Workload resampling for performance evaluation of parallel job schedulers
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Networking research would be well served by the adoption of a set of traffic benchmarks to model network applications for empirical evaluations; such benchmarks are common in many other areas of computing. While it has long been known that certain aspects of modeling traffic, such as round trip time, can dramatically affect application and network performance, there is still no agreement as to how such components should be controlled within an experiment. In this paper we advance the discussion of standards for empirical networking research by demonstrating how certain components of network traffic, such as the structure of application data exchanges within a TCP connection, can have a larger impact on the results obtained through experimentation than other dimensions of traffic such as round-trip time. Such findings point to the pressing need for traffic benchmarks in networking research. Through testbed experiments performed with synthetically generated network traffic from two very different traffic sources, and using several models of TCP connection structure, we demonstrate the strong effects of connection structure in traffic workload modeling on performance measures such as queue length at routers, number of active connections in the network, user response times, and connection durations.