Modified multi-objective firefly algorithm for task scheduling problem on heterogeneous systems. (2016)

• Record Type: Journal Article
• Authors: Eswari, R.; Nickolas, S.
• Is Part Of: International journal of bio-inspired computation. Volume 8:Number 6(2016)
• Page Start: 379
• Page End: 393
• Publication Date: 2016
• Subjects: task scheduling -- multi-objective optimisation -- multi-objective firefly algorithm -- MOFA -- modified algorithms -- metaheuristics -- simulation -- task assignment -- makespan -- reliability; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

Scheduling an application in a heterogeneous environment to find an optimal schedule is a challenging optimisation problem. Maximising the reliability of the application even when processors fails, adds more complexity to the problem. Both the objectives are conflict in nature, where maximising reliability of the application may increase application's completion time. Meta-heuristic algorithms are playing important role in solving the optimisation problem. In this paper, the applicability and efficiency of the new meta-heuristic algorithm called firefly algorithm to solve the workflow multi-objective task scheduling problem is studied. A modified version of the firefly algorithm (MFA) using weighted sum method and a modified version of multi-objective firefly algorithm (MMOFA) using Pareto-dominance method are proposed to solve the multi-objective task scheduling problem. The simulation results show that the proposed algorithms can be used for producing task assignments and also give significant improvements in terms of generating schedule with minimum makespan and maximum reliability compared with existing algorithms.