On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Empirically derived analytic models of wide-area TCP connections
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Modeling TCP Reno performance: a simple model and its empirical validation
IEEE/ACM Transactions on Networking (TON)
Testing the Gaussian approximation of aggregate traffic
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Long-Range Dependence: Ten Years of Internet Traffic Modeling
IEEE Internet Computing
MRTG - The Multi Router Traffic Grapher
LISA '98 Proceedings of the 12th USENIX conference on System administration
MRTG - The Multi Router Traffic Grapher
LISA '98 Proceedings of the 12th USENIX conference on System administration
Traffic Modeling with Gamma Mixtures and Dynamical Bandwidth Provisioning
CNSR '06 Proceedings of the 4th Annual Communication Networks and Services Research Conference
Empirical Bandwidth Provisioning Models for High Speed Internet Traffic
CNSR '06 Proceedings of the 4th Annual Communication Networks and Services Research Conference
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
Automated Detection of Load Changes in Large-Scale Networks
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
Detailed analysis of Skype traffic
IEEE Transactions on Multimedia
Long-term forecasting of Internet backbone traffic
IEEE Transactions on Neural Networks
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
Anomaly detection in VoIP traffic with trends
Proceedings of the 24th International Teletraffic Congress
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Traffic models are crucial for network planning, design, performance evaluation and optimization. However, it is first necessary to assess the validity of the newly proposed models. In this paper we present the validation of a multivariate fairly normal model for aggregate traffic that exploits the well-known day-night traffic pattern, which was first assumed and applied in a former work to detect changes in the Internet links’ load on-line. The validation process entails several normality analytical and graphical tests which are applied to real network traffic measurements, on attempts to assess fairly normality both in the marginal and joint distributions of the multivariate model. The results of the normality tests provide evidence that our design is adequate to model aggregate traffic accurately capturing the day-night traffic pattern.