Optimizing utility in cloud computing through autonomic workload execution

Paton, NW, de Aragão, MAT, Lee, K ORCID: 0000-0002-2730-9150, Fernandes, AAA and Sakellariou, R, 2009. Optimizing utility in cloud computing through autonomic workload execution. Bulletin of the Technical Committee on Data Engineering, 32 (1), pp. 51-58.


Download (147kB) | Preview


Cloud computing provides services to potentially numerous remote users with diverse requirements. Although predictable performance can be obtained through the provision of carefully delimited services, it is straightforward to identify applications in which a cloud might usefully host services that support the composition of more primitive analysis services or the evaluation of complex data analysis requests. In such settings, a service provider must manage complex and unpredictable workloads. This paper describes how utility functions can be used to make explicit the desirability of different workload evaluation strategies, and how optimization can be used to select between such alternatives. The approach is illustrated for workloads consisting of workflows or queries.

Item Type: Journal article
Description: Special issue on Data Management on Cloud Computing Platforms.
Publication Title: Bulletin of the Technical Committee on Data Engineering
Creators: Paton, N.W., de Aragão, M.A.T., Lee, K., Fernandes, A.A.A. and Sakellariou, R.
Publisher: IEEE Computer Society
Place of Publication: Los Alamitos, California
Date: 2009
Volume: 32
Number: 1
Rights: Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material foradvertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Divisions: Schools > School of Science and Technology
Depositing User: EPrints Services
Date Added: 09 Oct 2015 09:48
Last Modified: 09 Jun 2017 13:11
URI: http://irep.ntu.ac.uk/id/eprint/3060

Actions (login required)

Edit View Edit View


Views per month over past year


Downloads per month over past year