Int. J. of Data Science   »   2017 Vol.2, No.3

 

 

Title: An efficient algorithm based on differential evolution for optimum process scheduling

 

Authors: Pooja; Praveena Chaturvedi

 

Addresses:
Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar 249404, India
Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar 249404, India

 

Abstract: In the contemporary study, a modified variant of first-come, first-serve based on differential evolution (DE) algorithm is proposed for process scheduling. As optimised scheduling of processes in an operating system is the key to the overall system performance and throughput, the proposed algorithm, named optimal process sequence using differential evolution (OPS-DE), utilises the advantages of random solutions for initialisation of population with potential candidate solutions. Finally a new mutation strategy is introduced for generating the mutated solution. The performance of the proposed algorithm is evaluated against three classical process scheduling algorithms in terms of average waiting time (AWT) and standard deviation. The efficiency of the proposed algorithm is shown by the empirical analysis of the numerical results.

 

Keywords: differential evolution; mutation; process scheduling algorithms; AWT; average waiting time.

 

DOI: 10.1504/IJDS.2017.10007391

 

Int. J. of Data Science, 2017 Vol.2, No.3, pp.260 - 272

 

Available online: 27 Aug 2017

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article