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.

New development of optimal computing budget allocation for discrete event simulation

Abstract: This paper deals with ranking and selection problem via simulation. We present an optimal computing budget allocation technique which can select the bes t of k simulated designs. This approach can intelligently determine the best simulation lengths for all simulation experiments and significantly reduce the total computatio n cost to obtain the same confidence level. Numerical testing results are included. Also we provide the results of analysis for some parameters which affect the performance of our approach. Besides, we compare our method with traditional two-stage procedures. Numerical results show that our approach is much faster than the traditional two-stage procedures.

Investigation of network-level traffic flow relationships: some simulation results

Abstract: Results of an exploratory study of networklevel relationships in an isolated network with a fixed number of vehicles circulating according to the microscopic rules embedded in the NETSIM traffic simulation model are presented. The primary concern was to assess the usefulness of such simulation-based approaches in the investigation of macroscopic network-level traffic relationships. Three specific objectives were addressed: (a) identification of network-level descriptors that are related in operationally useful and simple ways, (b) exploration of some aspects of the two-fluid theory of town traffic, and (c) examination of the traffic flow distribution over the network components. A number of simulations were conducted on the same network under two different sets of control schemes and traffic characteristics at widely varying vehicle concentrations. The results were analyzed with respect to the three objectives, yielding useful insights into network-level traffic phenomena and suggesting promising avenues for further research.

A comparative analysis of web and peer-to-peer traffic

Abstract: Peer-to-Peer (P2P) applications continue to grow in popularity, and have reportedly overtaken Web applications as the single largest contributor to Internet traffic. Using traces collected from a large edge network, we conduct an extensive analysis of P2P traffic, compare P2P traffic with Web traffic, and discuss the implications of increased P2P traffic. In addition to studying the aggregate P2P traffic, we also analyze and compare the two main constituents of P2P traffic in our data, namely BitTorrent and Gnutella. The results presented in the paper may be used for generating synthetic workloads, gaining insights into the functioning of P2P applications, and developing network management strategies. For example, our results suggest that new models are necessary for Internet traffic. As a first step, we present flow-level distributional models for Web and P2P traffic that may be used in network simulation and emulation experiments.

A study of networks simulation efficiency: fluid simulation vs. packet-level simulation

Abstract: Network performance evaluation through traditional packet-level simulation is becoming increasingly difficult as today's networks grow in scale along many dimensions. As a consequence, fluid simulation has been proposed to cope with the size and complexity of such systems. This study focuses on analyzing and comparing the relative efficiencies of fluid simulation and packet-level simulation for several network scenarios. We use the "simulation event" rate to measure the computational effort of the simulators and show that this measure is both adequate and accurate. For some scenarios, we derive analytical results for the simulation event rate and identify the major factors that contribute to the simulation event rate. Among these factors, the "ripple effect" is very important since it can significantly increase the fluid simulation event rate. For a tandem queueing system, we identify the boundary condition to establish regions where one simulation paradigm is more efficient than the other. Flow aggregation is considered as a technique to reduce the impact of the "ripple effect" in fluid simulation. We also show that WFQ scheduling discipline can limit the "ripple effect", making fluid simulation particularly well suited for WFQ models. Our results show that tradeoffs between parameters of a network model determines the most efficient simulation approach.

Prediction of road traffic using a neural network approach

Abstract: A key component of the daily operation and planning activities of a traffic control centre is short-term forecasting, i.e. the prediction of daily to the next few days of traffic flow. Such forecasts have a significant impact on the optimal regulation of the road traffic on all kinds of freeways. They are increasingly important in an environment with increasing road traffic problems. The present paper aims at presenting the effectiveness of a neural network system for prediction based on time-series data. We only use one parameter, namely traffic volume for the forecasting. We employ artificial neural networks for traffic forecasting applied on a road section. Recurrent Jordan networks, popular in the modelling of time series, is examined in this study. Simulation results demonstrate that learning with this type of architecture has a good generalisation ability.