A genetic based disk scheduling method to decrease makespan and missed tasks

Bonyadi, Mohammad Reza, Rahmani, Hossein and Moghaddam, Mohsen Ebrahimi (2010) A genetic based disk scheduling method to decrease makespan and missed tasks. Information Systems, 35 7: 791-803. doi:10.1016/j.is.2010.04.002

Author Bonyadi, Mohammad Reza
Rahmani, Hossein
Moghaddam, Mohsen Ebrahimi
Title A genetic based disk scheduling method to decrease makespan and missed tasks
Journal name Information Systems   Check publisher's open access policy
ISSN 0306-4379
Publication date 2010-11-01
Year available 2010
Sub-type Article (original research)
DOI 10.1016/j.is.2010.04.002
Open Access Status Not yet assessed
Volume 35
Issue 7
Start page 791
End page 803
Total pages 13
Place of publication Oxford, United Kingdom
Publisher Elsevier
Language eng
Abstract Disk scheduling is an operating system process to service disk requests. It has an important role in QOS guarantee of soft real-time environments such as video-on-demand and multimedia servers. Since now, some disk scheduling algorithms have been proposed to schedule disk requests in an optimized manner. Most of these methods try to minimize makespan by decreasing the number of disk head seeks as one of the slowest operations in modern computers and crucial for system performance because it usually takes some milli-seconds. In this paper, we propose a new disk scheduling method based on genetic algorithm that considers makespan and number of missed tasks simultaneously. In the proposed method, a new coding scheme is presented which employs simple GA procedures such as crossover and mutation and a penalty function in fitness. To get the best performance of the proposed method, its parameters such as number of chromosomes in initial population, mutation, and crossover probabilities, etc have been adjusted by applying it on some sample problems. The algorithm has been tested on several problems and its results were compared with well-known related methods. Experimental results showed that the proposed method worked very well and excelled most related works in terms of miss ratio and average seeks.
Keyword Disk scheduling
Genetic algorithm
Missed tasks
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 600/1508
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 13 Jul 2016, 00:50:20 EST by System User on behalf of Learning and Research Services (UQ Library)