Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Queueing networks and Markov chains: modeling and performance evaluation with computer science applications
MPLS: technology and applications
MPLS: technology and applications
Internet QoS: Architectures and Mechanisms for Quality of Service
Internet QoS: Architectures and Mechanisms for Quality of Service
Supporting Service Level Agreements on IP Networks
Supporting Service Level Agreements on IP Networks
OSPF Network Design Solutions
OSPF: Anatomy of an Internet Routing Protocol
OSPF: Anatomy of an Internet Routing Protocol
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
BRITE: Universal Topology Generation from a User''s Perspective
BRITE: Universal Topology Generation from a User''s Perspective
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Traffic engineering approaches using multicriteria optimization techniques
WWIC'11 Proceedings of the 9th IFIP TC 6 international conference on Wired/wireless internet communications
A framework for robust traffic engineering using evolutionary computation
AIMS'13 Proceedings of the 7th IFIP WG 6.6 international conference on Autonomous Infrastructure, Management, and Security: emerging management mechanisms for the future internet - Volume 7943
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This paper presents a traffic engineering framework able to optimize OSPF weight setting administrative procedures. Using the proposed framework, enhanced OSPF configurations are now provided to network administrators in order to effectively improve the QoS performance of the corresponding network domain. The envisaged NP-hard optimization problem is faced resorting to Evolutionary Algorithms, which allocate OSPF weights guided by a bi-objective function. The results presented in this work show that the proposed optimization tool clearly outperforms common weight setting heuristics.