Adaptive Resource Allocation of Multiple Servers for Service-Based Systems in Cloud Computing

Siqian Gong, Beibei Yin, Wenlong Zhu, K. Cai
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引用次数: 4

Abstract

Due to the advantages of cloud computing, it has been adopted as deployment platform of SBS (Service-based Systems). It also provides an elastic "pay-as-you-go" mode, which creates new resource allocation challenge that satisfying the QoS (Quality of Service) requirements with least resource allocation. There has been much interest in using feedback control to make resource allocation, but these works focus on a single control that does not take the interactions between servers share and compete for the same resource pool. In this paper, we present an adaptive resource allocation approach for SBS in the cloud environment using MIMO (Multi-Input and Multi-Output) control to allocate resource to multiple servers according to multiple workloads. The experimental results show that our approach can ensure the QoS with least resource allocation and increase the resource utilization.
云计算中基于服务系统的多服务器自适应资源分配
由于云计算的优势,它已被采用为SBS (Service-based Systems)的部署平台。它还提供了一种弹性的“现收现付”模式,这种模式创造了新的资源分配挑战,以最少的资源分配满足QoS(服务质量)需求。人们对使用反馈控制来进行资源分配很感兴趣,但这些工作都集中在单一的控制上,这种控制不会使服务器之间的交互共享和竞争相同的资源池。在本文中,我们为云环境中的SBS提供了一种自适应资源分配方法,使用MIMO(多输入多输出)控制,根据多个工作负载将资源分配给多个服务器。实验结果表明,该方法可以在最少的资源分配情况下保证服务质量,提高资源利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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