Analysis of artificial intelligence-based metaheuristic algorithm for MPLS network optimization

Masood, Mohsin and Fouad, Mohamed Mostafa and Glesk, Ivan (2018) Analysis of artificial intelligence-based metaheuristic algorithm for MPLS network optimization. In: 20th International Conference on Transparent Optical Networks, 2018-07-01 - 2018-07-05, Central Library of University Politehnica Bucharest.

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Abstract

Multiprotocol label switched (MPLS) networks were introduced to enhance the network`s service provisioning and optimize its performance using multiple protocols along with label switched based networking technique. With the addition of traffic engineering entity in MPLS domain, there is a massive increase in the networks resource management capability with better quality of services (QoS) provisioning for end users. Routing protocols play an important role in MPLS networks for network traffic management, which uses exact and approximate algorithms. There are number of artificial intelligence-based optimization algorithms which can be used for the optimization of traffic engineering in MPLS networks. The paper presents an optimization model for MPLS networks and proposed dolphin-echolocation algorithm (DEA) for optimal path computation. For Network with different nodes, both algorithms performance has been investigated to study their convergence towards the production of optimal solutions. Furthermore, the DEA algorithm will be compared with the bat algorithm to examine their performance in MPLS network optimization. Various parameters such as mean, minimum /optimal fitness function values and standard deviation.

ORCID iDs

Masood, Mohsin ORCID logoORCID: https://orcid.org/0000-0002-0473-7865, Fouad, Mohamed Mostafa and Glesk, Ivan ORCID logoORCID: https://orcid.org/0000-0002-3176-8069;
  • Item type:Conference or Workshop Item(Paper)
    ID code:64776
    Dates:
    Date
    Event
    1 July 2018
    Published
    11 May 2018
    Accepted
    15 April 2018
    Submitted
    Notes:© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component 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:12 Jul 2018 11:36
    Last modified:11 Nov 2024 16:55
    URI:https://strathprints.strath.ac.uk/id/eprint/64776
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