Exploring cost-effective resource management strategies in the age of utility computing
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| Publicat a: | ProQuest Dissertations and Theses (2013) |
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| 001 | 1712397974 | ||
| 003 | UK-CbPIL | ||
| 020 | |a 978-1-321-96308-3 | ||
| 035 | |a 1712397974 | ||
| 045 | 0 | |b d20130101 | |
| 084 | |a 66569 |2 nlm | ||
| 100 | 1 | |a Zhao, Han | |
| 245 | 1 | |a Exploring cost-effective resource management strategies in the age of utility computing | |
| 260 | |b ProQuest Dissertations & Theses |c 2013 | ||
| 513 | |a Dissertation/Thesis | ||
| 520 | 3 | |a With the rapid progress of computing, storage and networking technologies, distributed computing paradigms have undergone profound changes in the past decade. We are entering an era of “Everything-as-a-Service” where resources are shared at an unprecedented scale and deliver agile, metered computing services to both business and scientific communities. The so called utility computing model, built upon cloud computing infrastructures, becomes ubiquitous in the enterprise IT landscape. It is therefore of paramount importance to devise efficient resource management strategies to scale with the growth of the system. However, the problem of managing resource allocations in a utility computing environment is challenging because both resources and administrative parties who operate these resources feature diverse heterogeneity. As utility computing proliferates, scalable resource sharing platform instantiated on multiple resource providers become cheaper and more accessible. As a result, strategy design for resource management in a utility computing model should equally address the heterogeneous interests of various involved parties who pursue maximum economic benefits. As a result, an inter-disciplinary research approach that combines economic models in social computing scenarios with algorithmic design in computer science becomes a viable option for researchers to build cost-effective resource scheduling strategies in utility computing. We recognized three fundamental issues that govern the exploration in cost-effective resource management strategies in this dissertation. 1. The flourish of virtualization technology enables more flexible resource aggregation and presents an exponential search space for optimization. 2. The heterogeneous nature of user interests has direct impact on resource management decisions. 3. Financial costs play an important role in determining the achievable application performance. To address these issues, we develop several resource management strategies that achieve cost-effectiveness and flexibility with regard to various scheduling contexts in utility computing. Our study seeks to investigate economic models and their implication to the utility-oriented scheduling problems. The proposed research highlights the heterogeneity challenge presented in utility and cloud computing. Concentrating on the strategy design space of resource customers, our study for cost-effective resource management strategy progressively evolve towards better efficiency and flexibility. Specifically, this dissertation include the following main scientific contributions: (1) development of optimal resource rental planning models in a utility computing environment, based on linear integer programming and stochastic optimization techniques; (2) design of a suite of efficient and fair resource trading protocols, allowing the distributed system to benefit from utility-driven resource trading activities; and (3) implementation of an experimental market-oriented resource sharing platform integrating cloud resource management with eBay’s transaction model. The study presented in this dissertation improves upon existing research as it targets at cost-effective design and accommodates flexibility in service provisioning and acquisition in utility computing. | |
| 653 | |a Computer science | ||
| 653 | |a Computer engineering | ||
| 773 | 0 | |t ProQuest Dissertations and Theses |g (2013) | |
| 786 | 0 | |d ProQuest |t ProQuest Dissertations & Theses Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1712397974/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1712397974/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |