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Knowledge-based disk scheduling policy using fuzzy logic

Hard disk is the important component in computer system as data storage device. It is being used to store large amount of information in all modern computers. However, hard drive speed improvement slower than their capacity. Thus, long service delay for I/O bound processes may occur. Disk scheduling is an important issue for providing a quick response time in query processing. Operating System being the interface between the user and the hardware has the responsibility to use hardware efficiently. One crucial branch of this function is to decrease the response time and allow for better bandwidth through disk scheduling. Disk scheduling is used when processes running on the machine have multiple requests for data from the disks and a particular order is needed to access them most effectively. There are two major operations in the disk scheduling head-positioning of a hard disk i.e. seeking and tracking. Current algorithm have not included the system knowledge about the additional information provided by Operating System and not been used for improvement of the seeking and/or tracking accessing. This research project applies fuzzy model knowledge based on improving the disk scheduling algorithm. Incorporating knowledge-based scheduling policy using fuzzy logic improves the average response time, average seeks distance and average seeks time.