FLAME: Flow level traffic matrix estimation using poisson shot-noise process for SDN

2016 ◽  
Author(s):  
Yoonseon Han ◽  
Taeyeol Jeong ◽  
Jae-Hyoung Yoo ◽  
James Won-Ki Hong
Keyword(s):  
Shot Noise ◽  
Matrix Estimation ◽  
Noise Process ◽  
Shot Noise Process ◽  
Traffic Matrix ◽  
Traffic Matrix Estimation ◽  
Poisson Shot Noise

The central limit theorem for the Poisson shot-noise process

1984 ◽  
Vol 21 (02) ◽  
pp. 287-301 ◽  
Author(s):  
John A. Lane
Keyword(s):  
Shot Noise ◽  
Sufficient Conditions ◽  
Infinitely Divisible ◽  
Noise Process ◽  
Shot Noise Process ◽  
The Central Limit Theorem ◽  
Cluster Point Process ◽  
Necessary And Sufficient ◽  
Poisson Cluster ◽  
Poisson Shot Noise

The Poisson shot-noise process discussed here takes the form f:oo H(t, s)N(ds), where N(· is the counting measure of a Poisson process and the H(·, s) are independent stochastic processes. Necessary and sufficient conditions are obtained for convergence in distribution, as t ∼ OC, to any infinitely divisible distribution. The main interest is in the explosive transient one-sided shot-noise, Y(t) = f:1 H(t, s)N(ds) where Var Y(t)∼ oc, Here conditions for asymptotic normality are discussed in detail. Important examples include the Poisson cluster point process and the integrated stationary shotnoise.

The central limit theorem for the Poisson shot-noise process

1984 ◽  
Vol 21 (2) ◽  
pp. 287-301 ◽  
Author(s):  
John A. Lane
Keyword(s):  
Shot Noise ◽  
Sufficient Conditions ◽  
Infinitely Divisible ◽  
Noise Process ◽  
Shot Noise Process ◽  
The Central Limit Theorem ◽  
Cluster Point Process ◽  
Necessary And Sufficient ◽  
Poisson Cluster ◽  
Poisson Shot Noise

The Poisson shot-noise process discussed here takes the form f:oo H(t, s)N(ds), where N(· is the counting measure of a Poisson process and the H(·, s) are independent stochastic processes. Necessary and sufficient conditions are obtained for convergence in distribution, as t ∼ OC, to any infinitely divisible distribution. The main interest is in the explosive transient one-sided shot-noise, Y(t) = f:1 H(t, s)N(ds) where Var Y(t)∼ oc, Here conditions for asymptotic normality are discussed in detail. Important examples include the Poisson cluster point process and the integrated stationary shotnoise.

scholarly journals On the intensity of crossings by a shot noise process

1987 ◽  
Vol 19 (3) ◽  
pp. 743-745 ◽  
Author(s):  
Tailen Hsing
Keyword(s):  
Shot Noise ◽  
Marginal Probability ◽  
Noise Process ◽  
Shot Noise Process

The crossing intensity of a level by a shot noise process with a monotone response is studied, and it is shown that the intensity can be naturally expressed in terms of a marginal probability.

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