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IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 8, AUGUST 2003 2229 Cluster Processes: A Natural Language
 

Summary: IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 51, NO. 8, AUGUST 2003 2229
Cluster Processes: A Natural Language
for Network Traffic
Nicolas Hohn, Darryl Veitch, Senior Member, IEEE, and Patrice Abry
Abstract--We introduce a new approach to the modeling of
network traffic, consisting of a semi-experimental methodology
combining models with data and a class of point processes (cluster
models) to represent the process of packet arrivals in a physically
meaningful way. Wavelets are used to examine second-order
statistics, and particular attention is paid to the modeling of
long-range dependence and to the question of scale invariance at
small scales. We analyze in depth the properties of several large
traces of packet data and determine unambiguously the influence
of network variables such as the arrival patterns, durations, and
volumes of transport control protocol (TCP) flows and internal
flow structure. We show that session-level modeling is not relevant
at the packet level. Our findings naturally suggest the use of
cluster models. We define a class where TCP flows are directly
modeled, and each model parameter has a direct meaning in
network terms, allowing the model to be used to predict traffic

  

Source: Abry, Patrice - Laboratoire de Physique, Ecole Normale Supérieure de Lyon

 

Collections: Engineering