A First Order Approach to Optimizing Storage As A Service Open Access
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Cloud computing service providers are currently viewed as innovative solutions to the global need for massive data systems because of their superior flexibility, scalability, and cost benefits. Cloud computing enabled by virtualized services is still constrained, however, by the capacities of the underlying physical systems that are combined into sharable pools of resources. The next challenge for computer systems will arise when Cloud computing is no longer sufficient. What comes after Cloud migration and adoption?This research examined how service providers can manage Cloud storage resources and costs when the amount of collected data that needs to be retained grows exponentially, to the point that it strains even virtualized resource capacities. A comprehensive review was conducted to assess the analytical frameworks being developed to identify which storage architectures can best accommodate the specific needs of large data storage consumers. This dissertation demonstrates the areas in which prior research on Cloud storage failed to fully address the problem of data growth and proposed a solution. Specific steps, tools, and results from this study produced a Cloud Storage Framework (CSF). The developed framework addresses data volume, data growth trends over time, and requirements to assist Cloud consumers with storage management. The framework’s intent is to enable Cloud consumer with a method to optimize Cloud storage resources and manage costs in such a manner that the Cloud will continue to offer the greatest benefits for the storage of massive data systems.