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

Mohsin Masood, Mohamed Mostafa Fouad, Ivan Glesk

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)
24 Downloads (Pure)


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.
Original languageEnglish
Number of pages4
Publication statusPublished - 1 Jul 2018
Event20th International Conference on Transparent Optical Networks - Central Library of University Politehnica Bucharest, Bucharest, Romania
Duration: 1 Jul 20185 Jul 2018


Conference20th International Conference on Transparent Optical Networks
Abbreviated titleICTON 2018
Internet address


  • Artificial-Intelligence optimization tools
  • MPLS network optimization
  • traffic engineering
  • dolphin echolocation algorithm
  • bat algorithm


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