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Multi-objective multi-constrained QoS Routing in large-scale networks: A genetic algorithm approach

Abstract : The growing need for a simplified management of network infrastructures has recently led to the emergence of software-defined networking (SDN), which enables a centralized path calculation. The diversification of services, as well as the need of rapid path deployment, raises, however, challenges in routing algorithms. Moreover, Quality of Service (QoS) requirements and conflicts between them pile up the complexity of the problem. An intuitive method is formulating the problem as an Integer Linear Programming and solving it by an approximation algorithm. This method tends to have a specific design and usually suffers from unacceptable computational delays to provide a sub-optimal solution. Genetic algorithms (GAs) are deemed as a promising solution to cope with highly complex optimization problems. However, the convergence speed and the quality of solutions should be addressed in order to fit into practical implementations. In this paper, we propose a genetic algorithm-based mechanism to address the multi-constrained multi-objective routing problem. Using a repairer to reduce the search space to feasible solutions, results confirm that the proposed mechanism is able to find the Pareto-optimal solutions within a short run-time.
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https://hal.inria.fr/hal-01933976
Contributor : Yassine Hadjadj Aoul <>
Submitted on : Saturday, November 24, 2018 - 11:34:46 PM
Last modification on : Thursday, February 25, 2021 - 5:30:02 PM
Long-term archiving on: : Monday, February 25, 2019 - 12:41:14 PM

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  • HAL Id : hal-01933976, version 1

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Quang Tran Anh Pham, Jean-Michel Sanner, Cedric Morin, Yassine Hadjadj-Aoul. Multi-objective multi-constrained QoS Routing in large-scale networks: A genetic algorithm approach. SaCoNet 2018 - 7th IEEE International Conference on Smart Communications in Network Technologies, Oct 2018, El Oued, Algeria. pp.1-6. ⟨hal-01933976⟩

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