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.

On Global Modeling of Backbone Network Traffic

Abstract: We develop a probabilistic framework for global modeling of the traffic over a computer network. The 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 real data and applied to predict traffic fluctuations over unobserved links from a limited set of observed links.

Dynamic Simulation-Assignment Model (DynaTAIWAN) under Mixed Traffic Flows for ITS Applications

Abstract: This research aims at developing an integrated dynamic simulation-assignment model, DynaTAIWAN under mixed traffic flow conditions, for Advanced Traffic Management Systems as well as Advanced Traveler Information Systems. The model is composed of two layers, namely simulation-layer and real-time control layer. The simulation layer is designed to simulate traffic flow patterns according to assumed tripmaker characteristics and/or under a set of given conditions; the real-time control layer receives real-time vehicle information and forecast short-term traffic flow patterns. In this paper, the simulation layer is discussed in detail and numerical experiments are conducted to illustrate functional capabilities of the proposed model. In the simulation process, each vehicle is moved and tracked individually. Four different vehicle types are explicitly considered in DynaTAIWAN, including car, bus, motorcycle, and truck. Vehicles are moving along the link through macroscopic flow relationships, speeds of each type of vehicle are adjusted. Numerical experiments are conducted in a 50-node test network and a Taichung City Network.

Methods, apparatus, and systems for simulation of mixed traffic in a wireless network

Abstract: Methods, apparatus, and systems are provided to simulate a network carrying a heterogeneous mix of traffic in order to assess the performance of the network. Parameters and information are provided to define the configuration of the network and define how resources in the network are shared between types of traffic for a simulation run. In addition, sets of parameters define characteristics for individual types of traffic. During a simulation run, the individual types of traffic are generated with the defined characteristics using one or more models. The individual types of traffic are then aggregated to generate a joint, heterogeneous mix of traffic. As the mix of traffic is generated, resources in the network are allocated. Statistics are then collected for each simulation run to indicate the performance of the simulated network when loaded with the heterogeneous mix of traffic.

Characterising Distributed Haptic Virtual Environment Network Traffic Flows

Abstract: The effective transmission of haptic data in Distributed Haptic Virtual Environment (DHVEs) is a new research area which presents a number of challenges to the underlying network. The transmission of reflected force in these applications has the potential to change the way humans interact with machines and communicate with each other. The future Internet will have to carry multiple DHVE type traffic and it is now established that the best effort service offered by current IP networks is insufficient to meet the needs of these type of applications, which require specific Quality of Service (QoS) from network. The aim of the work presented here is to characterise the traffic generated by multiple DHVE network connections. The approach taken is to develop a simulation model of DHVE traffic based on empirical measurements. Both synchronous and asynchronous real world DHVE traffic is analyzed, quantified and imported into a network simulation. Probability Density Function (PDF) models are subsequently derived for each type of traffic in the DHVE system. The results show the network simulation model compares favourably with the physical network, and can be used to generate a scalable haptic network model where multiple DHVE connections may be examined.

Dynamic network traffic analysis and traffic flow configuration for radio networks

Abstract: A system may receive, from a base station, information indicating that a network congestion level associated with the base station satisfies a threshold, the network congestion level being a measurement of traffic associated with a network, and the network including the base station The system may determine, based on the network congestion level satisfying the threshold, traffic flow information for a plurality of traffic flows associated with the base station The system may identify a congestion-causing traffic flow, of the plurality of traffic flows, based on the traffic flow information The system may provide information identifying the congestion-causing traffic flow