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This paper proposes a novel framework for evaluating techniques for power optimization in storage. Given an arbitrary trace of disk requests, the authors split it into short time intervals, extract a set of simple statistics for each interval, and apply an analytical model to those statistics to obtain accurate information regarding the performance and energy characteristics of the system for that workload. The key abstraction used in the analytical model is the run-length - a single sequential run of requests at the disk level. Using this abstraction, the model is able to account for arbitrary interactions of random and sequential I/Os in the context of a RAID array, and obtain accurate results with less effort than a detailed individual request-level simulation.
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