On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
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)
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
The changing nature of network traffic: scaling phenomena
ACM SIGCOMM Computer Communication Review
Data networks as cascades: investigating the multifractal nature of Internet WAN traffic
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
On estimating the intensity of long-range dependence in finite and infinite variance time series
A practical guide to heavy tails
Dynamics of IP traffic: a study of the role of variability and the impact of control
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
On the relevance of long-range dependence in network traffic
IEEE/ACM Transactions on Networking (TON)
On the propagation of long-range dependence in the Internet
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Random Data: Analysis and Measurement Procedures
Random Data: Analysis and Measurement Procedures
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
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)
Wavelet analysis of long-range-dependent traffic
IEEE Transactions on Information Theory
A multifractal wavelet model with application to network traffic
IEEE Transactions on Information Theory
On multimedia networks: self-similar traffic and network performance
IEEE Communications Magazine
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
On TCP and self-similar traffic
Performance Evaluation - Long range dependence and heavy tail distributions
Predictive connectionist approach for VoD bandwidth management
Computer Communications
BGP-lens: patterns and anomalies in internet routing updates
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Long memory of pathfinding aesthetics
International Journal of Computer Games Technology
A unified study of burst assembly in optical burst switching networks
Photonic Network Communications
Self-similarity: Behind workload reshaping and prediction
Future Generation Computer Systems
APPT'05 Proceedings of the 6th international conference on Advanced Parallel Processing Technologies
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
Characterizing per-application network traffic using entropy
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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The concepts of self-similarity, fractals, and long-range dependence (LRD) have revolutionized network modeling during the last decade. However, despite all the attention these concepts have received, they remain difficult to use by non-experts. This difficulty can be attributed to a relative complexity of the mathematical basis, the absence of a systematic approach to their application and the absence of publicly available software. In this paper, we introduce SELFIS, a comprehensive tool, to facilitate the evaluation of LRD by practitioners. Our goal is to create a stand-alone public tool that can become a reference point for the community. Our tool integrates most of the required functionality for an in-depth LRD analysis, including several LRD estimators. In addition, SELFIS includes a powerful approach to stress-test the existence of LRD, Using our tool, evidence are presented that the widely-used LRD estimators can provide misleading results. It is worth mentioning that 25 researchers have acquired SELFIS within a month of its release, which clearly demonstrates the need for such a tool.