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A Cuckoo-based Workflow Scheduling Algorithm to Reduce Cost and Increase Load Balance in the Cloud Environment

机译:基于CUCKOO的工作流程调度算法,以降低成本并增加云环境中的负载平衡

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摘要

Workflow scheduling is one of the important issues in implementing workflows in the cloud environment. Workflow scheduling means how to allocate workflow resources to tasks based on requirements and features of the tasks. The problem of workflow scheduling in cloud computing is a very important issue and is an NP problem. The relevant scheduling algorithms try to find optimal scheduling of tasks on the available processing resources in such a way some qualitative criteria when executing the entire workflow are satisfied. In this paper, we proposed a new scheduling algorithm for workflows in the cloud environment using Cuckoo Optimization Algorithm (COA). The aims of the proposed algorithm are reducing the processing and transmission costs as well as maintaining a desirable load balance among the processing resources. The proposed algorithm is implemented in MATLAB and its performance is compared with Cat Swarm Optimization (CSO). The results of the comparisons showed that the proposed algorithm is superior to CSO in discovering optimal solutions.
机译:工作流程调度是在云环境中实现工作流程的重要问题之一。工作流程调度意味着如何根据任务的要求和功能将工作流程资源分配给任务。云计算中的工作流程调度问题是一个非常重要的问题,是一个NP问题。相关的调度算法尝试在满足时,在某种方式中找到可用处理资源上的任务的最佳调度,这是满足整个工作流的一些定性标准。在本文中,我们提出了一种使用Cuckoo优化算法(COA)在云环境中的工作流程的新调度算法。所提出的算法的目的是降低处理和传输成本,以及在处理资源之间保持所需的负载平衡。该算法在MATLAB中实现,其性能与CAT群优化(CSO)进行了比较。比较结果表明,在发现最佳解决方案时,所提出的算法优于CSO。

著录项

  • 作者

    Shahin Ghasemi; Ali Hanani;

  • 作者单位
  • 年度 2019
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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