域中移动。这使得选择最合适的雾节点来执行用户的任务挑战,特别是由于该组可见FNS动态地改变。因此,要处理这种雾计算环境的不确定和动态性质,我们使用多武装匪模拟FN选择问题。但是,具有改变FN可用性的情况下,匪盗问题的标准解决方案不适用于方案。另外,由于从一个fn切换到另一个fn导致切换成本,因此这种解决方案导致累积高的开关成本。因此,要解决这些问题,我们首先提出基于块的FN选择方案,其中在一块时隙块期间不允许在FNS之间切换。我们还提出了一种贪婪的方法,其中FN以贪婪的方式选择具有足够良好的延迟性能。仿真结果表明,两种方法都显着提高了FN选择性能。特别是,我们发现基于块的选择导致了最低的开关成本,而贪婪选择实现了最佳的整体性能。

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