Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Experimental queueing analysis with long-range dependent packet traffic
IEEE/ACM Transactions on Networking (TON)
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
Does fractal scaling at the IP level depend on TCP flow arrival processes?
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Bridging router performance and queuing theory
Proceedings of the joint international conference on Measurement and modeling of computer systems
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
A model for interference on links in inter-working multi-hop wireless networks
AST/UCMA/ISA/ACN'10 Proceedings of the 2010 international conference on Advances in computer science and information technology
A framework for connectivity in inter-working multi-hop wireless networks
ruSMART/NEW2AN'10 Proceedings of the Third conference on Smart Spaces and next generation wired, and 10th international conference on Wireless networking
Framework for link reliability in inter-working multi-hop wireless networks
Mathematical and Computer Modelling: An International Journal
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This paper concerns the modelling of Internet packet traffic. In previous work we showed that a Bartlett-Lewis point process, as a model of packet arrivals on backbone links, enjoys strong physical backing and can predict key features. It is based on the surprising empirical observation that flows can often be considered independent for the purpose of modelling packet arrival times. We extend this work in two ways by using a unique dataset obtained from an experiment where all the packets crossing a backbone router are captured. First, this enables an examination of the validity of the fundamental assumptions underlying the model across several links, covering a large range of bandwidths and utilization levels. Second, we extend the model from links to a network node, by examining the merging and splitting properties of the (sub)streams through the router, and mapping these to the merging and splitting properties of the model. We show how the model can, in most cases, capture the observed multiplexing and demultiplexing behaviour of the router, opening up the possibility of its use for understanding traffic flows in networks. We show that failures in the model cannot be accounted for simply through considering utilisation levels, and explain how they can in fact be used as a detector of upstream bottlenecks and traffic shaping.