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General applications 1: a highly efficient M/G/∞ model for generating self-similar traces
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Source Winter Simulation Conference archive
Proceedings of the 34th conference on Winter simulation: exploring new frontiers table of contents
San Diego, California
SESSION: General applications and methodology table of contents
Pages: 2003 - 2010  
Year of Publication: 2002
ISBN:0-7803-7615-3
Authors
Maria Estrella Sousa-Vieira  Universidade de Vigo, Spain
Andrés Suarez-González  Universidade de Vigo, Spain
Cándido Lopez-García  Universidade de Vigo, Spain
Manuel Fernández-Veiga  Universidade de Vigo, Spain
José C. López-Ardao  Universidade de Vigo, Spain
Sponsors
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
(SCS) : The Society for Modeling and Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
Publisher
Winter Simulation Conference 
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ABSTRACT

Several traffic measurement reports have convincingly shown the presence of self-similarity in modern networks, inducing as a result a revolution in the stochastic modeling of traffic. The use of self-similar processes in performance analysis has opened new problems and research issues in simulation studies, where the efficient generation of synthetic sample paths with self-similar properties is one of the fundamental concerns. In this paper, we present an M/G/∞ generator of self-similar traces, based on a highly efficient simulation model using the decomposition property of Poisson processes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Cox, D. R. 1984. Long range dependence: A review. Statistics: An Appraisal. Iowa State University Press.
 
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Cox, D. R. and V. Isham. 1980. Point Processes. Chapman and Hall.
 
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Krunz, M. M. and A. M. Makowski. Modeling Video Traffic Using M/G/∞ Input Processes: A Compromise Between Markovian and LRD Models. IEEE Journal on Selected Areas in Communications 16 (5): 733--748.
 
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Parulekar, M. and A. M. Makowski. 1996. Tail probabilities for a multiplexer with self-similar traffic. In Proceedings of IEEE INFOCOMM'96. San Francisco, CA.
 
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Poon, W. and K. Lo 2001. A refined version of M/G/∞ processes for modeling VBR video traffic. Computer Communications 24 (11): 1105--1114.
 
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Collaborative Colleagues:
Maria Estrella Sousa-Vieira: colleagues
Andrés Suarez-González: colleagues
Cándido Lopez-García: colleagues
Manuel Fernández-Veiga: colleagues
José C. López-Ardao: colleagues