Compared with the traditional computing models such as grid computing and cluster computing, a key advantage of Cloud computing is that it provides a practical business model for customers to use remote resources. However, it is challenging for Cloud providers to allocate the pooled computing resources dynamically among the differentiated customers so as to maximize their revenue. It is not an easy task to transform the customer-oriented service metrics into operating level metrics, and control the Cloud resources adaptively based on Service Level Agreement (SLA). This paper addresses the problem of maximizing the provider's revenue through SLA-based dynamic resource allocation as SLA plays a vital role in Cloud computing to bridge service providers and customers. We formalize the resource allocation problem using Queuing Theory and propose optimal solutions for the problem considering various Quality of Service (QoS) parameters such as pricing mechanisms, arrival rates, service rates and available resources. The experimental results, both with the synthetic dataset and with traced dadataset, show that our algorithms outperform related work.
History
Publication title
Proceedings of the 13th ACM/IEEE International Conference on Grid Computing 2012
Pagination
192-200
ISBN
978-1-4673-2901-9
Department/School
School of Information and Communication Technology
Publisher
Institute of Electrical and Electronics Engineers
Place of publication
United States of America
Event title
13th ACM/IEEE International Conference on Grid Computing 2012
Event Venue
Beijing, China
Date of Event (Start Date)
2012-09-20
Date of Event (End Date)
2012-09-23
Rights statement
Copyright 2012 IEEE
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified