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Multiple Criteria Decision Analysis in Autonomous Computing: A Study on Independent and Coordinated Self-Management.

机译:自主计算中的多准则决策分析:独立和协调的自我管理研究。

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摘要

In this dissertation, we focus on the problem of self-management in distributed systems. In this context, we propose a new methodology for reactive self-management based on multiple criteria decision analysis (MCDA). The general structure of the proposed methodology is extracted from the commonalities of the former well-established approaches that are applied in other problem domains. The main novelty of this work, however, lies in the usage of MCDA during the reaction processes in the context of the two problems that the proposed methodology is applied to.;In order to provide a detailed analysis and assessment of this new approach, we have used the proposed methodology to design distributed autonomous agents that can provide self-management in two outstanding problems. These two problems also represent the two distinct ways in which the methodology can be applied to self-management problems. These two cases are: 1) independent self management, and 2) coordinated self-management. In the simulation case study regarding independent self-management, the methodology is used to design and implement a distributed resource consolidation manager for clouds, called IMPROMPTU. In IMPROMPTU, each autonomous agent is attached to a unique physical machine in the cloud, where it manages resource consolidation independently from the rest of the autonomous agents. On the other hand, the simulation case study regarding coordinated self-management focuses on the problem of adaptive routing in mobile ad hoc networks (MANET). The resulting system carries out adaptation through autonomous agents that are attached to each MANET node in a coordinated manner. In this context, each autonomous node agent expresses its opinion in the form of a decision regarding which routing algorithm should be used given the perceived conditions. The opinions are aggregated through coordination in order to produce a final decision that is to be shared by every node in the MANET.;Although MCDA has been previously considered within the context of artificial intelligence---particularly with respect to algorithms and frameworks that represent different requirements for MCDA problems, to the best of our knowledge, this dissertation outlines a work where MCDA is applied for the first time in the domain of these two problems that are represented as simulation case studies.
机译:本文主要研究分布式系统中的自我管理问题。在这种情况下,我们提出了一种基于多准则决策分析(MCDA)的反应式自我管理的新方法。拟议方法的一般结构是从在其他问题领域中应用的先前公认的方法的共性中提取的。然而,这项工作的主要新颖之处在于,在所提出的方法论所应用的两个问题的背景下,在反应过程中使用了MCDA。为了对这种新方法进行详细的分析和评估,我们已使用建议的方法来设计可在两个突出问题中提供自我管理的分布式自治代理。这两个问题也代表了将方法论应用于自我管理问题的两种不同方式。这两种情况是:1)独立的自我管理,以及2)协调的自我管理。在有关独立自我管理的模拟案例研究中,该方法用于设计和实现用于云的分布式资源整合管理器,称为IMPROMPTU。在IMPROMPTU中,每个自治代理都连接到云中唯一的物理计算机,在该物理计算机上,它独立于其余自治代理来管理资源合并。另一方面,关于协调式自我管理的模拟案例研究集中在移动自组织网络(MANET)中的自适应路由问题。生成的系统通过以协调方式附加到每个MANET节点的自治代理执行适配。在这种情况下,每个自治节点代理以决定的形式表达自己的意见,该决定涉及在给定的感知条件下应使用哪种路由算法。意见是通过协调汇总的,以便做出最终决定,以供MANET中的每个节点共享;尽管MCDA先前已在人工智能的背景下进行了考虑-尤其是在表示算法和框架方面就我们对MCDA问题的不同要求而言,就我们所知,本文概述了在这两个问题领域中首次应用MCDA的工作,这两个问题以模拟案例研究的形式表示。

著录项

  • 作者

    Yazir, Yagiz Onat.;

  • 作者单位

    University of Victoria (Canada).;

  • 授予单位 University of Victoria (Canada).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 171 p.
  • 总页数 171
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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