Title: Hybrid genetic algorithm for task scheduling in distributed real-time system

Authors: Harendra Kumar; Nutan Kumari Chauhan; Pradeep Kumar Yadav

Addresses: Department of Mathematics and Statistics, Gurukula Kangri Vishwavidyalaya Haridwar, 249404, Uttarakhand, India ' Department of Mathematics and Statistics, Gurukula Kangri Vishwavidyalaya Haridwar, 249404, Uttarakhand, India ' Department of Research Planning and Business Development, Central Building Research Institute, Roorkee, 247667, Uttarakhand, India

Abstract: A distributed real-time system consists of a set of heterogeneous processors located at possibly different sites and connected by a communication link. Task scheduling in distributed real-time system attracts the attention of the researcher in many disciplines. Many researchers have been developed the solution of task scheduling problem by using different types of technique. In this paper, a hybrid genetic algorithm (HGA) is developed which is a combination of k-means and genetic algorithm to form the clusters of tasks in an effort to minimise the communication costs. A genetic algorithm is also developed to schedule the formed clusters of tasks onto set of processors to minimise the execution costs. The results of the algorithm have been compared with various existing techniques. Experiment results shows that the proposed algorithm achieves better efficiency than other existing techniques.

Keywords: task scheduling; distributed real-time system; DRTS; genetic algorithm; k-mean; system costs; response time.

DOI: 10.1504/IJSCC.2019.097417

International Journal of Systems, Control and Communications, 2019 Vol.10 No.1, pp.32 - 51

Received: 11 Jan 2018
Accepted: 21 Aug 2018

Published online: 15 Jan 2019 *

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