Name
Abstract | ||
|---|---|---|
We develop a probabilistic framework for global modeling of the traffic over
a computer network. This model integrates existing single-link (-flow) traffic
models with the routing over the network to capture the global traffic
behavior. It arises from a limit approximation of the traffic fluctuations as
the time--scale and the number of users sharing the network grow. The resulting
probability model is comprised of a Gaussian and/or a stable, infinite variance
components. They can be succinctly described and handled by certain
'space-time' random fields. The model is validated against simulated and real
data. It is then applied to predict traffic fluctuations over unobserved links
from a limited set of observed links. Further, applications to anomaly
detection and network management are briefly discussed. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | random field,anomaly detection,network management,limit set,computer network |
Field | DocType | Volume |
Data mining,Traffic generation model,Anomaly detection,Network planning and design,Computer science,Network simulation,Computer network,Gaussian,Network management,Network traffic simulation,Traffic equations,Distributed computing | Journal | abs/1005.4 |
Citations | PageRank | References |
2 | 0.46 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stilian A. Stoev | 1 | 10 | 1.26 |
| George Michailidis | 2 | 303 | 35.19 |
| Joel Vaughan | 3 | 13 | 1.44 |