Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki
{"title":"Predictive Auto-scaling Techniques for Clouds Subjected to Requests with Service Level Agreements","authors":"Anshuman Biswas, S. Majumdar, B. Nandy, A. El-Haraki","doi":"10.1109/SERVICES.2015.54","DOIUrl":null,"url":null,"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.","PeriodicalId":106002,"journal":{"name":"2015 IEEE World Congress on Services","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE World Congress on Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERVICES.2015.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.