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A testbed capable of representing detailed operations of complex applications under diverse network conditions is invaluable for understanding the design and performance of new protocols and applications before their real deployment. We introduce a novel method that combines high-performance large-scale network simulation and high-fidelity network emulation, and thus enables real instances of network applications and protocols to run in real operating environments and be tested under simulated network settings. Using our approach, network simulation and emulation can form a symbiotic relationship, through which they are synchronized for an accurate representation of the network-scale traffic behavior. We introduce a model downscaling method along with an efficient queuing model and a traffic reproduction technique, which can significantly reduce the synchronization overhead and improve accuracy. We validate our approach with extensive experiments via simulation and with a real-system implementation. We also present a case study using our approach to evaluate a multipath data transport protocol.

A testbed capable of representing detailed operations of complex applications under diverse large-scale network conditions can be extremely helpful for investigating potential system design and implementation problems, and studying application performance issues, such as scalability and robustness, even before the applications are deployed in a real environment. We introduce a novel method that combines high-performance large-scale network simulation and high-fidelity network emulation, and thereby enables real instances of network applications and protocols to run in real operating environments, and be tested under large-scale simulated network settings. In our approach, network simulation and emulation form a symbiotic relationship, through which they are synchronized for an accurate representation of the large-scale traffic behavior. We introduce a model downscaling method, along with an efficient queuing model and a traffic reproduction technique, which can significantly reduce the synchronization overhead and improve computational efficiency, while maintaining the accuracy of the system. We validate our approach with extensive experiments via simulation and with a real-system prototype.

Small-scale experiments are insufficient for a comprehensive study of congestion control protocols. Similarly, results obtained from pure simulation platforms without exercising real protocols and applications lack realism. Motivated by these reasons, we developed SVEET, a TCP performance evaluation testbed where real implementations of TCP variants can be accurately evaluated under diverse network configurations and workloads from real applications in large-scale network settings. It is our purpose to provide the research community a standard environment through which quantitative assessment regarding TCP behavior can be drawn from large-scale experiments. In order to accomplish our goal, we adopted a novel model-driven emulation approach combining real-time simulation, machine and time virtualization techniques. We validate the testbed via extensive experiments to assess its potentials and limitations. Additionally, we performed case studies involving real web, streaming, and peer-to-peer applications. Our results indicate that SVEET can accurately model the behavior of the TCP variants and support large-scale network scenarios.