ActiveSLA: a profit-oriented admission control framework for database-as-a-service providers

  • Authors:

  • Pengcheng Xiong;Yun Chi;Shenghuo Zhu;Junichi Tatemura;Calton Pu;Hakan HacigümüŞ

  • Affiliations:

  • Georgia Institute of Technology, Atlanta, GA;NEC Laboratories America, Cupertino, CA;NEC Laboratories America, Cupertino, CA;NEC Laboratories America, Cupertino, CA;Georgia Institute of Technology, Atlanta, GA;NEC Laboratories America, Cupertino, CA

  • Venue:
  • Proceedings of the 2nd ACM Symposium on Cloud Computing
  • Year:
  • 2011

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Abstract

The system overload is a common problem in a Database-as-a-Serice (DaaS) environment because of unpredictable and bursty workloads from various clients. Due to the service delivery nature of DaaS, such system overload usually has direct economic impact on the service provider, who has to pay penalties if the system performance does not meet clients' service level agreements (SLAs). In this paper, we investigate techniques that prevent system overload by using admission control. We propose a profit-oriented admission control framework, called ActiveSLA, for DaaS providers. ActiveSLA is an end-to-end framework that consists of two components. First, a prediction module estimates the probability for a new query to finish the execution before its deadline. Second, based on the predicted probability, a decision module determines whether or not to admit the given query into the database system. The decision is made with the profit optimization objective, where the expected profit is derived from the service level agreements between a service provider and its clients. We present extensive real system experiments with standard database benchmarks, under different traffic patterns, DBMS settings, and SLAs. The results demonstrate that ActiveSLA is able to make admission control decisions that are both more accurate and more profit-effective than several state-of-the-art methods.