TY - GEN
T1 - Lightweight resource scaling for cloud applications
AU - Han, Rui
AU - Guo, Li
AU - Ghanem, Moustafa M.
AU - Guo, Yike
PY - 2012
Y1 - 2012
N2 - Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the virtual machine (VM) instances to the application. This VM-level elasticity typically incurs both considerable overhead and extra costs, especially for applications with rapidly fluctuating demands. In this paper, we propose a lightweight approach to enable cost-effective elasticity for cloud applications. Our approach operates fine-grained scaling at the resource level itself (CPUs, memory, I/O, etc) in addition to VM-level scaling. We also present the design and implementation of an intelligent platform for light-weight resource management of cloud applications. We describe our algorithms for light-weight scaling and VM-level scaling and show their interaction. We then use an industry standard benchmark to evaluate the effectiveness of our approach and compare its performance against traditional approaches.
AB - Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the virtual machine (VM) instances to the application. This VM-level elasticity typically incurs both considerable overhead and extra costs, especially for applications with rapidly fluctuating demands. In this paper, we propose a lightweight approach to enable cost-effective elasticity for cloud applications. Our approach operates fine-grained scaling at the resource level itself (CPUs, memory, I/O, etc) in addition to VM-level scaling. We also present the design and implementation of an intelligent platform for light-weight resource management of cloud applications. We describe our algorithms for light-weight scaling and VM-level scaling and show their interaction. We then use an industry standard benchmark to evaluate the effectiveness of our approach and compare its performance against traditional approaches.
KW - cloud computing
KW - lightweight scaling
KW - resource allocation algorithms
UR - http://www.scopus.com/inward/record.url?scp=84863690423&partnerID=8YFLogxK
U2 - 10.1109/CCGrid.2012.52
DO - 10.1109/CCGrid.2012.52
M3 - Conference contribution
AN - SCOPUS:84863690423
SN - 9780769546919
T3 - Proceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
SP - 644
EP - 651
BT - Proceedings - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
T2 - 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
Y2 - 13 May 2012 through 16 May 2012
ER -