2015Unpublished venueRequires access

Expressing Different Traffic Models Using the LegoTG Framework

Genevieve Bartlett, Jelena Mirković

Open publisher page 3 citations

Abstract

In this paper we demonstrate the ease of generating and modifying background traffic in testbed experiments through the traffic generation framework we developed, called LegoTG. LegoTG is a modular framework for composing custom traffic generation. It makes it easy to combine different traffic generators and traffic modulators (e.g., Delay models), and to port the same background traffic to different topologies. In addition to the framework, we have developed several traffic generation/modulation tools that can be used in LegoTG to generate realistic and highly controllable network and transport-level traffic. We build our demonstration around a series of simple experiments which reinforce how much background traffic matters in experiments and how different traffic models can drastically affect experiment results and research conclusions.

About this research paper

What this paper is about

In this paper we demonstrate the ease of generating and modifying background traffic in testbed experiments through the traffic generation framework we developed, called LegoTG. LegoTG is a modular framework for composing custom traffic generation. It makes it easy to combine different traffic generators and traffic modulators (e.g., Delay models), and to port the same background traffic to different topologies. In addition to the framework, we have developed several traffic generation/modulation tools that can be used in LegoTG to generate realistic and highly controllable network and transport-level traffic. We build our demonstration around a series of simple experiments which reinforce how much background traffic matters in experiments and how different traffic models can drastically affect experiment results and research conclusions.

Why it matters

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

Key contribution

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Method / approach

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Available abstract

In this paper we demonstrate the ease of generating and modifying background traffic in testbed experiments through the traffic generation framework we developed, called LegoTG. LegoTG is a modular framework for composing custom traffic generation. It makes it easy to combine different traffic generators and traffic modulators (e.g., Delay models), and to port the same background traffic to different topologies. In addition to the framework, we have developed several traffic generation/modulation tools that can be used in LegoTG to generate realistic and highly controllable network and transport-level traffic. We build our demonstration around a series of simple experiments which reinforce how much background traffic matters in experiments and how different traffic models can drastically affect experiment results and research conclusions.

Key concepts: Traffic generation model, Testbed, Computer science, Modular design, Network topology, Traffic shaping, Floating car data, Network traffic simulation

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