• DocumentCode
    2384670
  • Title

    Two-Tier Multi-tenancy Scaling and Load Balancing

  • Author

    Tsai, Wei-Tek ; Sun, Xin ; Shao, Qihong ; Qi, Guanqiu

  • Author_Institution
    Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
  • fYear
    2010
  • fDate
    10-12 Nov. 2010
  • Firstpage
    484
  • Lastpage
    489
  • Abstract
    Cloud computing often uses the multi-tenancy architecture where tenants share system software. To support dynamically increasing demands from multi-tenants, the cloud service providers have to duplicate computing resources to cope with the fluctuation of requests from tenants. This is currently handled by virtualization and duplication at the application level in the existing cloud environment, such as Google App Engine. However, duplicating at the application level only may result in significant resource waste as the entire application is duplicated. This paper proposes a two-tier SaaS scaling and scheduling architecture that works at both service and application levels to save resources, and the key idea is to increase the resources to those bottleneck components only. Several duplication strategies are proposed, including lazy duplication and pro-active duplication to achieve better system performance. Additionally, a resource allocation algorithm is proposed in a clustered cloud environment. The experiment results showed that the proposed algorithms can achieve a better resource utilization rate.
  • Keywords
    cloud computing; resource allocation; scheduling; software architecture; virtualisation; SaaS scaling architecture; SaaS scheduling architecture; cloud computing; duplication; load balancing; multi-tenancy architecture; two-tier multi-tenancy scaling; virtualization; Clustering algorithms; Computer architecture; Containers; Monitoring; Resource management; Scheduling; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Business Engineering (ICEBE), 2010 IEEE 7th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-8386-0
  • Electronic_ISBN
    978-0-7695-4227-0
  • Type

    conf

  • DOI
    10.1109/ICEBE.2010.103
  • Filename
    5704303