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Optimized self-service resource containers for next generation cloud delivery

Next generation cloud computing is envisioned to allow any logical combination of information technology (IT) and network resources to deliver cloud services in the most cost-effective and efficient manner. Advanced self-service, infrastructure convergence, and high flexibility are crucial in such an environment. To achieve the vision of such a next generation paradigm, suitable means of addressing complex interaction between various virtual resources need to be addressed. This thesis proposes a novel service framework, the virtual-cells-as-a-service (vCAAS), to address the need for advanced interaction of cloud services. vCAAS enables converged cloud services in which virtual machines, network and storage resources are delivered in a self-service virtual infrastructure container. The approach views cloud resources in a holistic manner where components interact and complement each other to complete a task without manual intervention. The thesis begins with a statement of the problem addressed and the objectives of the research. The methodology adopted for the research is .described subsequently and the outline of the thesis presented. These are followed by a brief introduction highlighting the current developments in cloud computing and the enabling technologies for the new paradigm. Next, the thesis presents a framework for the proposed vCAAS. Various components and enabling functionalities required to realise the framework are described. Multi-objective optimization strategies suitable for the problems in vCAAS are presented. A case for hybrid optical and electrical switching for intra-cloud datacenters to enable cloud services is also made. Novel algorithms for traffic management in the hybrid cloud data center are proposed and demonstrated in a simulation experiment. Finally, the thesis presents a practical application of the novel concept of vCAAS in solving a real world scientific data analysis problem.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:654479
Date January 2014
CreatorsMusa, Ibrahim Kabiru
PublisherUniversity of Essex
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

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