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Decentralized LPV-MPC controller with heuristic load balancing for a private cloud hosted application

机译:分散的LPV-MPC控制器,具有私有云托管应用程序的启发式负载平衡

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摘要

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.
机译:Web服务越来越多地部署在利用虚拟机(VM)以在许多订户之间共享物理资源的云平台上部署。这允许服务提供商利用诸如按需资源供应的特征,并使用付费付费定价模型。 Web服务提供商的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云上托管的Web服务器的性能保证的控制理论。目的是实例化最佳的VM,以保持响应时间,低于某个阈值。首先,为每个托管服务器开发了线性参数变化(LPV)模型。其次,设计了具有工作负载预测的分散的LPV-MPC控制器,以确保在不同工作负载下的性能。基于由三种模式组成的启发式算法来执行跨不同服务器的进入的工作负载分布:常规,浪涌和能量优化。结果在实验试验台上验证。

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