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Decentralized LPV-MPC controller with heuristic load balancing for a private cloud hosted application
Control Engineering Practice ( IF 4.9 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.conengprac.2020.104438
Durgesh Singh , Saikrishna P.S. , Ramkrishna Pasumarthy , Diwakar Krishnamurthy

Abstract Web-services are increasingly being deployed on cloud platforms that utilize virtual machines (VMs) to share physical resources among many subscribers. This allows a service provider to leverage features such as on-demand resource provisioning with a pay-as-you-go pricing model. An important consideration for the provider of a web-service is the response time experienced by the end-user. This work relies on control theory for performance guarantees of web-servers hosted on the cloud. The objective is to instantiate the optimal number of VMs to keep the response time, below a certain threshold. Firstly, a linear parameter-varying (LPV) model is developed for each of the hosted server. Secondly, a decentralized LPV-MPC controller with workload prediction, is designed to ensure performance under varying workload. The incoming workload distribution across different servers is performed based on a heuristic algorithm consisting of three modes: regular, surge, and energy optimization. The results are validated on an experimental test bed.

中文翻译:

用于私有云托管应用程序的具有启发式负载平衡的分散式 LPV-MPC 控制器

摘要 Web 服务越来越多地部署在云平台上,这些云平台利用虚拟机 (VM) 在许多订阅者之间共享物理资源。这允许服务提供商利用按需资源供应等功能,使用即用即付定价模型。Web 服务提供者的一个重要考虑因素是最终用户所经历的响应时间。这项工作依赖于控制理论来保证托管在云上的网络服务器的性能。目标是实例化最佳虚拟机数量,以将响应时间保持在某个阈值以下。首先,为每个托管服务器开发线性参数变化 (LPV) 模型。其次,具有工作负载预测功能的分散式 LPV-MPC 控制器旨在确保在不同工作负载下的性能。跨不同服务器的传入工作负载分配基于启发式算法执行,该算法由三种模式组成:常规、激增和能量优化。结果在实验测试台上得到验证。
更新日期:2020-07-01
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