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

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. Document type: Conference objec

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

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

A Coevolutionary Particle Swarm Algorithm for Bi-Level Variational Inequalities: Applications to Competition in Highway Transportation Networks

A climate of increasing deregulation in traditional highway transportation, where the private sector has an expanded role in the provision of traditional transportation services, provides a background for practical policy issues to be investigated. One of the key issues of interest, and the focus of this chapter, would be the equilibrium decision variables offered by participants in this market. By assuming that the private sector participants play a Nash game, the above problem can be described as a Bi-Level Variational Inequality (BLVI). Our problem differs from the classical Cournot-Nash game because each and every player’s actions is constrained by another variational inequality describing the equilibrium route choice of users on the network. In this chapter, we discuss this BLVI and suggest a heuristic coevolutionary particle swarm algorithm for its resolution. Our proposed algorithm is subsequently tested on example problems drawn from the literature. The numerical experiments suggest that the proposed algorithm is a viable solution method for this problem

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Fixed-Mobile Convergence in the 5G era: From Hybrid Access to Converged Core

The availability of different paths to communicate to a user or device introduces several benefits, from boosting enduser performance to improving network utilization. Hybrid access is a first step in enabling convergence of mobile and fixed networks, however, despite traffic optimization, this approach is limited as fixed and mobile are still two separate core networks inter-connected through an aggregation point. On the road to 5G networks, the design trend is moving towards an aggregated network, where different access technologies share a common anchor point in the core. This enables further network optimization in addition to hybrid access, examples are userspecific policies for aggregation and improved traffic balancing across different accesses according to user, network, and service context. This paper aims to discuss the ongoing work around hybrid access and network convergence by Broadband Forum and 3GPP. We present some testbed results on hybrid access and analyze some primary performance indicators such as achievable data rates, link utilization for aggregated traffic and session setup latency. We finally discuss the future directions for network convergence to enable future scenarios with enhanced configuration capabilities for fixed and mobile convergence.Comment: to appear in IEEE Networ