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Resources are often shared to improve resource utilization and reduce costs. However, not all resources exhibit good performance when shared amongst multiple applications. The paper presented here focuses on effectively managing a shared storage cache. In order to provide differentiated services to applications exercising a storage cache, the authors propose a novel scheme that uses curve fitting to dynamically partition the storage cache. The scheme quickly adapts to application execution showing increasing accuracy over time. It satisfies application QoS if it is possible to do so, maximizes the individual hit rates of the applications utilizing the cache, and consequently increases the overall storage cache hit rate.
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