A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
IEEE/ACM Transactions on Networking (TON)
Online multicast routing with bandwidth guarantees: a new approach using multicast network flow
IEEE/ACM Transactions on Networking (TON)
Making routing robust to changing traffic demands: algorithms and evaluation
IEEE/ACM Transactions on Networking (TON)
Routing optimization in IP networks utilizing additive and concave link metrics
IEEE/ACM Transactions on Networking (TON)
On the use of accounting data for QoS-aware IP network planning
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Achieving high robustness and performance in QoS-aware route planning for IPTV networks
Information Sciences: an International Journal
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This paper proposes a novel approach to performing residual bandwidth optimization with QoS guarantees in multi-class networks. The approach combines the use of a new highly scalable hybrid GA-VNS algorithm (Genetic Algorithm with Variable Neighborhood Search) with the efficient and accurate estimation of QoS requirements using empirical effective bandwidth estimations. Given a QoS-aware demand matrix, experimental results indicate that the GA-VNS algorithm shows significantly higher success rate in terms of converging to optimum/near optimum solution in comparison to pure GA and another combination of GA and local search heuristic, and also exhibits better scalability and performance. Additional results also show that the proposed solution performs significantly better than OSPF in optimizing residual bandwidth in a medium to large sized network.