QoS Swarm State Dependent Routing for Irregular Traffic in Telecommunication Networks

Baguenine, F.; Mellouk, Abdelhamid

doi:10.1109/icc.2009.5199379

Cited by 1 publication

(2 citation statements)

References 11 publications

(7 reference statements)

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“…The first one, called N Optimal Path Routing (NOPAR), used the swarm bio-inspired colony optimization with metaheuristics and is based on the work of Sutton and Barto [1997]. The version implemented here is given in Baguenine and Mellouk [2009]. The other one, called AntNet, uses another approach based on the well-known ant colony optimization technique [Dorigo and Stuzle 2004;Dressler and Akan 2010;Dorigo and Blum 2005].…”

Section: Performance Evaluationmentioning

confidence: 99%

“…BeeAdHoc is a reactive source routing algorithm and it consumes less energy as compared to existing state-of-the-art routing algorithms because it utilizes less control packets to do routing. NOPAR (N-best Optimal PAths Routing) [Baguenine and Mellouk 2009] is based on a bio-inspired ant routing technique. The NOPAR system uses a type of forward ant in the exploration phase and a corrective rule in the backward phase.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A state-dependent time evolving multi-constraint routing algorithm

Mellouk

Hoceini

Zeadally

2013

ACM Trans. Auton. Adapt. Syst.

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This article proposes a state-dependent routing algorithm based on a global optimization cost function whose parameters are learned from the real-time state of the network with no a priori model. The proposed approach samples, estimates, and builds the model of pertinent and important aspects of the network environment such as type of traffic, QoS policies, resources, etc. It is based on the trial/error paradigm combined with swarm-adaptive approaches. The global system uses a model that combines both a stochastic planned prenavigation for the exploration phase with a deterministic approach for the backward phase. We conducted a performance analysis of the proposed algorithm using OPNET based on several topologies such as the Nippon telephone and telegraph network. The simulation results obtained demonstrate substantial performance improvements over traditional routing approaches as well as the benefits of learning approaches for networks with dynamically changing traffic.

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