Effective bandwidths at multi-class queues
Queueing Systems: Theory and Applications
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
D-BIND: an accurate traffic model for providing QoS guarantees to VBR traffic
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
On the nonstationarity of Internet traffic
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Principles of Neurocomputing for Science and Engineering
Principles of Neurocomputing for Science and Engineering
Internet research needs better models
ACM SIGCOMM Computer Communication Review
Longitudinal study of Internet traffic in 1998-2003
WISICT '04 Proceedings of the winter international synposium on Information and communication technologies
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Long-range dependence in a changing internet traffic mix
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Techniques for available bandwidth measurement in IP networks: a performance comparison
Computer Networks: The International Journal of Computer and Telecommunications Networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
Neural Networks in Finance: Gaining Predictive Edge in the Market (Academic Press Advanced Finance Series)
Prediction of MPEG-coded video source traffic using recurrent neural networks
IEEE Transactions on Signal Processing
Understanding Internet traffic streams: dragonflies and tortoises
IEEE Communications Magazine
IEEE Journal on Selected Areas in Communications
On the use of fractional Brownian motion in the theory of connectionless networks
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Neural Networks
Admission control for statistical QoS: theory and practice
IEEE Network: The Magazine of Global Internetworking
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This paper proposes using artificial neural network (ANN)-based architectures for modeling and predicting network traffic. Application on the Connexion by Boeing^(R) (CBB) global broadband network was evaluated to establish feasibility. Accurate characterization and prediction of network traffic is essential for network resource sizing and for real-time network management. As networks increase in size and complexity the task becomes increasingly difficult. Current methods try to model network bandwidth through linear mathematical expressions that are not sufficiently adaptable or scalable. Accuracy of these models is based on detailed characterization of the traffic stream measured at points along the network that are subject to constant variation and evolution. The main contribution of this paper is development of a methodology that allows utilization of artificial neural networks with the capability for adaptation. A simulation model was constructed and feasibility tests were run to evaluate the applicability on the CBB network and to demonstrate improvements in accuracy over existing methods.