On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Wide-area traffic: the failure of Poisson modeling
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
IEEE/ACM Transactions on Networking (TON)
Proof of a fundamental result in self-similar traffic modeling
ACM SIGCOMM Computer Communication Review
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Heavy-tailed probability distributions in the World Wide Web
A practical guide to heavy tails
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Evidence for long-tailed distributions in the internet
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
Corrections to "How Does TCP Generate Pseudo-Self-Similarity?"
ACM SIGCOMM Computer Communication Review
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
On the autocorrelation structure of TCP traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
A flow-based model for internet backbone traffic
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
An integrated experimental environment for distributed systems and networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
On the relationship between file sizes, transport protocols, and self-similar network traffic
ICNP '96 Proceedings of the 1996 International Conference on Network Protocols (ICNP '96)
How Does TCP Generate Pseudo-Self-Similarity?
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Long-Range Dependence: Ten Years of Internet Traffic Modeling
IEEE Internet Computing
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
Estimating flow distributions from sampled flow statistics
IEEE/ACM Transactions on Networking (TON)
GNET-1: gigabit Ethernet network testbed
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
Operating system support for planetary-scale network services
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
End-host based mechanisms for implementing flow scheduling in GridNetworks
Proceedings of the first international conference on Networks for grid applications
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Difficulties in modeling SCADA traffic: a comparative analysis
PAM'12 Proceedings of the 13th international conference on Passive and Active Measurement
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After the seminal work by Taqqu et al. relating self-similarity to heavy-tailed distributions, a number of research articles verified that aggregated Internet traffic time series show self-similarity and that Internet attributes, like Web file sizes and flow lengths, were heavy-tailed. However, the validation of the theoretical prediction relating self-similarity and heavy tails remains unsatisfactorily addressed, being investigated using either numerical or network simulations, or from uncontrolled Web traffic data. Notably, this prediction has never been conclusively verified on real networks using controlled and stationary scenarios, prescribing specific heavy-tailed distributions, and estimating confidence intervals. With this goal in mind, we use the potential and facilities offered by the large-scale, deeply reconfigurable and fully controllable experimental Grid5000 instrument, combined with state-of-the-art estimators, to investigate the prediction's observability on real networks. To this end, we organize a large number of controlled traffic circulation sessions on a nationwide real network involving 200 independent hosts. We use a FPGA-based measurement system to collect the corresponding traffic at packet level. We then estimate both the self-similarity exponent of the aggregated time series and the heavy-tail index of flow-size distributions, independently. Not only do our results complement and validate, with a striking accuracy, some conclusions drawn from a series of pioneering studies, but they also bring in new insights on the controversial role of certain components of real networks.