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Adaptively improving performance stability of cloud based application using the modern portfolio theory

Alrebeish, Faisal (2016)
Ph.D. thesis, University of Birmingham.

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The increasing number of Software-as-a-Service(SaaS) services available in the cloud market make them plausible and attractive for building cloud-based applications. However, performance instability is common in the cloud environment due to changes in supply and demand of shared computational infrastructure and resources. Candidate services are vulnerable to such instability. Current service selection and composition approaches do not explicitly address performance fluctuations when building cloud-based applications. This thesis proposes a novel approach to improve performance stability by leveraging on the principles of design diversity and portfolio-based thinking when selecting and composing cloud-based applications. The objective is to minimize the risks that could stem from selecting and composing cloud-based services that are vulnerable to performance instability.

In this thesis, we use two scenarios to illustrate the applicability and the effectiveness of the approach. As scalability is of paramount importance for efficient dynamic and adaptive selection and composition, the thesis adapt a systematic method to identify the various scalability dimensions that can affect the working of the approach and consequently evaluate the sensitivity of the approach to the identified dimensions. The thesis concludes with possible directions for future work.

Type of Work:Ph.D. thesis.
Supervisor(s):Bahsoon, Rami
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:School of Computer Science
Additional Information:

Publications resulting from research:

F. Alrebeish and R. Bahsoon, "Stabilising Performance in Cloud Services Composition Using Portfolio Theory," Web Services (ICWS), 2015 IEEE International Conference on, New York, NY, 2015, pp. 1-8.
doi: 10.1109/ICWS.2015.11

Faisal ALRebeish, Rami Bahsoon, "Risk-Aware Web Service Allocation in the Cloud Using Portfolio Theory", SCC, 2013, 2013 IEEE International Conference on Services Computing (SCC), 2013 IEEE International Conference on Services Computing (SCC) 2013, pp. 675-682, doi:10.1109/SCC.2013.40

Alrebeish, Faisal, and Rami Bahsoon. "Using portfolio theory to diversify the dynamic allocation of web services in the cloud." Proceedings of the 15th annual conference companion on Genetic and evolutionary computation. ACM, 2013.

F. Alrebeish and R. Bahsoon, "Implementing Design Diversity Using Portfolio Thinking to Dynamically and Adaptively Manage the Allocation of Web Services in the Cloud," in IEEE Transactions on Cloud Computing, vol. 3, no. 3, pp. 318-331, July-Sept. 1 2015.
doi: 10.1109/TCC.2015.2415783

Subjects:TK Electrical engineering. Electronics Nuclear engineering
Institution:University of Birmingham
ID Code:6932
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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