Michel Mandjes

  1. Flow-level models for multipath routing.

    Authors: Michel Mandjes, Sarah Lilienthal
    Subjects: Optimization and Control
    Abstract

    In this paper we study coordinated multipath routing at the flow-level in
    networks with routes of length one. As a first step the static case is
    considered, in which the number of flows is fixed. A clustering pattern in the
    rate allocation is identified, and we describe a finite algorithm to find this
    rate allocation and the clustering explicitly. Then we consider the dynamic
    model, in which there are stochastic arrivals and departures; we do so for
    models with both streaming and elastic traffic, and where a peak-rate is
    imposed on the elastic flows (to be thought of as an access rate).

  2. On convergence to stationarity of fractional Brownian storage.

    Authors: Michel Mandjes, Ilkka Norros, Peter Glynn
    Subjects: Probability
    Abstract

    With $M(t):=\sup_{s\in[0,t]}A(s)-s$ denoting the running maximum of a
    fractional Brownian motion $A(\cdot)$ with negative drift, this paper studies
    the rate of convergence of $\mathbb {P}(M(t)>x)$ to $\mathbb{P}(M>x)$. We
    define two metrics that measure the distance between the (complementary)
    distribution functions $\mathbb{P}(M(t)>\cdot)$ and $\mathbb{P}(M>\cdot)$.

  3. On convergence to stationarity of fractional Brownian storage.

    Authors: Michel Mandjes, Ilkka Norros, Peter Glynn
    Subjects: Probability
    Abstract

    With $M(t):=\sup_{s\in[0,t]}A(s)-s$ denoting the running maximum of a
    fractional Brownian motion $A(\cdot)$ with negative drift, this paper studies
    the rate of convergence of $\mathbb {P}(M(t)>x)$ to $\mathbb{P}(M>x)$. We
    define two metrics that measure the distance between the (complementary)
    distribution functions $\mathbb{P}(M(t)>\cdot)$ and $\mathbb{P}(M>\cdot)$.

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