On the Aggregation of Self-Similar Processes

Gianluca MAZZINI; Riccardo ROVATTI; Gianluca SETTI

doi:10.1093/ietfec/e88-a.10.2656

On the Aggregation of Self-Similar Processes

Gianluca MAZZINI, Riccardo ROVATTI, Gianluca SETTI

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The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E88-A No.10 pp.2656-2663

Publication Date: 2005/10/01

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DOI: 10.1093/ietfec/e88-a.10.2656

Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)

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Gianluca MAZZINI
Riccardo ROVATTI
Gianluca SETTI

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Gianluca MAZZINI, Riccardo ROVATTI, Gianluca SETTI, "On the Aggregation of Self-Similar Processes" in IEICE TRANSACTIONS on Fundamentals, vol. E88-A, no. 10, pp. 2656-2663, October 2005, doi: 10.1093/ietfec/e88-a.10.2656.
Abstract: The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e88-a.10.2656/_p

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@ARTICLE{e88-a_10_2656,
author={Gianluca MAZZINI, Riccardo ROVATTI, Gianluca SETTI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={On the Aggregation of Self-Similar Processes},
year={2005},
volume={E88-A},
number={10},
pages={2656-2663},
abstract={The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.},
keywords={},
doi={10.1093/ietfec/e88-a.10.2656},
ISSN={},
month={October},}

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TY - JOUR
TI - On the Aggregation of Self-Similar Processes
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2656
EP - 2663
AU - Gianluca MAZZINI
AU - Riccardo ROVATTI
AU - Gianluca SETTI
PY - 2005
DO - 10.1093/ietfec/e88-a.10.2656
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E88-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2005
AB - The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.
ER -