Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks

Mohsin Masood, Mohamed Mostafa Fouad, Ivan Glesk

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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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.
Original languageEnglish
Title of host publicationThe International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018)
EditorsAboul Ella Hassanien, Mohamed F. Tolba, Mohamed Elhoseny, Mohamed Mostafa
Place of PublicationCham
PublisherSpringer
Pages33-41
Number of pages9
ISBN (Print)9783319746890, 9783319746906
DOIs
Publication statusE-pub ahead of print - 26 Jan 2018
EventThe International Conference on Machine Learning Technologies and Applications - Cairo, Egypt
Duration: 22 Feb 201824 Feb 2018
http://egyptscience.net/AMLTA18/

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume723
ISSN (Print)2194-5357

Conference

ConferenceThe International Conference on Machine Learning Technologies and Applications
Abbreviated titleAMLTA2018
CountryEgypt
CityCairo
Period22/02/1824/02/18
Internet address

Fingerprint

Switching networks
Labels
Internet protocols
Resource allocation
Telecommunication networks
Costs
Quality of service
Polynomials
Communication

Keywords

  • bat algorithm
  • GMPLS networks
  • networks optimization
  • particle swarm optimization
  • routing protocols
  • traffic engineering

Cite this

Masood, M., Fouad, M. M., & Glesk, I. (2018). Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks. In A. E. Hassanien, M. F. Tolba, M. Elhoseny, & M. Mostafa (Eds.), The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) (pp. 33-41). (Advances in Intelligent Systems and Computing; Vol. 723). Cham: Springer. https://doi.org/10.1007/978-3-319-74690-6_4
Masood, Mohsin ; Fouad, Mohamed Mostafa ; Glesk, Ivan. / Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks. The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). editor / Aboul Ella Hassanien ; Mohamed F. Tolba ; Mohamed Elhoseny ; Mohamed Mostafa. Cham : Springer, 2018. pp. 33-41 (Advances in Intelligent Systems and Computing).
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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.",
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Masood, M, Fouad, MM & Glesk, I 2018, Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks. in AE Hassanien, MF Tolba, M Elhoseny & M Mostafa (eds), The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). Advances in Intelligent Systems and Computing, vol. 723, Springer, Cham, pp. 33-41, The International Conference on Machine Learning Technologies and Applications, Cairo, Egypt, 22/02/18. https://doi.org/10.1007/978-3-319-74690-6_4

Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks. / Masood, Mohsin; Fouad, Mohamed Mostafa; Glesk, Ivan.

The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). ed. / Aboul Ella Hassanien; Mohamed F. Tolba; Mohamed Elhoseny; Mohamed Mostafa. Cham : Springer, 2018. p. 33-41 (Advances in Intelligent Systems and Computing; Vol. 723).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N2 - 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.

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Masood M, Fouad MM, Glesk I. Pareto based bat algorithm for multi objectives multiple constraints optimization in GMPLS networks. In Hassanien AE, Tolba MF, Elhoseny M, Mostafa M, editors, The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). Cham: Springer. 2018. p. 33-41. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-74690-6_4