Enhancing storage performance in virtualized environments: a pro-active approach
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Efficient storage and retrieval of data is critical in today's computing environments and storage systems need to keep up with the pace of evolution of other system components like CPU, memory etc., for building an overall efficient system. With virtualization becoming pervasive in enterprise and cloud-based infrastructures, it becomes vital to build I/O systems that better account for the changes in scenario in virtualized systems. However, the evolution of storage systems have been limited significantly due to adherence to legacy interface standards between the operating system and storage subsystem. Even though storage systems have become more powerful in the recent times hosting large processors and memory, thin interface to file system leads to wastage of vital information contained in the storage system from being used by higher layers. Virtualization compounds this problem with addition of new indirection layers that makes underlying storage systems even more opaque to the operating system. This dissertation addresses the problem of inefficient use of disk information by identifying storage-level opportunities and developing pro-active techniques to storage management. We present a new class of storage systems called pro-active storage systems (PaSS), which in addition to being compatible with existing I/O interface, exerts a limit degree of control over the file system policies by leveraging it's internal information. In this dissertation, we present our PaSS framework that includes two new I/O interfaces called push and pull, both in the context of traditional systems and virtualized systems. We demonstrate the usefulness of our PaSS framework by a series of case studies that exploit the information available in underlying storage system layer, for overall improvement in IO performance. We also built a framework to evaluate performance and energy of modern storage systems by implementing a novel I/O trace replay tool and an analytical model for measuring performance and energy of complex storage systems. We believe that our PaSS framework and the suite of evaluation tools helps in better understanding of modern storage system behavior and thereby implement efficient policies in the higher layers for better performance, data reliability and energy efficiency by making use of the new interfaces in our framework.