Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks
Author(s)
Masood, Mohsin
Fouad, Mohamed Mostafa
Glesk, Ivan
Type
Conference Paper
Abstract
Modern communication networks offer advance and diverse applications, which require huge usage of network resources while providing quality of services to the users. Advance communication is based on multiple switched networks that cannot be handle by traditional IP (internet protocol) networks. GMPLS (Generalized multiprotocol label switched) networks, an advance version of MPLS (multiprotocol label switched networks), are introduced for multiple switched networks. Traffic engineering in GMPLS networks ensures traffic movement on multiple paths. Optimal path(s) computation can be dependent on multiple objectives with multiple constraints. From optimization prospective, it is an NP (non-deterministic polynomial-time) hard optimization problem, to compute optimal paths based on multiple objectives having multiple constraints. The paper proposed a metaheuristic Pareto based Bat algorithm, which uses two objective functions; routing costs and load balancing costs to compute the optimal path(s) as an optimal solution for traffic engineering in MPLS/GMPLS networks. The proposed algorithm has implemented on different number of nodes in MPLS/GMPLS networks, to analysis the algorithm performance.
Date Issued
2018-01-26
Date Acceptance
2018-01-01
Citation
Advances in Intelligent Systems and Computing, 2018, 723
ISSN
2194-5357
Publisher
Springer
Journal / Book Title
Advances in Intelligent Systems and Computing
Volume
723
Copyright Statement
© 2018, Springer International Publishing AG.
Source
The International Conference on Machine Learning Technologies and Applications (AMLTA2018)
Publication Status
Published
Start Date
2018-02-22
Finish Date
2018-02-24
Coverage Spatial
Cairo, Egypt