N-Best Optimal Path Ant Routing Algorithm for State-Dependent N Best Quality of service Routes in IP Networks

Pong, Fong; Tzeng, M.-F.

doi:10.1109/lcn.2007.154

Cited by 3 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In papers of routing applied to IP networks, Bagula (2006) attempts to maximize the use of network bandwidth and to reduce the delay through the GEP method (Gene Expression Programming). Baguenine & Mellouk (2007) aim at finding a feasible path that satisfies QoS requirements, from the optimization of resources, by reducing the number of hops and delay. The metaheuristic used is the Ant Colony, which attempts to distribute the traffic through the N-best paths according to the criterion of end-to-end delay.…”

Section: Routing Applied To Ip Networkmentioning

confidence: 99%

Multiobjective optimization of MPLS-IP networks with a variable neighborhood genetic algorithm

Onety

Tadei

Neto

et al. 2013

Applied Soft Computing

View full text Add to dashboard Cite

The demand for different levels of Quality of Service (QoS) in IP networks is growing, mainly to attend multimedia applications. However, not only indicators of quality have conflicting features, but also the problem of determining routes covered by more than two QoS constraints is NP-complete (Nondeterministic Polynomial Time Complete). This work proposes an algorithm to optimize multiple Quality of Service indices of Multi Protocol Label Switching (MPLS) IP networks. Such an approach aims at minimizing the network cost and the amount of simultaneous requests rejection, as well as performing load balancing among routes. The proposed algorithm, the Variable Neighborhood Multiobjective Genetic Algorithm (VN-MGA), is a Genetic Algorithm based on the Elitist Non-Dominated Sorted Genetic Algorithm (NSGA-II), with a particular feature that different parts of a solution are encoded differently, at Level 1 and Level 2. In order to improve results, both representations are needed. At Level 1, the first part of the solution is encoded by considering as decision variables the arrows that form the routes to be followed by each request (whilst the second part of the solution is kept constant), whereas at Level 2, the second part of the solution is encoded by considering the sequence of requests as decision variables, and first part is kept constant. Paretofronts obtained by VN-MGA dominate fronts obtained by fixed-neighborhood encoding schemes. Besides potential benefits of the proposed approach application to packet routing optimization in MPLS networks, this work raises the theoretical issue of the systematic application of variable encodings, which allow variable neighborhood searches, as operators inside general evolutionary computation algorithms.

show abstract

Section: Routing Applied To Ip Networkmentioning

confidence: 99%

Multiobjective optimization of MPLS-IP networks with a variable neighborhood genetic algorithm

Onety

Tadei

Neto

et al. 2013

Applied Soft Computing

View full text Add to dashboard Cite

show abstract

“…In this paper, we propose an extension to our previous work on artificial adaptive routing algorithms for real-time flows: Nbest Optimal Paths Ant Routing (NOPAR) system [6] based on Ant routing technique. The NOPAR system uses a model combining both a stochastic planned pre-navigation for the exploration phase (forward ant) and a deterministic approach for the backward phase (backward ant).…”

Section: Introductionmentioning

confidence: 99%

QoS Swarm State Dependent Routing for Irregular Traffic in Telecommunication Networks

Baguenine

Mellouk

2009

2009 IEEE International Conference on Communications

View full text Add to dashboard Cite

This paper introduces a polynomial time approximation Quality of Service (QoS) routing algorithm and constructs dynamic state-dependent routing policies. The proposed algorithm uses an inductive approach based on trial/error paradigm combined with swarm adaptive approaches to optimize the end-to-end delay packet transmission. The algorithm presented here is based on our earlier adaptive routing system and uses a model combining both a stochastic planned pre-navigation for the exploration phase and a deterministic approach for the backward phase. Numerical results obtained with OPNET simulator for different levels of traffic's load show good performances of our approach compared the classical non adaptive algorithms in a high dynamic environment.

show abstract

ANT Based Routing Algorithm over a HAP Network with Integrated Services

Rango¹,

Tropea²,

Provato³

et al. 2008

MICAI 2008: Advances in Artificial Intelligence

View full text Add to dashboard Cite

N-Best Optimal Path Ant Routing Algorithm for State-Dependent N Best Quality of service Routes in IP Networks

Cited by 3 publications

References 31 publications

Multiobjective optimization of MPLS-IP networks with a variable neighborhood genetic algorithm

Multiobjective optimization of MPLS-IP networks with a variable neighborhood genetic algorithm

QoS Swarm State Dependent Routing for Irregular Traffic in Telecommunication Networks

ANT Based Routing Algorithm over a HAP Network with Integrated Services

Contact Info

Product

Resources

About