Narrow Results

Nowadays, it is desirable to generate traffic which can reflect realistic network traffic environment for performance evaluation of network equipments. Existing traffic generation solutions mainly include special test equipments, software traffic generators and field programmable gate array (FPGA)-based traffic generators. However, special test equipments are generally too expensive, software traffic generators could not achieve high data rates and FPGA-based traffic generators mostly lack flexibility. This paper presents a novel traffic generation solution according to an aggregated process-based model to overcome the weakness of above methods. The traffic generator can generate real-time Poisson, two-state Markov-modulated Poisson process (MMPP-2) and self-similar traffic by hardware. The main structure of the traffic generator is presented and statistical properties of the generated traffic have been evaluated. Experiment results indicate that the proposed traffic generation solution can achieve better performance of the generated traffic compared with existing FPGA-based traffic generators while the required date rates can be up to Gbps line rate.

Among real-system applications of AI, the field of traffic simulation makes use of a wide range of techniques and algorithms. Especially, microscopic models of road traffic have been expanding for several years. Indeed, Multi-Agent Systems provide the capability of modeling the very diversity of individual behaviors. Several professional tools provide comprehensive sets of ready-made, accurate behaviors for several kinds of vehicles. The price in such tools is the difficulty to modify the nature of programmed behaviors, and the specialization in a single purpose, e.g. either studying resulting ows, or providing an immersive virtual reality environment. Thus, we advocate for a more exible approach for the design of multi-purpose tools for decision support. Especially, the use of geographical open databases offers the opportunity to design agent-based traffic simulators which can be continuously informed of changes in traffic conditions. Our proposal also makes decision support systems able to integrate environmental and behavioral modifications in a linear fashion, and to compare various scenarios built from different hypotheses in terms of actors, behaviors, environment and ows. We also describe here the prototype tool that has been implemented according to our design principles.