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首页> 外文期刊>Concurrency, practice and experience >Comprehensive multi‐objective model to remote sensing data processing task scheduling problem
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Comprehensive multi‐objective model to remote sensing data processing task scheduling problem

机译：遥感数据处理任务调度问题的综合多目标模型

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摘要

Scientific scheduling of limited resource plays an important role in the remote sensing datarnprocessing. The remote sensing data processing task scheduling is characterized as one novelrncomprehensive multi‐objective model. In this proposed model, the remote sensing data processingrntask scheduling problem is divided into task dispensation and task scheduling sub‐problemrnwith hundreds of variables being considered in it. In order to effectively solve this problem, Bayesrnbelief model is applied to generate the initial dispensation plan, and learnable ant colonyrnoptimization is proposed to solve task scheduling sub‐problem. Experimental results suggest thatrnthe proposed comprehensive multi‐objective model and its solving methods are feasible andrnefficient to remote sensing data processing task scheduling, and it also promotes processingrncenters interoperability among heterogeneous and dispersed processing center. The model andrnthe method of this paper can provide a valuable reference for solving other complex schedulingrnproblem.
机译：有限资源的科学调度在遥感数据处理中起着重要作用。遥感数据处理任务调度被描述为一种新颖的多目标模型。在该模型中，遥感数据处理任务调度问题分为任务分配和任务调度子问题，其中考虑了数百个变量。为了有效地解决这一问题，应用贝叶斯信念模型生成初始分配计划，并提出了可学习的蚁群优化算法来解决任务调度的子问题。实验结果表明，所提出的综合多目标模型及其求解方法对于遥感数据处理任务的调度是可行且有效的，并且可以促进异构中心和分散处理中心之间的处理中心互操作性。本文的模型和方法可以为解决其他复杂的调度问题提供有价值的参考。

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  • 来源
    《Concurrency, practice and experience》 |2017年第24期|e4248.1-e4248.11|共11页
  • 作者

    Lining Xing; Wen Li; Minfan He; Xu Tan;

  • 作者单位

    School of Mathematics and Big Data, FoshanUniversity, Foshan 528000, P.R. China College of Engineering, Shanghai PolytechnicUniversity, Shanghai 201209, P.R. China College of Information Systems andManagement, National University of DefenseTechnology, Changsha 410073, P.R. China;

    Business School of Hunan University,Changsha 410082, P. R. China;

    School of Mathematics and Big Data, FoshanUniversity, Foshan 528000, P.R. China;

    School of Software Engineering, ShenzhenInstitute of Information Technology, Shenzhen518172, P.R. China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ant colony optimization; comprehensive model; remote sensing data processing; scheduling problem;

    机译：蚁群优化;综合模型;遥感数据处理;调度问题;

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