Network traffic simulation

About: Network traffic simulation is a research topic. Over the lifetime, 4535 publications have been published within this topic receiving 74606 citations.

A weighted network evolution with traffic flow

Abstract: In this paper, we propose a simple weighted network model that generalizes the complex network model evolution with traffic flow previously presented to investigate the relationship between traffic flow and network structure. In the model, the nodes in the network are represented by the traffic flow states, the links in the network are represented by the transform of the traffic flow states, and the traffic flow transported when performing the transform of the traffic flow states is considered as the weight of the link. Several topological features of this generalized weighted model, such as the degree distribution and strength distribution, have been numerically studied. A scaling behavior between the strength and degree s ∼ k log k is obtained. By introducing some constraints to the generalized weighted model, we study its subnetworks and find that the scaling behavior between the strength and degree is conserved, though the topology properties are quite sensitive to the constraints.

Detecting attack signatures in the real network traffic with ANNIDA

Abstract: In this paper, an improved version of ANNIDA for detecting attack signatures in the payload of network packets is presented. The Hamming Net artificial neural network methodology was used with good results. A review of the application's development is followed by a summary of the modifications made in the application in order to classify real data. Application improvements are reported, solving the problems of time delays in writing/reading data in the files and data collision effects when generating numeric keys used to model data for the neural network. Test results highlight the increased accuracy and efficiency of the new application when submitted to real data from HTTP network traffic containing actual traces of attacks and legitimate data. Finally, an evaluation of the application to detect signatures in real network traffic data is presented.

Traffic flow forecasting

Abstract: This paper presents a review of methods used to perform dynamic traffic forecasting. New models for tracing and forecasting of congested spatial-temporal patterns on highways are examined. These include ASDA (automatic tracing of moving traffic jams) and FOTO (Forecasting of traffic objects). The advantage of these models is that they allow for the tracing and prediction of macroscopic spatial-temporal properties of traffic patterns without any validation of model parameters at different conditions. In addition, a macroscopic model for dynamic traffic forecasting in urban areas is described. The model, which allows for the prediction of macroscopic characteristics of traffic (such as queue lengths at traffic signals and link travel times), is shown to have a calculation time that can be several thousand times shorter than that of a microscopic traffic model.

Traffic engineering experience from operating cellular networks

Abstract: Modeling of user traffic and the mobility impact of mobile users onto cellular networks is considered. The quality of service and traffic-handling capacity offered by the network play the most important roles. This article discusses the requirements on a traffic model and on performance design objectives which can be used as a basis for designing and engineering cellular networks. Requirements from actual network operation are discussed and are illustrated by measurement results.

Methods and systems for network traffic forecast and analysis

Abstract: A computer-implemented method and system are provided for forecasting traffic load on a communications network driven by market factors.