Stochastic modeling of traffic processes
Frontiers in queueing
On the nonstationarity of Internet traffic
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
On the characteristics and origins of internet flow rates
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Why is the internet traffic bursty in short time scales?
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Multifractality in TCP/IP traffic: the case against
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Small-time scaling behavior of Internet backbone traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Queueing analysis of network traffic: methodology and visualization tools
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Stochastic processes for computer network traffic modeling
Computer Communications
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
Wavelet analysis of long-range-dependent traffic
IEEE Transactions on Information Theory
Packet Trains--Measurements and a New Model for Computer Network Traffic
IEEE Journal on Selected Areas in Communications
A nonstationary traffic train model for fine scale inference from coarse scale counts
IEEE Journal on Selected Areas in Communications
On the use of fractional Brownian motion in the theory of connectionless networks
IEEE Journal on Selected Areas in Communications
PAM '09 Proceedings of the 10th International Conference on Passive and Active Network Measurement
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Much effort has been spent in analyzing and modeling IP traffic from the perspective of the packet-counting process that aggregates packet arrivals over fixed time intervals. Much less has been done regarding the modeling of the patterns of arrival of IP packets. The main purpose of this study was to determine whether the ON-OFF packet-level model is an adequate model. As shown in this paper, at the aggregate level the answer is yes, to great accuracy. Further, it compares favorably to other models such as modulated Poisson arrivals. At the IP-flow level, the ON-OFF model is not adequate; rather, an active-inactive model is appropriate. The reason is that the rate in the ON state greatly varies from an ON period to the other. We further argue experimentally that it is only necessary to consider a small number of hosts and host pairs to account for the impact on a queuing system and on the long-term variability of the traffic. The starting point of the approach is to analyze and model traffic along the dimensions of packet size and packet inter-arrival processes. The method is applied to well-known and publicly available traces from the ITA and NLANR repositories, as well as traces of traffic captured in our institution premises.