首页> 外文期刊>Concurrency and computation: practice and experience >Customer satisfaction-aware scheduling for utility maximization on geo-distributed data centers
【24h】

Customer satisfaction-aware scheduling for utility maximization on geo-distributed data centers

机译:了解客户满意度的计划,以最大化地理分布数据中心的效用

获取原文
获取原文并翻译 | 示例

摘要

With the increasingly growing amount of service requests from the world-wide customers, the cloud systemsrnare capable of providing services while meeting the customers’ satisfaction. Recently, to achieve thernbetter reliability and performance, the cloud systems have been largely depending on the geographically distributedrndata centers. Nevertheless, the dollar cost of service placement by service providers (SP) differ fromrnthe multiple regions. Accordingly, it is crucial to design a request dispatching and resource allocation algorithmrnto maximize net profit. The existing algorithms are either built upon energy-efficient schemes alone,rnor multi-type requests and customer satisfaction oblivious. They cannot be applied to multi-type requestsrnand customer satisfaction-aware algorithm design with the objective of maximizing net profit. This paperrnproposes an ant-colony optimization-based algorithm for maximizing SP’s net profit (AMP) on geographicallyrndistributed data centers with the consideration of customer satisfaction. First, using model of customerrnsatisfaction, we formulate the utility (or net profit) maximization issue as an optimization problem underrnthe constraints of customer satisfaction and data centers. Second, we analyze the complexity of the optimalrnrequests dispatchment problem and rigidly prove that it is an NP-complete problem. Third, to evaluate thernproposed algorithm, we have conducted the comprehensive simulation and compared with the other stateof-rnthe-art algorithms. Also, we extend our work to consider the data center’s power usage effectiveness. Itrnhas been shown that AMP maximizes SP net profit by dispatching service requests to the proper data centersrnand generating the appropriate amount of virtual machines to meet customer satisfaction. Moreover, we alsorndemonstrate the effectiveness of our approach when it accommodates the impacts of dynamically arrivedrnheavy workload, various evaporation rate and consideration of power usage effectiveness.
机译:随着全球客户对服务的需求日益增长,云系统能够在满足客户满意度的同时提供服务。最近,为了获得更好的可靠性和性能,云系统很大程度上取决于地理分布的数据中心。但是,服务提供商(SP)提供服务的美元成本与多个地区不同。因此,设计一个请求分配和资源分配算法以最大化净利润至关重要。现有的算法要么仅基于节能方案,要么基于多种类型的请求,而客户满意度却被忽略。它们不能应用于以最大化净利润为目标的多种类型的请求和客户满意度感知算法设计。本文提出了一种基于蚁群优化的算法,该算法可在考虑客户满意度的情况下最大化地理分布数据中心上SP的净利润(AMP)。首先,使用客户满意度模型,将效用(或净利润)最大化问题表述为在客户满意度和数据中心约束下的优化问题。其次,我们分析了最优请求调度问题的复杂性,并严格证明了它是一个NP完全问题。第三,为了评估提出的算法,我们进行了全面的仿真,并与其他最新技术进行了比较。此外,我们将工作范围扩展到考虑数据中心的电源使用效率。已经证明,AMP通过将服务请求分配到适当的数据中心并生成适当数量的虚拟机来满足客户满意度,从而最大限度地提高了SP净利润。此外,当该方法适应动态到达的繁重工作负载,各种蒸发速率以及对功率使用效率的影响时,我们还将演示该方法的有效性。

著录项

  • 来源
  • 作者

    Chao Jing; Yanmin Zhu; Minglu Li;

  • 作者单位

    Department of Computer Science and Engineering, Shanghai Jiao Tong Univerisity, Shanghai 200240, ChinaShanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai 200240, ChinaCollege of Information Science and Engineering, Guilin University of Technology, Guilin China,541004;

    Department of Computer Science and Engineering, Shanghai Jiao Tong Univerisity, Shanghai 200240, ChinaShanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai 200240, China;

    Department of Computer Science and Engineering, Shanghai Jiao Tong Univerisity, Shanghai 200240, ChinaShanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai 200240, China;

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

    geo-distributed data centers; utility maximization; customer satisfaction model;

    机译:地理分布的数据中心;效用最大化客户满意度模型;

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