2014•Journal of Theoretical and Applied Information TechnologyRequires access

Generation of real world traffic using ns2 traffic agents

Sami Abbas Nagar, Sulaiman Mohd Nor, Mohamed Saad Boba

Open publisher page 3 citations

Abstract

There has been substantial interest from researchers in the development and contribution of modules in NS2. One of the challenges in NS2 modeling is to seamlessly integrate real world traffic data into the NS2 network model. Normally the traffic in NS2 is generated from the traffic agents such as TCP and UDP agents whose parameters are based on certain statistical distribution. The aim of this paper is to demonstrate how traffic agents in NS2 simulator are used to generate different types of traffic based on real traffic network. In this work, a modified sniffer program was used to capture real traffic data from a production network and output to a traffic text file. This traffic test file is then used by the NS2 traffic agents in the simulated network model representing the real production network. To validate that the simulation works accurately, the output trace file of NS2 after simulation is compared with the traffic generated at the destinations of the production network. Error percentage and t-test data analyses were conducted. It was found, based on comparisons that the difference was nearly zero for traffic captured for duration of around 15 minutes simultaneously generated from four different production sites.

About this research paper

What this paper is about

There has been substantial interest from researchers in the development and contribution of modules in NS2. One of the challenges in NS2 modeling is to seamlessly integrate real world traffic data into the NS2 network model. Normally the traffic in NS2 is generated from the traffic agents such as TCP and UDP agents whose parameters are based on certain statistical distribution. The aim of this paper is to demonstrate how traffic agents in NS2 simulator are used to generate different types of traffic based on real traffic network. In this work, a modified sniffer program was used to capture real traffic data from a production network and output to a traffic text file. This traffic test file is then used by the NS2 traffic agents in the simulated network model representing the real production network. To validate that the simulation works accurately, the output trace file of NS2 after simulation is compared with the traffic generated at the destinations of the production network. Error percentage and t-test data analyses were conducted. It was found, based on comparisons that the difference was nearly zero for traffic captured for duration of around 15 minutes simultaneously generated from four different production sites.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

There has been substantial interest from researchers in the development and contribution of modules in NS2. One of the challenges in NS2 modeling is to seamlessly integrate real world traffic data into the NS2 network model. Normally the traffic in NS2 is generated from the traffic agents such as TCP and UDP agents whose parameters are based on certain statistical distribution. The aim of this paper is to demonstrate how traffic agents in NS2 simulator are used to generate different types of traffic based on real traffic network. In this work, a modified sniffer program was used to capture real traffic data from a production network and output to a traffic text file. This traffic test file is then used by the NS2 traffic agents in the simulated network model representing the real production network. To validate that the simulation works accurately, the output trace file of NS2 after simulation is compared with the traffic generated at the destinations of the production network. Error percentage and t-test data analyses were conducted. It was found, based on comparisons that the difference was nearly zero for traffic captured for duration of around 15 minutes simultaneously generated from four different production sites.

Key concepts: Traffic generation model, Computer science, Network traffic simulation, Floating car data, Network traffic control, Real-time computing, Simulation, Computer network

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