A Pareto based approach with elitist learning strategy for MPLS/GMPS networks
Masood, Mohsin and Fouad, Mohamed Mostafa and Glesk, Ivan (2017) A Pareto based approach with elitist learning strategy for MPLS/GMPS networks. In: 9th Computer Science & Electronic Engineering Conference, 2017-09-27 - 2017-09-29, Tony Rich Teaching Centre, University of Essex.
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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.
ORCID iDs
Masood, Mohsin ORCID: https://orcid.org/0000-0003-4388-569X, Fouad, Mohamed Mostafa and Glesk, Ivan ORCID: https://orcid.org/0000-0002-3176-8069;-
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Item type: Conference or Workshop Item(Paper) ID code: 62008 Dates: DateEvent27 September 2017Published25 August 2017Accepted3 July 2017SubmittedNotes: (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. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 11 Oct 2017 14:45 Last modified: 11 Nov 2024 16:51 URI: https://strathprints.strath.ac.uk/id/eprint/62008