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.

Method simulating data traffic on network in accordance with a client/server paradigm

Abstract: A method for modeling traffic on a network according to a Client/Server paradigm is disclosed. The method includes the steps of exctracting the model parameters from known or measured interactions between a client node running a particular application and a server node with no other activity on the network. The method is repeated for each nodal configuration and for each application until the traffic for each node-application combination has, been modeled with no other load on the network. Scripts are created from the Paradigm parameters and are used in conjunction with a traffic generator to create discreet events mimicking the traffic which would be generated from each node. The model will insure that the traffic generated by each traffic source will be adjusted as a function of the response of the network under the load created by all of the traffic loading the network.

Self-similar traffic and network dynamics

Abstract: One of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it.

A stochastic model of traffic flow: Theoretical foundations

Abstract: In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.

Network testing systems

Abstract: A method of testing a digital mobile phone network such as a GPRS or 3 G network comprises creating test traffic using an unmodified test mobile phone coupled to a computer, and using the computer to measure a parameter associated with the network's response to the test traffic. The measurements made by the computer are encoded into the test traffic to create a data stream within the mobile phone network comprising test traffic, measurements relating to the test traffic, and signalling relating to the test traffic, whereby this data stream can be captured at points within the network and analysed to investigate the functioning of the network dynamically as the network is exercised with the test traffic. Software and test equipment for performing the method are also described.

RENAISSANCE – A Unified Macroscopic Model-Based Approach to Real-Time Freeway Network Traffic Surveillance

Abstract: The paper presents a unified macroscopic model-based approach to real-time freeway network traffic surveillance as well as a software tool RENAISSANCE that has been recently developed to implement this approach for field applications. RENAISSANCE is designed on the basis of stochastic macroscopic freeway network traffic flow modeling, extended Kalman filtering, and a number of traffic surveillance algorithms. Fed with a limited amount of real-time traffic measurements, RENAISSANCE enables a number of freeway network traffic surveillance tasks, including traffic state estimation and short-term traffic state prediction, travel time estimation and prediction, queue tail/head/length estimation and prediction, and incident alarm. The traffic state estimation and prediction lay the operating foundation of RENAISSANCE since RENAISSANCE bases the other traffic surveillance tasks on its traffic state estimation or prediction results. The paper first introduces the utilized stochastic macroscopic freeway network traffic flow model and a real-time traffic measurement model, upon which the complete dynamic system model of RENAISSANCE is established with special attention to the handling of some important model parameters. The algorithms for the various traffic surveillance tasks addressed are described along with the functional architecture of the tool. A simulation test was conducted via application of RENAISSANCE to a hypothetical freeway network example with a sparse detector configuration, and the testing results are presented in some detail. Final conclusions and future work are outlined.