36,963 research outputs found
HetHetNets: Heterogeneous Traffic Distribution in Heterogeneous Wireless Cellular Networks
A recent approach in modeling and analysis of the supply and demand in
heterogeneous wireless cellular networks has been the use of two independent
Poisson point processes (PPPs) for the locations of base stations (BSs) and
user equipments (UEs). This popular approach has two major shortcomings. First,
although the PPP model may be a fitting one for the BS locations, it is less
adequate for the UE locations mainly due to the fact that the model is not
adjustable (tunable) to represent the severity of the heterogeneity
(non-uniformity) in the UE locations. Besides, the independence assumption
between the two PPPs does not capture the often-observed correlation between
the UE and BS locations.
This paper presents a novel heterogeneous spatial traffic modeling which
allows statistical adjustment. Simple and non-parameterized, yet sufficiently
accurate, measures for capturing the traffic characteristics in space are
introduced. Only two statistical parameters related to the UE distribution,
namely, the coefficient of variation (the normalized second-moment), of an
appropriately defined inter-UE distance measure, and correlation coefficient
(the normalized cross-moment) between UE and BS locations, are adjusted to
control the degree of heterogeneity and the bias towards the BS locations,
respectively. This model is used in heterogeneous wireless cellular networks
(HetNets) to demonstrate the impact of heterogeneous and BS-correlated traffic
on the network performance. This network is called HetHetNet since it has two
types of heterogeneity: heterogeneity in the infrastructure (supply), and
heterogeneity in the spatial traffic distribution (demand).Comment: JSA
Global Modeling and Prediction of Computer Network Traffic
We develop a probabilistic framework for global modeling of the traffic over
a computer network. This model integrates existing single-link (-flow) traffic
models with the routing over the network to capture the global traffic
behavior. It arises from a limit approximation of the traffic fluctuations as
the time--scale and the number of users sharing the network grow. The resulting
probability model is comprised of a Gaussian and/or a stable, infinite variance
components. They can be succinctly described and handled by certain
'space-time' random fields. The model is validated against simulated and real
data. It is then applied to predict traffic fluctuations over unobserved links
from a limited set of observed links. Further, applications to anomaly
detection and network management are briefly discussed
The pseudo-self-similar traffic model: application and validation
Since the early 1990¿s, a variety of studies has shown that network traffic, both for local- and wide-area networks, has self-similar properties. This led to new approaches in network traffic modelling because most traditional traffic approaches result in the underestimation of performance measures of interest. Instead of developing completely new traffic models, a number of researchers have proposed to adapt traditional traffic modelling approaches to incorporate aspects of self-similarity. The motivation for doing so is the hope to be able to reuse techniques and tools that have been developed in the past and with which experience has been gained. One such approach for a traffic model that incorporates aspects of self-similarity is the so-called pseudo self-similar traffic model. This model is appealing, as it is easy to understand and easily embedded in Markovian performance evaluation studies. In applying this model in a number of cases, we have perceived various problems which we initially thought were particular to these specific cases. However, we recently have been able to show that these problems are fundamental to the pseudo self-similar traffic model. In this paper we review the pseudo self-similar traffic model and discuss its fundamental shortcomings. As far as we know, this is the first paper that discusses these shortcomings formally. We also report on ongoing work to overcome some of these problems
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