A Pareto based approach with elitist learning strategy for MPLS/GMPS networks

Mohsin Masood, Mohamed Mostafa Fouad, Ivan Glesk

Research output: Contribution to conferenceProceeding

1 Citation (Scopus)
38 Downloads (Pure)

Abstract


Abstract—Modern telecommunication networks are based on diverse applications that highlighted the status of efficient use of network resources and performance optimization. Various methodologies are developed to address multi-objectives optimization within the traffic engineering of MPLS/ GMPLS networks. However, Pareto based approach can be used to achieve the optimization of multiple conflicting objective functions concurrently. The paper considered two objective functions such as routing and load balancing costs functions. The paper introduces a heuristics algorithm for solving multi-objective multiple constrained optimization (MCOP) in MPLS/ GMPLS networks. The paper proposes the application of a Pareto based particle swarm optimization (PPSO) for such network’s type and through a comparative analysis tests its efficiency against another modified version; Pareto based particle swarm optimization with elitist learning strategy (PPSO ELS). The simulation results showed that the former proposed approach not only solved the MCOP problem but also provide effective solution for exploration problem attached with PPSO algorithm.
Original languageEnglish
Publication statusPublished - 27 Sep 2017
Event9th Computer Science & Electronic Engineering Conference - Tony Rich Teaching Centre, University of Essex, Colchester, United Kingdom
Duration: 27 Sep 201729 Sep 2017
http://ceec.uk/

Conference

Conference9th Computer Science & Electronic Engineering Conference
Abbreviated titleCEEC'17
CountryUnited Kingdom
CityColchester
Period27/09/1729/09/17
Internet address

Fingerprint

Particle swarm optimization (PSO)
Constrained optimization
Heuristic algorithms
Multiobjective optimization
Cost functions
Resource allocation
Telecommunication networks

Keywords

  • MPLS
  • GMPLS network optimization
  • particle swarm optimization
  • heurastic algorithm
  • traffic engineering
  • weight inertia

Cite this

Masood, M., Fouad, M. M., & Glesk, I. (2017). A Pareto based approach with elitist learning strategy for MPLS/GMPS networks. 9th Computer Science & Electronic Engineering Conference, Colchester, United Kingdom.
Masood, Mohsin ; Fouad, Mohamed Mostafa ; Glesk, Ivan. / A Pareto based approach with elitist learning strategy for MPLS/GMPS networks. 9th Computer Science & Electronic Engineering Conference, Colchester, United Kingdom.
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Masood, M, Fouad, MM & Glesk, I 2017, 'A Pareto based approach with elitist learning strategy for MPLS/GMPS networks' 9th Computer Science & Electronic Engineering Conference, Colchester, United Kingdom, 27/09/17 - 29/09/17, .

A Pareto based approach with elitist learning strategy for MPLS/GMPS networks. / Masood, Mohsin; Fouad, Mohamed Mostafa; Glesk, Ivan.

2017. 9th Computer Science & Electronic Engineering Conference, Colchester, United Kingdom.

Research output: Contribution to conferenceProceeding

TY - CONF

T1 - A Pareto based approach with elitist learning strategy for MPLS/GMPS networks

AU - Masood, Mohsin

AU - Fouad, Mohamed Mostafa

AU - Glesk, Ivan

N1 - (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

PY - 2017/9/27

Y1 - 2017/9/27

N2 - Abstract—Modern telecommunication networks are based on diverse applications that highlighted the status of efficient use of network resources and performance optimization. Various methodologies are developed to address multi-objectives optimization within the traffic engineering of MPLS/ GMPLS networks. However, Pareto based approach can be used to achieve the optimization of multiple conflicting objective functions concurrently. The paper considered two objective functions such as routing and load balancing costs functions. The paper introduces a heuristics algorithm for solving multi-objective multiple constrained optimization (MCOP) in MPLS/ GMPLS networks. The paper proposes the application of a Pareto based particle swarm optimization (PPSO) for such network’s type and through a comparative analysis tests its efficiency against another modified version; Pareto based particle swarm optimization with elitist learning strategy (PPSO ELS). The simulation results showed that the former proposed approach not only solved the MCOP problem but also provide effective solution for exploration problem attached with PPSO algorithm.

AB - Abstract—Modern telecommunication networks are based on diverse applications that highlighted the status of efficient use of network resources and performance optimization. Various methodologies are developed to address multi-objectives optimization within the traffic engineering of MPLS/ GMPLS networks. However, Pareto based approach can be used to achieve the optimization of multiple conflicting objective functions concurrently. The paper considered two objective functions such as routing and load balancing costs functions. The paper introduces a heuristics algorithm for solving multi-objective multiple constrained optimization (MCOP) in MPLS/ GMPLS networks. The paper proposes the application of a Pareto based particle swarm optimization (PPSO) for such network’s type and through a comparative analysis tests its efficiency against another modified version; Pareto based particle swarm optimization with elitist learning strategy (PPSO ELS). The simulation results showed that the former proposed approach not only solved the MCOP problem but also provide effective solution for exploration problem attached with PPSO algorithm.

KW - MPLS

KW - GMPLS network optimization

KW - particle swarm optimization

KW - heurastic algorithm

KW - traffic engineering

KW - weight inertia

M3 - Proceeding

ER -

Masood M, Fouad MM, Glesk I. A Pareto based approach with elitist learning strategy for MPLS/GMPS networks. 2017. 9th Computer Science & Electronic Engineering Conference, Colchester, United Kingdom.