Title: Experimental study for makespan reduction in enterprise application integration processes using bio-inspired algorithms

Authors: Maira S. Brigo; Fernando Parahyba; Rafael Z. Frantz; Sandro Sawicki; Fabricia Roos-Frantz

Addresses: Unijuí University, Rua do Comércio, Ijuí, Rio Grande do Sul, Brazil ' Unijuí University, Rua do Comércio, Ijuí, Rio Grande do Sul, Brazil ' Unijuí University, Rua do Comércio, Ijuí, Rio Grande do Sul, Brazil ' Unijuí University, Rua do Comércio, Ijuí, Rio Grande do Sul, Brazil ' Unijuí University, Rua do Comércio, Ijuí, Rio Grande do Sul, Brazil

Abstract: Enterprise Application Integration area seeks to support the companies' business processes by enabling data and functionality of the applications to become reusable. Integration platforms are tools that develop and execute integration processes. This execution is done by a key component of the platforms called run-time system; that said, the performance from integration processes heavily depends on the efficiency of the run-time system. The task-based execution model implemented by the run-time system can use a strategy based on local pools to store computational threads associated with each task that make up the workflow of the integration process, in order to execute them. The challenge in this strategy is to evenly distribute the threads in each pool, minimising the makespan. We propose an experimental study, which uses two meta-heuristics to find the best distribution with the optimal number of threads. We compared both Particle Swarm Optimisation and Cat Swarm Optimisation, with the latter showing better results.

Keywords: makespan; task-based; run-time system; optimisation; integration platforms; integration process; meta-heuristics; particle swarm optimisation; cat swarm optimisation; threads.

DOI: 10.1504/IJCAT.2023.131063

International Journal of Computer Applications in Technology, 2023 Vol.71 No.1, pp.18 - 32

Received: 21 Dec 2021
Received in revised form: 29 Mar 2022
Accepted: 02 May 2022
Published online: 23 May 2023 *

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