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
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