Abstract
In recent years deploying data-intensive applications in the cloud are gaining a lot of momentum in both research and industrial communities. As the data rates and the processing demands of these applications vary over time, the on-demand cloud paradigm is becoming a good match for their needs. However, the prevalent commercial cloud providers (CPs), operating in isolation (i.e., proprietary in nature), may face resource over-provisioning, degraded performance, and service level agreement (SLA) violations to meet the storage, communication, and processing demands of data-intensive applications. In this chapter, we argue that data intensive cloud providers can form dynamic federation with other CPs to gain economies of scale and an enlargement of their virtual machine (VM) infrastructure capabilities to meet the requirements of data intensive applications. However, there is a need to develop dynamic resource management mechanism to model the economics of VM resource supplying in federating environment. So we also study a game-theoretic solution to this problem that ensures mutual benefits of all the participants in the federation.
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Hassan, M.M., Huh, EN. (2011). Resource Management for Data Intensive Clouds Through Dynamic Federation: A Game Theoretic Approach. In: Furht, B., Escalante, A. (eds) Handbook of Data Intensive Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1415-5_7
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DOI: https://doi.org/10.1007/978-1-4614-1415-5_7
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