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Fast Converging Evolutionary Strategy for Multi-Constraint QoS Routing in Computer Networks Using New Decoding Mechanism

In: Computing and Informatics, vol. 36, no. 2
H.s. Shahhoseini - S. Torkzadeh

Details:

Year, pages: 2017, 405 - 422
Keywords:
Convergence time, evolutionary algorithm, genetic algorithm, multi-objective, population size, QoS routing
About article:
In recent years, real-time multimedia applications' demands such as Voice-on-IP (VoIP) and video conference are extremely increased which require QoS routing. This type of routing has been considered as an NP-Complete problem since it requires satisfying multiple constraints. Many solutions have been proposed to solve it, but most of them are complex and time consuming. In this paper, a novel multi-constraints QoS routing algorithm is proposed based on Evolutionary Strategies (ES). The algorithm preserves simplicity and offers a feasible solution in a few numbers of generations. This is due to a novel gene decoding mechanism that is used in the algorithm; and consequently more simple evolutionary operators can be applied. The simulation results show that our method outperforms previous algorithms in terms of speed and performance, so that it is 2.6 and 11.3 times faster, and its success ratio is also better.
How to cite:
ISO 690:
Shahhoseini, H., Torkzadeh, S. 2017. Fast Converging Evolutionary Strategy for Multi-Constraint QoS Routing in Computer Networks Using New Decoding Mechanism. In Computing and Informatics, vol. 36, no.2, pp. 405-422. 1335-9150. DOI: https://doi.org/10.4149/cai_2017_2_405

APA:
Shahhoseini, H., Torkzadeh, S. (2017). Fast Converging Evolutionary Strategy for Multi-Constraint QoS Routing in Computer Networks Using New Decoding Mechanism. Computing and Informatics, 36(2), 405-422. 1335-9150. DOI: https://doi.org/10.4149/cai_2017_2_405
About edition: