Title :
Lightweight Resource Scaling for Cloud Applications
Author :
Han, Rui ; Guo, Li ; Ghanem, Moustafa M. ; Guo, Yike
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
Abstract :
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.
Keywords :
cloud computing; resource allocation; virtual machines; VM level scaling; VM-level elasticity; cloud computing; cost effective elasticity; fine grain scaling; industry standard benchmark; lightweight resource management; lightweight resource scaling; resource allocation; resource deallocation; virtual machine; Cloud computing; Databases; Monitoring; Quality of service; Resource management; Servers; Time factors; cloud computing; lightweight scaling; resource allocation algorithms;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4673-1395-7
DOI :
10.1109/CCGrid.2012.52