Using the Cuckoo Algorithm to Optimizing the Response Time and Energy Consumption Cost of Fog Nodes by Considering Collaboration in the Fog Layer

Shakoor Vakilian, Seyed Vahid Moravvej, A. Fanian
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引用次数: 22

Abstract

With the growth of the Internet of Things (IoT) technology, Fog computing has moved the processing capability of generated data near IoT devices and objects. Therefore, fog nodes able to reduce the response time to high volumes of generated data. As fog nodes extend from the edge of the network to the cloud, their cooperation in workload processing can lighten processing queues and further reduce response time. On the other hand, by increasing processing data in fog nodes, the fog layer’s energy consumption cost is increased. Therefore, to investigate this issue, in this paper, an optimization problem for collaboration between fog nodes is presented to reduce the response time and energy consumption cost. In this work, the goal is to make a balance between these two parameters. Then, the proposed problem is solved using the Cuckoo evolutionary algorithm. The evaluation results show that the proposed solution in solving the problem has been able to have significant impacts in reducing response time and energy consumption cost compared to competing works.
考虑雾层协同的布谷鸟算法优化雾节点的响应时间和能耗成本
随着物联网(IoT)技术的发展,雾计算将生成数据的处理能力转移到物联网设备和对象附近。因此,雾节点能够减少对大量生成数据的响应时间。随着雾节点从网络边缘延伸到云端,它们在工作负载处理方面的合作可以减轻处理队列,进一步缩短响应时间。另一方面,通过增加雾节点上的处理数据,增加了雾层的能耗成本。因此,为了研究这一问题,本文提出了一个雾节点间协作的优化问题,以减少响应时间和能耗成本。在这项工作中,目标是在这两个参数之间取得平衡。然后,利用布谷鸟进化算法求解该问题。评价结果表明,与竞争方案相比,所提出的解决方案在减少响应时间和能耗成本方面具有显著的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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