Title: Labelled evolutionary Petri nets/genetic algorithm based approach for workflow scheduling in cloud computing

Authors: Manel Femmam; Okba Kazar; Laid Kahloul; Mohamed El-Kabir Fareh

Addresses: LINFI Laboratory, Computer Science Department, Biskra University, Biskra, Algeria ' LINFI Laboratory, Computer Science Department, Biskra University, Biskra, Algeria ' LINFI Laboratory, Computer Science Department, Biskra University, Biskra, Algeria ' LINFI Laboratory, Computer Science Department, Biskra University, Biskra, Algeria

Abstract: Nowadays, many evolutionary algorithms for workflow scheduling in cloud computing are available. Most of those algorithms focus on the effectiveness, discarding the issue of flexibility. Research on Petri nets addresses the issue of flexibility; many extensions have been proposed to facilitate the modelling of complex systems. Typical extensions are the addition of 'colour', 'time' and 'hierarchy'. By mapping scheduling problems into Petri nets, we are able to use standard Petri net theory. In this case, the scheduling problem can be reduced to finding an optimal sequence of transitions leading from an initial marking to a final one. To find the optimal scheduling, we propose a new approach based on a recently proposed formalism 'Evolutionary Petri Net' (EPN), which is an extension of Petri net, enriched with two genetic operators, crossover and mutation. The objectives of our research are to minimise the workflow application completion time (makespan) as well as the cost incurred by using cloud resources. Some numerical experiments are carried out to demonstrate the usefulness of our algorithm.

Keywords: workflow scheduling; cloud computing; Petri nets; genetic algorithm.

DOI: 10.1504/IJGUC.2018.091721

International Journal of Grid and Utility Computing, 2018 Vol.9 No.2, pp.157 - 169

Received: 13 May 2016
Accepted: 07 Mar 2017

Published online: 01 May 2018 *

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