Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Proof of a fundamental result in self-similar traffic modeling
ACM SIGCOMM Computer Communication Review
On routes and multicast trees in the Internet
ACM SIGCOMM Computer Communication Review
A practical guide to heavy tails
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Difficulties in simulating the internet
IEEE/ACM Transactions on Networking (TON)
Evidence for long-tailed distributions in the internet
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Towards capturing representative AS-level Internet topologies
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
BGP4: Inter-Domain Routing in the Internet
BGP4: Inter-Domain Routing in the Internet
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Estimating flow distributions from sampled flow statistics
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
In search of path diversity in ISP networks
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
A first-principles approach to understanding the internet's router-level topology
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
Flow labelled IP: a connectionless approach to ATM
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 3
Fractals and Scaling In Finance: Discontinuity, Concentration, Risk
Fractals and Scaling In Finance: Discontinuity, Concentration, Risk
A parameterizable methodology for Internet traffic flow profiling
IEEE Journal on Selected Areas in Communications
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
Understanding internet topology: principles, models, and validation
IEEE/ACM Transactions on Networking (TON)
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
More "normal" than normal: scaling distributions and complex systems
WSC '04 Proceedings of the 36th conference on Winter simulation
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Power-Laws in a Large Object-Oriented Software System
IEEE Transactions on Software Engineering
Automatic bandwidth adjustment for content distribution in MPLS networks
Advances in Multimedia
What are our standards for validation of measurement-based networking research?
ACM SIGMETRICS Performance Evaluation Review
Non-parametric and self-tuning measurement-based admission control
NETWORKING'07 Proceedings of the 6th international IFIP-TC6 conference on Ad Hoc and sensor networks, wireless networks, next generation internet
Statistical analysis and modeling of Skype VoIP flows
Computer Communications
A Socratic method for validation of measurement-based networking research
Computer Communications
Computers and Industrial Engineering
Data clustering based on correlation analysis applied to highly variable domains
Computer Networks: The International Journal of Computer and Telecommunications Networking
Detecting correlation between server resources for system management
Journal of Computer and System Sciences
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The Internet is teeming with high variability phenomena, from measured IP flow sizes to aspects of inferred router-level connectivity, but there still exists considerable debate about how best to deal with this encountered high variability and model it. While one popular approach favors modeling highly variable event sizes with conventional, finite variance distributions such as lognormal or Weibull distributions, Mandelbrot has argued for the last 40 years that there are compelling mathematical, statistical, and practical reasons for why infinite variance distributions are natural candidates for capturing the essence behind high variability phenomena. In this paper, we elaborate on Mandelbrot's arguments and present a methodology that often allows for a clear distinction between the two approaches. In particular, by requiring the resulting models to be resilient to ambiguities (i.e., robust to real-world deficiencies in the underlying network measurements) and internally self-consistent (i.e., insensitive with respect the duration, location, or time of the data collection), we provide a rigorous framework for a qualitative assessment of the observed high variability. We apply the proposed framework to assess previously reported findings about measured Internet traffic and inferred router- and AS-level connectivity. In the process, we also discuss what our approach has to say about recent discussions concerning network traffic being Poisson or self-similar and router-level or AS-level connectivity graphs of the Internet being scale-free or not.