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The Availability Heuristic01:08

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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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在云计算平台中基于多决策 AHP 方法的虚拟机调度研究.

Hangyu Gu1, Jinjiang Wang1, Junyang Yu1

  • 1Software School, Henan University, Kaifeng, Henan Province, China.

PeerJ. Computer science
|December 11, 2023
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概括
此摘要是机器生成的。

本研究介绍了用于虚拟机调度的高效算法 (AESVMP),以减少云数据中心的能源消耗和服务级别协议违规. 与现有方法相比,拟议的方法显著降低了迁移数量,违规行为和能源消耗.

关键词:
在 AHP AHP 中.云计算平台 云计算平台在 QoS 时,QoS 是 QoS.虚拟机放置位置 虚拟机放置位置

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科学领域:

  • 计算机科学 计算机科学
  • 云计算 云计算 云计算
  • 人工智能的人工智能

背景情况:

  • 云数据中心面临着大量的能源消耗和服务水平协议 (SLA) 违规行为.
  • 动态虚拟机整合需要高效的调度和资源分配机制.
  • 提高服务质量 (QoS) 对云数据中心运营至关重要.

研究的目的:

  • 为动态整合中的虚拟机调度提出一个高效的算法 (AESVMP).
  • 为了减少能源消耗和SLA违规,同时改善云数据中心的QoS.
  • 使用分析层次过程 (AHP) 增强虚拟机调度.

主要方法:

  • 开发了一个基于分析层次过程 (AHP) 的算法 (AESVMP).
  • 考虑主机功耗,可用资源和资源分配平衡比率作为关键标准.
  • 基于三维资源 (CPU,RAM,BW) 的计算资源分配平衡比率.
  • 在虚拟机安置决策中使用多标准决策技术.

主要成果:

  • AESVMP算法将迁移的数量平均减少了51.76%.
  • 违反服务水平协议 (SLAV) 的情况平均减少了67.4%.
  • 与LBVMP相比,总能耗 (ESV) 平均下降了67.6%,比LBVMP.
  • 使用CloudSim模拟器与PlanetLab工作负载进行了广泛的实验.

结论:

  • 拟议的AESVMP算法有效地减轻了云数据中心的能源消耗和SLA违规行为.
  • 与前沿的LBVMP方法相比,AESVMP在虚拟机调度方面表现优越.
  • 该方法验证了AHP在云资源管理的多标准决策中的有效性.