Hardware design of a new genetic based disk scheduling method

Abstract

Disk management is an increasingly important aspect of operating systems research and development because it has great effect on system performance. As the gap between processor and disk performance continues to increase in modern systems, access to mass storage is a common bottleneck that ultimately limits overall system performance. In this paper, we propose hardware architecture of a new genetic based real-time disk scheduling method. Also, to have a precise simulation, a neural network is proposed to simulate seek-time of disks. Simulation results showed the hardware implementation of proposed algorithm outperformed software implementation in term of execution time, and other related works in terms of number of tasks that miss deadlines and average seeks.

Supervised Evolution: Research Concerning the Number of Evolutions that Occur Under Certain Constraints

“…Studies dealing with use of genetic algorithms in structure–activity relationship modeling [methods able to establish functional links between the structure of chemical compounds and the associated physical–chemical properties (SPRs) or biological activities (SARs) ] are reported in literature. Generally, the algorithm effectiveness (speed required to achieve the imposed objective function), mutation, and cross‐operators have been investigated and reported , besides identification of the optimum solution . Furthermore, some studies related to genetic algorithms were conducted regarding the correlation coefficient , evolution , validation of number of genotypes present in the generations when an evolution occurred , and assessment of the distribution law for the relative moments of evolution .…”