Modeling teletraffic arrivals by a Poisson cluster process

Modeling teletraffic arrivals by a Poisson cluster process

In this paper we consider a Poisson cluster process N as a generating process for the arrivals of packets to a server. This process generalizes in a more realistic way the infinite source Poisson model which has been used for modeling teletraffic for a long time. At each Poisson point Γj , a flow of packets is initiated which is modeled as a partial iid sum process Γj + Pk i=1 Xji, k ≤ Kj , wit...

Poisson Cluster process as a model for teletraffic arrivals and its extremes

Poisson-Poisson Cluster SINR Coverage Process

In [1], a new coverage process was defined. It was motivated by the various SINR(Signal to Interference Noise Ratio) models in wireless communications. The underlying point process was assumed to be a Poisson process. In this report, we extend the theory to the case when the underlying point process is a Poisson-Poisson cluster process. Firstly, we define the stochastic geometric model. We give...

Modeling network traffic by a cluster Poisson input process with heavy and light-tailed file sizes

We consider a cluster Poisson model with heavy-tailed interarrival times and cluster sizes as a generalization of an infinite source Poisson model where the file sizes have a regularly varying tail distribution function or a finite second moment. One result is that this model reflects long range dependence of teletraffic data. We show that depending on the heaviness of the file sizes, the inter...

Computer Networks Modeling arrivals and service with Poisson

In computer networks, packet arrivals and service are modeled as a stochastic process in which events occur at times t1, t2, . . . For instance, in the figure below, t1, t2, . . . can be interpreted as the packet arrival times, or the service completion times. Accordingly, Ti, defined as ti−ti−1 for i > 1, can be interpreted as the inter-arrival times of packets (intervals between subsequent ar...