Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.816456
Title: Intelligent management of virtualised computer based workloads and systems
Author: Oakes, James
ISNI:       0000 0004 9354 5578
Awarding Body: University of Northampton
Current Institution: University of Northampton
Date of Award: 2020
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Abstract:
Managing the complexity within virtualised IT infrastructure platforms is a common problem for many organisations today. Computer systems are often highly consolidated into a relatively small physical footprint compared with previous decades prior to late 2000s, so much thought, planning and control is necessary to effectively operate such systems within the enterprise computing space. With the development of private, hybrid and public cloud utility computing this has become even more relevant; this work examines how such cloud systems are using virtualisation technology and embedded software to leverage advantages, and it uses a fresh approach of developing and creating an Intelligent decision engine (expert system). Its aim is to help reduce the complexity of managing virtualised computer-based platforms, through tight integration, high-levels of automation to minimise human inputs, errors, and enforce standards and consistency, in order to achieve better management and control. The thesis investigates whether an expert system known as the Intelligent Decision Engine (IDE) could aid the management of virtualised computer-based platforms. Through conducting a series of mixed quantitative and qualitative experiments in the areas of research, the initial findings and evaluation are presented in detail, using repeatable and observable processes and provide detailed analysis on the recorded outputs. The results of the investigation establish the advantages of using the IDE (expert system) to achieve the goal of reducing the complexity of managing virtualised computer-based platforms. In each detailed area examined, it is demonstrated how using a global management approach in combination with VM provisioning, migration, failover, and system resource controls can create a powerful autonomous system.
Supervisor: Turner, Scott John ; Johnson, Mark Andrew ; Xue, Wenjun Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.816456  DOI: Not available
Keywords: Intelligent ; Virtual Machine ; Automation ; VM ; Expert System ; IDE ; Decision Engine ; Computer Virtualisation ; Computer Virtualization
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