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Local dependencies and Poissonification: a case study

Andersson, Sofia LU and Rydén, Tobias LU (2003) In Performance Evaluation 52(1). p.41-58
Abstract
Traffic characterization is of great importance in the analysis and dimensioning of modem telecommunication networks. In this paper, the microdynamics of some sets of traffic are investigated. The approach we use to study the microdynamics is Poissonification, which is away of transforming a point process into a Poisson process locally. We want to gain basic knowledge of how the traffic behaves on smaller time scales, but we also want to see if there are any effects when the traffic is fed into a queue. As an application, Poissonification can be used when modeling is done with a doubly stochastic Poisson process to find the time scale where we no longer have the doubly stochastic behavior. Three different traffic traces were analyzed in... (More)
Traffic characterization is of great importance in the analysis and dimensioning of modem telecommunication networks. In this paper, the microdynamics of some sets of traffic are investigated. The approach we use to study the microdynamics is Poissonification, which is away of transforming a point process into a Poisson process locally. We want to gain basic knowledge of how the traffic behaves on smaller time scales, but we also want to see if there are any effects when the traffic is fed into a queue. As an application, Poissonification can be used when modeling is done with a doubly stochastic Poisson process to find the time scale where we no longer have the doubly stochastic behavior. Three different traffic traces were analyzed in this paper. The results show that provided the Poissonification is carried out at a sufficiently small time scale, the performance characteristics are not decisively changed and this gives a guide to choosing the time scale at which to start traffic modeling. (Less)
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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
analysis, performance, traffic analysis, microdynamics, Poissonification, point process spectrum
in
Performance Evaluation
volume
52
issue
1
pages
41 - 58
publisher
Elsevier
external identifiers
  • wos:000180923700003
  • scopus:0037349043
ISSN
0166-5316
DOI
10.1016/S0166-5316(02)00162-1
language
English
LU publication?
yes
id
91c03ef8-c50d-4297-8e32-b691ee35be26 (old id 318502)
date added to LUP
2016-04-01 12:30:00
date last changed
2022-01-27 05:54:17
@article{91c03ef8-c50d-4297-8e32-b691ee35be26,
  abstract     = {{Traffic characterization is of great importance in the analysis and dimensioning of modem telecommunication networks. In this paper, the microdynamics of some sets of traffic are investigated. The approach we use to study the microdynamics is Poissonification, which is away of transforming a point process into a Poisson process locally. We want to gain basic knowledge of how the traffic behaves on smaller time scales, but we also want to see if there are any effects when the traffic is fed into a queue. As an application, Poissonification can be used when modeling is done with a doubly stochastic Poisson process to find the time scale where we no longer have the doubly stochastic behavior. Three different traffic traces were analyzed in this paper. The results show that provided the Poissonification is carried out at a sufficiently small time scale, the performance characteristics are not decisively changed and this gives a guide to choosing the time scale at which to start traffic modeling.}},
  author       = {{Andersson, Sofia and Rydén, Tobias}},
  issn         = {{0166-5316}},
  keywords     = {{analysis; performance; traffic analysis; microdynamics; Poissonification; point process spectrum}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{41--58}},
  publisher    = {{Elsevier}},
  series       = {{Performance Evaluation}},
  title        = {{Local dependencies and Poissonification: a case study}},
  url          = {{http://dx.doi.org/10.1016/S0166-5316(02)00162-1}},
  doi          = {{10.1016/S0166-5316(02)00162-1}},
  volume       = {{52}},
  year         = {{2003}},
}