TY - GEN
T1 - Two-tier multi-tenancy scaling and load balancing
AU - Tsai, Wei Tek
AU - Sun, Xin
AU - Shao, Qihong
AU - Qi, Guanqiu
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=79951775911&partnerID=8YFLogxK
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U2 - 10.1109/ICEBE.2010.103
DO - 10.1109/ICEBE.2010.103
M3 - Conference contribution
AN - SCOPUS:79951775911
SN - 9780769542270
T3 - Proceedings - IEEE International Conference on E-Business Engineering, ICEBE 2010
SP - 484
EP - 489
BT - Proceedings - IEEE International Conference on E-Business Engineering, ICEBE 2010
T2 - IEEE International Conference on E-Business Engineering, ICEBE 2010
Y2 - 10 November 2010 through 12 November 2010
ER -