Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
High performance TCP in ANSNET
ACM SIGCOMM Computer Communication Review
Simulation-based comparisons of Tahoe, Reno and SACK TCP
ACM SIGCOMM Computer Communication Review
Experimentations with TCP selective acknowledgment
ACM SIGCOMM Computer Communication Review
Packet reordering is not pathological network behavior
IEEE/ACM Transactions on Networking (TON)
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Topology Discovery by Active Probing
SAINT-W '02 Proceedings of the 2002 Symposium on Applications and the Internet (SAINT) Workshops
ICNP '97 Proceedings of the 1997 International Conference on Network Protocols (ICNP '97)
Sampling large Internet topologies for simulation purposes
Computer Networks: The International Journal of Computer and Telecommunications Networking
Reducing large internet topologies for faster simulations
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
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Simulation has become the evaluation method of choice for many areas of computer networking research. When designing new or revised transport protocols, queuing methods, routing protocols, (just to name a few), a common approach is to create a simulation of a small to moderate scale topology and measure the performance of the new methodology as compared to existing methods. We demonstrate that simulation results using this approach can lead to very misleading, and even incorrect, results. The interaction between the large number of variables in these simulations can lead to results that vary widely from between different simulation topologies. We give empirical evidence showing different conclusions when the same comparisons are done using differing topologies. We argue the need for a standardized taxonomy of simulation topologies that capture a significant and realistic range of values for the various variables that impact the performance of a simulated network.