基于截止日期调度算法的雾环境性能改进

Amal El-Nattat, Sahar Elkazzaz, Nirmeen A. El-Bahnasawy, A. El-Sayed
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引用次数: 1

摘要

雾计算(FC)是一种提供更接近用户的云服务的计算范式。近年来,由于数据请求和FC的大量增长,使得数据的可访问性和自适应性不断增强。在FC中必须考虑负载平衡(LB)和任务调度等许多挑战。负载均衡是实现高资源利用率和缩短响应时间的一个重要问题。为了在雾环境下实现高效的负载均衡,已经提出了许多算法。本文提出了一种新的任务调度算法——增强平均最大时间(EAM)算法。EAM的目的是在用户定义的截止日期约束下,通过提高平均最大完工时间参数来提高雾系统的性能。将其性能与最有效的负载平衡算法之一如改进轮询(MRR)算法进行了比较,结果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Improvement of Fog Environment Using Deadline Based Scheduling Algorithm
Fog computing (FC) is a computing paradigm that provides cloud services closer to the user. Recently, there is a great growth of data requests and FC which lead to enhance data accessibility and adaptability. Many challenges must be considered in FC like load balancing (LB) and task scheduling. LB is an important issue to achieve high resource utilization and reduce response time. A lot of algorithms have been proposed to achieve efficient load balancing in fog environment. In this paper, a new task scheduling algorithm called enhanced average makespan (EAM) algorithm has been proposed. EAM aims to improve the performance of fog system by improving average makespan parameter under the user’s defined deadline constraint. Its performance was compared with one of the most efficient load balancing algorithms like Modified Round Robin (MRR) algorithm and it provided better results.
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