A Deployment Platform for Dynamically Scaling Applications in the Cloud

Authors:
Rui Han;Li Guo;Yike Guo;Sijin He
Affiliations:
-;-;-;-
Venue:
CLOUDCOM '11 Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science
Year:
2011

Citing 0
Cited 5

Lightweight Resource Scaling for Cloud Applications

CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
A generic framework for service-based business process elasticity in the cloud

BPM'12 Proceedings of the 10th international conference on Business Process Management
A model-driven approach for virtual machine image provisioning in cloud computing

ESOCC'12 Proceedings of the First European conference on Service-Oriented and Cloud Computing
Enabling cost-aware and adaptive elasticity of multi-tier cloud applications

Future Generation Computer Systems
A model view controller based Self-Adjusting Clustering Framework

Journal of Systems and Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

Simplifying the process of deploying applications is almost essential in the cloud. However, existing techniques can automate applications' initial deployment but have not yet adequately addressed their scaling problem. In this paper, a deployment platform to enable a novel dynamic scaling technique is introduced. This platform employs: (i) an extensible specification that describes all aspects of applications, (ii) a flexible analytical model that determines how many servers to be deployed for an application in each scaling. The platform's ability to handle dynamic workloads and to scale applications quickly enough to maintain the response time target is demonstrated.