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

Authors

  • Hadi Shahriar Shahhoseini School of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran
  • Samaneh Torkzadeh School of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran

Keywords:

Convergence time, evolutionary algorithm, genetic algorithm, multi-objective, population size, QoS routing

Abstract

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.

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Published

2017-06-12

How to Cite

Shahhoseini, H. S., & 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. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/2017_2_405