...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Future generation computer systems >A predictive approach for the efficient distribution of agent-based systems on a hybrid-cloud
【24h】

A predictive approach for the efficient distribution of agent-based systems on a hybrid-cloud

机译：在混合云上有效分配基于代理的系统的一种预测方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Hybrid clouds are increasingly used to outsource non-critical applications to public clouds. However, the main challenge within such environments, is to ensure a cost-efficient distribution of the systems between the resources that are on/off premises. For Multi Agent Systems (MAS), this challenge is deepened due to irregular workload progress and intensive communication between the agents, which may result in high computing and data transfer costs. Thus, in this paper we propose a generic framework for adaptive cost-efficient deployment of MAS with a special focus on hybrid clouds. The framework is based mainly on the use of a performance evaluation process that consists of simulating various partitioning options to estimate and optimize the overall deployment costs. Further, to cope with the irregular workload changes within a MAS and dynamically adapt its initial deployment, we propose an extended version of the Fiduccia–Mattheyses algorithm (E-FM). The experimental results highlight the efficiency of E-FM and show that an efficient MAS deployment to hybrid clouds depends on various factors such as the cloud providers and their different cost-models, the network state, the used partitioning algorithm, and the initial deployment.
机译：混合云越来越多地用于将非关键应用程序外包给公共云。但是，在这种环境中的主要挑战是确保在开/关场所的资源之间以经济高效的方式分配系统。对于多代理系统（MAS），由于工作负载进度不正常以及代理之间的密集通信，这一挑战变得更加严峻，这可能会导致较高的计算和数据传输成本。因此，在本文中，我们提出了一种适用于MAS的自适应经济高效部署的通用框架，其中特别关注混合云。该框架主要基于性能评估过程的使用，该过程包括模拟各种分区选项以估计和优化总体部署成本。此外，为了应对MAS中不规则的工作负载变化并动态调整其初始部署，我们提出了Fiduccia-Mattheyses算法（E-FM）的扩展版本。实验结果突出了E-FM的效率，并表明将MAS有效部署到混合云取决于多种因素，例如云提供商及其不同的成本模型，网络状态，使用的分区算法和初始部署。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号