Research and Advances
Artificial Intelligence and Machine Learning

Optimal balancing of I/O requests to disks

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Determining a policy for efficient allocation and utilization of a set of disk drives with differing operational characteristics is examined using analytical techniques. Using standard queueing theory, each disk drive is characterized by a queueing model with service time of a disk drive represented by the probability density function of the sum of two uniform distributions. Total response time of the set of disk models is then minimized under varying load conditions. The results indicate that faster devices should have higher utilization factors and that the number of different device types utilized tends to decrease with decreasing load. Specific examples using 2314 and 3330 combinations are examined.

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