Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Control Theoretic Analysis of Mixed TCP and UDP Traffic under RED Based on Nonlinear Dynamic Model
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Network Management: Current Trends and Future Perspectives
Journal of Network and Systems Management
New Regulations to the Next Generation Network
CMC '09 Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 02
QoS-aware service composition using NSGA-II1
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Metaheuristic Optimization of Large-Scale QoS-aware Service Compositions
SCC '10 Proceedings of the 2010 IEEE International Conference on Services Computing
QoS-based service optimization using differential evolution
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Equitable solutions in QoS-aware service optimization
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Fraud detection in web transactions
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Methodology for fraud detection in electronic transactions
Proceedings of the 18th Brazilian symposium on Multimedia and the web
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In recent years, computer networks have been characterized by heterogeneous traffic and dynamic management of different kinds of services. The web and network requirements have increased within time and, since bandwidth is limited, it becomes necessary to employ optimization procedures in order to make the network able to operate in its full capacity. Traffic shaping mechanisms implement Quality of Service (QoS) concepts to ensure acceptable service levels. This paper describes an approach for traffic shaping optimization. It is proposed a methodology based on throughput and packet loss optimization using genetic algorithms. This method was validated using actual data from a network infrastructure of a Public Educational Institution.