A Storage Process with Local Time Input

In this paper we introduce a storage process with singular continuous input. The input process is defined as the local time of a stationary reflecting Brownian motion with drift. Many basic charateristics of the process are computed explicitly, e.g., stationary distribution, distributions of the starting and ending time of on-going busy and idle periods. We also consider the multifractal spectrum of the input process and observe that it is independent of system parameters.     

Fluid queue driven by anM/M/1 queue

A fluid queue receiving its input from the output of a precedingM/M/1 queue is considered. The input can be characterized as a Markov modulated rate process and the well known spectral decomposition technique can be applied. The novel features in this system relate to the nature of the spectrum, which is shown to be composed of a continuous part and one or two discrete points depending on whether the load of the fluid queue is less or greater than the output to input rate ratio. Explicit expressions of the generalized eigenvectors are given in terms of Chebyshev polynomials of the second kind, and the resolution of unity is determined. The solution for the buffer content distribution is obtained as a simple integral expression. Numerical examples are given.     

On the stability of two-chunk file-sharing systems

We consider five different peer-to-peer file-sharing systems with two chunks, assuming non-altruistic peers who leave the system immediately after downloading the second chunk. Our aim is to find chunk selection algorithms that have provably stable performance with any input rate. We show that many algorithms that first looked promising lead to unstable or oscillating behaviour. However, we end up with a system with desirable properties. Most of our rigorous results concern the corresponding deterministic large system limits, but in the two simplest cases we provide proofs for the stochastic systems also.     

Local independence of fractional Brownian motion

Let _σ(t,t′)${\sigma }_{(t,t^{\prime })}$ be the sigma-algebra generated by the differences _Xs−_Xs′$X_s-X_{s^{\prime }}$ with s,s^′∈(t,t^′)$s,s^{\prime }\in (t,t^{\prime })$, where _{(Xt)−∞<t<∞}${\left(X_t\right)}_{-\infty <t<\infty }$ is the fractional Brownian motion with Hurst index H∈(0,1)$H\in (0,1)$. We prove that for any two distinct timepoints _t1$t_1$ and _t2$t_2$ the sigma-algebras _{σ(t1−ε,t1+ε)}${\sigma }_{(t_1-\epsilon ,t_1+\epsilon )}$ and _{σ(t2−ε,t2+ε)}${\sigma }_{(t_2-\epsilon ,t_2+\epsilon )}$ are asymptotically independent as ε↘0$\epsilon \searrow 0$. We show the independence in the strong sense that Shannon’s mutual information between the two σ$\sigma$-algebras tends to zero as ε↘0$\epsilon \searrow 0$. Some generalizations and quantitative estimates are also provided.     

Filtering the histories of a partially observed marked point process

We consider a situation in which the evolution of an ‘underlying’ marked point process is of interest, but where this process is not directly observable. Instead, we assume that another marked point process, which is fully determined by the underlying process, can be observed. The problem is then the estimation, at any given time t, of the underlying development so far, given the corresponding observations. The solution, in the sense of a conditional distribution of the underlying pre-t history, is shown to satisfy a recursive filter formula. Sufficient conditions for the uniqueness of the solution are given. Two non-trivial examples are considered in detail.     

On Busy Periods of the Unbounded Brownian Storage

A stationary storage process with Brownian input and constant service rate is studied. Explicit formulae for quantities related to busy periods (excursions) are derived. In particular, we compute the distributions of the occupation times the process spends above and below, respectively, the present level during the on-going busy period, and make the surprising observation that these occupation times are identically distributed.     

Large deviations of infinite intersections of events in Gaussian processes

Consider events of the form {_Zs≥ζ(s),s∈S}$\{Z_s\ge \zeta \left(s\right),s\in S\}$, where Z$Z$ is a continuous Gaussian process with stationary increments, ζ$\zeta$ is a function that belongs to the reproducing kernel Hilbert space R$R$ of process Z$Z$, and S⊂R$S\subset \mathbb{R}$ is compact. The main problem considered in this paper is identifying the function β^∗∈R${\beta }^{\ast }\in R$ satisfying β^∗(s)≥ζ(s)${\beta }^{\ast }\left(s\right)\ge \zeta \left(s\right)$ on S$S$ and having minimal R$R$-norm. The smoothness (mean square differentiability) of Z$Z$ turns out to have a crucial impact on the structure of the solution. As examples, we obtain the explicit solutions when ζ(s)=s$\zeta \left(s\right)=s$ for s∈[0,1]$s\in [0,1]$ and Z$Z$ is either a fractional Brownian motion or an integrated Ornstein–Uhlenbeck process.     

Systems weakend by failures

The ideas of a dynamic approach to the analysis of multivariate life length distributions, introduced in Arjas (1981a) and Arjas and Norros (1984), are developed further. Basic definitions are given in terms of prediction processes. Properties of martingales jumping downwards at failure times are studied. Finally, the spaecial case of a general multivariate exponential distribution is considered.     

A storage model with self-similar input

A storage model with self-similar input process is studied. A relation coupling together the storage requirement, the achievable utilization and the output rate is derived. A lower bound for the complementary distribution function of the storage level is given.