An Ant-colony Based Model for Load Balancing in Fog Environments

Q2 Computer Science

Supercomputing Frontiers and Innovations Pub Date : 2023-03-01 DOI:10.14529/jsfi230101

S. L. Mirtaheri, Mahya Azari, Sergio Greco, Ehsan Arianian

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引用次数: 0

Abstract

c (cid:13) The Authors 2023. This paper is published with open access at SuperFri.org Delay-sensitive applications are becoming more and more in demand as a result of the development of information systems and the expansion of communication in cloud computing technologies. Some of these requests will be overlooked in cloud environments due to the communication delay between the processing center and the client’s request. The ‘fog-based computing paradigm’, a novel processing model, can be added to cloud computing to help with the aforementioned issues. The performance of computing systems is always inﬂuenced by latency. In this paper, we focus on balancing the load on the fog nodes to lower the latency. It is also a crucial component of fog computing devices. It necessitates the use of load-balancing algorithms to select the optimal hosts, resulting in an even distribution of the load on the available resources. We provide a load-balancing approach based on the Ant-colony optimization algorithm’s latency rate for responding to tasks. A random data set evaluation of this model reveals shorter response times than those of earlier strategies suggested in this ﬁeld.

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雾环境下基于蚁群的负载均衡模型

c (cid:13)作者2023。由于信息系统的发展和云计算技术中通信的扩展，对延迟敏感应用的需求越来越大。由于处理中心和客户端请求之间的通信延迟，其中一些请求在云环境中会被忽略。“基于雾的计算范式”是一种新的处理模型，可以添加到云计算中，以帮助解决上述问题。计算系统的性能总是受到延迟的影响。在本文中，我们着重于平衡雾节点上的负载以降低延迟。它也是雾计算设备的关键组成部分。它需要使用负载平衡算法来选择最优主机，从而在可用资源上均匀分配负载。我们提供了一种基于蚁群优化算法延迟率的负载平衡方法来响应任务。对该模型的随机数据集评估表明，该模型的响应时间比该领域先前提出的策略要短。

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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来源期刊

Supercomputing Frontiers and Innovations Computer Science-Computational Theory and Mathematics

CiteScore

1.60

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： The Journal of Supercomputing Frontiers and Innovations (JSFI) is a new peer reviewed publication that addresses the urgent need for greater dissemination of research and development findings and results at the leading edge of high performance computing systems, highly parallel methods, and extreme scaled applications. Key topic areas germane include, but not limited to: Enabling technologies for high performance computing Future generation supercomputer architectures Extreme-scale concepts beyond conventional practices including exascale Parallel programming models, interfaces, languages, libraries, and tools Supercomputer applications and algorithms Distributed operating systems, kernels, supervisors, and virtualization for highly scalable computing Scalable runtime systems software Methods and means of supercomputer system management, administration, and monitoring Mass storage systems, protocols, and allocation Energy and power minimization for very large deployed computers Resilience, reliability, and fault tolerance for future generation highly parallel computing systems Parallel performance and correctness debugging Scientific visualization for massive data and computing both external and in situ Education in high performance computing and computational science.