Study On The Methods To Improve The Performance Of Large-Scale Discrete Event Network Simulation

Simulation is a key method to do research on network behavior and to analyze network protocols, and it is of great value in science research and application. With the rapid development of computer networks, the scale of network for simulation grows larger and larger, yet the computation overhead of the large-scale discrete event network simulation can hardly be satisfied. How to reduce the running time of large-scale network simulation, that is, how to improve the simulation performance, so as to make it possible to simulate a network with a scale of million-node fastly, or even to simulate the Internet, is a most challenging problem. So, this paper is dedicated to this problem.Taking large-scale discrete event network simulation as the research object, this dissertation analyzes various factors that may affect the performance of network simulation, and investigates solutions to improve the performance of network simulation. This paper is mainly composed of the following five parts:First, to investigate how to improve performance of network simulation, various factors, including load balancing, communication overhead, lookahead, simulation running platform, and the application to be simulated etc., are analyzed, and based on these factors, a model for estimating the performance of parallel network simulation is developed. Compared to the traditional estimating models, this model can give guidance to how to improve the performance of network simulation. Through analysis of those various factors and establishment of the estimating model, the actual methods on how to improve the performance of network simulation are put forward, which are the basis of the following research work.Second, as there are shortcomings, such as convergence to local minima and unreasonable patitioning result, of the current parallel network simulation partitioning methods which are based on topology graph partitioning tools, a method for optimized partitioning for parallel network simulation topology is developed. In this optimized partitioning method, the network topology for simulation is partitioned by the improved simulated annealing, and the model for estimating the performance of parallel network simulation is treated as the object function. Depending on the simulated annealing, the partitioning result does not tend to converge to local minima, and depending on the estimating model, the partitioning method can take various factors that may affect the performance of network simulation into consideration, and partition the simulation task reasonably, so this method can improve the performance of parallel network simulation efficiently.Third, as during the procedure of large-scale discrete event network simulation, much computation overhead is needed to deal with a great lot of packet transmissions, a fast discrete event network simulation method based on dynamic continuous computing is put forward. In this method, the simulation of packet transmission is depicted by continuous computing in order to reduce the overhead generated by the discontinuity of the simulation of packet transmission in the traditional network simulation. The inaacuracy of the continuous computing is analysed, and to keep the accuracy, the dynamic continuous computing method, which means to process the packet transmissions with continuous computing dynamically and selectively, is put forward.Fourth, to reduce the simulation overhead of background traffic which is generated by the traffic generator, a simplified background traffic simulation method based on packet sampling is developed. When generating the background traffic, the method only generate part of the packets in the original background traffic by sampling; In the congested links, all the packets in the original background traffic are recovered according to these few packets; Depending on these recoverd packets, the buffers of the routers and the foreground traffics are simulated. Expriments show that this method can improve the performance of background traffic simulation, while keeping the accuracy of simulation result.Fifth, combining the topology generating module of network simulation, the configuration module of remote route, the script generating module of simulation application, and the studies metioned above, a parallel network simulation application platform is developed. The application platform is of high performance and convenience. At last, the procedure of how to use the platform is demonstrated through an example of large-scale parallel network simulation.