Cloud adoption: a goal-oriented requirements engineering approach

Zardari, Shehnila (2016). Cloud adoption: a goal-oriented requirements engineering approach. University of Birmingham. Ph.D.

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The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers’ ability to meet service level agreements. These risks hinder the adoption of cloud computing.
We motivate the need for a new requirements engineering methodology for systematically helping businesses and users to adopt cloud services and for mitigating risks in such transition. The methodology is grounded in goal-oriented approaches for requirements engineering. We argue that Goal-Oriented Requirements Engineering (GORE) is a promising paradigm to adopt for goals that are generic and flexible statements of users’ requirements, which could be refined, elaborated, negotiated, mitigated for risks and analysed for economics considerations. The methodology can be used by small to large scale organisations to inform crucial decisions related to cloud adoption.
We propose a risk management framework based on the principle of GORE. In this approach, we liken risks to obstacles encountered while realising cloud user goals, therefore proposing cloud-specific obstacle resolution tactics for mitigating identified risks. The proposed framework shows benefits by providing a principled engineering approach to cloud adoption and empowering stakeholders with tactics for resolving risks when adopting the cloud.
We extend the work on GORE and obstacles for informing the adoption process. We argue that obstacles’ prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Computer Science
Funders: None/not applicable
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science


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