Predictive Auto-scaling Techniques for Clouds Subjected to Requests with Service Level Agreements

Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki
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引用次数: 14

Abstract

This paper focuses research focuses on automatic provisioning of cloud resources performed by an intermediary enterprise that provides a virtual private cloud for a single client enterprise by using resources from a public cloud. This paper concerns auto-scaling techniques for dynamically controlling the number of resources used by the client enterprise. We focus on proactive auto-scaling that is based on predictions of future workload based on the past workload. The primary goal of the auto-scaling techniques is to achieve a profit for the intermediary enterprise while maintaining a desired grade of service for the client enterprise. The technique supports both on demand requests and requests with service level agreements (SLAs). This paper presents an auto-scaling algorithm and includes a discussion of system design and implementation experience for a prototype system that implements the technique. A detailed performance analysis based on measurements made on the prototype is presented.
受服务水平协议请求影响的云的预测自动扩展技术
本文的研究重点是由中间企业执行的云资源自动供应,通过使用公共云的资源为单个客户企业提供虚拟私有云。本文关注用于动态控制客户企业使用的资源数量的自动扩展技术。我们主要关注基于基于过去工作负载的未来工作负载预测的主动自动扩展。自动扩展技术的主要目标是为中间企业实现利润,同时为客户企业保持所需的服务等级。该技术既支持随需应变请求,也支持带有服务水平协议(sla)的请求。本文提出了一种自动缩放算法,并讨论了实现该技术的原型系统的系统设计和实现经验。基于对样机的测量,给出了详细的性能分析。
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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