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
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)
Providing public intradomain traffic matrices to the research community
ACM SIGCOMM Computer Communication Review
Making routing robust to changing traffic demands: algorithms and evaluation
IEEE/ACM Transactions on Networking (TON)
A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
Routing optimization in IP networks utilizing additive and concave link metrics
IEEE/ACM Transactions on Networking (TON)
Constraint-Based Evolutionary QoS Adaptation for Power Utility Communication Networks
ICTAI '09 Proceedings of the 2009 21st IEEE International Conference on Tools with Artificial Intelligence
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
Ensemble of constraint handling techniques
IEEE Transactions on Evolutionary Computation
A memetic algorithm for extending wireless sensor network lifetime
Information Sciences: an International Journal
EA'09 Proceedings of the 9th international conference on Artificial evolution
Entropy of ATM traffic streams: a tool for estimating QoS parameters
IEEE Journal on Selected Areas in Communications
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Quality of Service (QoS)-aware network planning in internet protocol television (IPTV) networks becomes increasingly important for network operators and Internet Service Providers (ISP) alike as different components of IPTV traffic have different and stringent QoS requirements. Proposing a routing algorithm to meet individual QoS parameters is a tedious task, since providing guarantee of meeting individual parameters in a stochastic system is impossible. Therefore, we propose optimum allocation of bandwidth where bandwidth requirements are evaluated based on accurate empirical effective bandwidth estimation for different classes of traffic by simulating a path as a First-in-First-out (FIFO) queue [2], whereby meeting the individual QoS requirements of each class of traffic. The route planning problem was formulated as a residual bandwidth optimization problem and solved using Genetic Algorithm-Variable Neighborhood Search (GA-VNS) hybrid algorithm. Although the standard evolutionary algorithms do not perform well on constrained optimization problems [4], GA-VNS was found to perform well on this particular problem [9]. This paper proposes new and novel adjustments and parameter settings to best suit the problem in terms of robustness and performance. The use of dynamically switching between two cost functions to meet the above requirements, the reduction of the difficulty of the problem in the initial generations to find a feasible solution and the use of a variation of the original VNS algorithm, besides the use of specific operators and general parameter settings are some of the recommendations of this paper. The proposed recommendations are based on extensive experiments on the performance and analysis carried out on different network topologies including Abilene topology. The proposed algorithm performed better than the recently proposed specialized constrained handling algorithms proposed in the literature, i.e. problem specific solutions are more desirable than black-box optimization for this problem. The proposed route planning mechanism was also found to produce good results even under dynamic traffic conditions.