Application of sampling methodologies to network traffic characterization
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
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IEEE/ACM Transactions on Networking (TON)
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IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
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SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Data networks as cascades: investigating the multifractal nature of Internet WAN traffic
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
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Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
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Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
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Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
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MASCOTS '00 Proceedings of the 8th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
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ACM SIGCOMM Computer Communication Review
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NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
DNCOCO'09 Proceedings of the 8th WSEAS international conference on Data networks, communications, computers
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PADS '11 Proceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation
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Performance Evaluation
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Proceedings of the 4th Asia-Pacific Workshop on Systems
Flow-based partitioning of network testbed experiments
Computer Networks: The International Journal of Computer and Telecommunications Networking
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As the Internet grows, it is becoming increasingly difficult to collect performance measurements, to monitor its state, and to perform simulations efficiently. This is because the size and the heterogeneity of the Internet makes it time-consuming and difficult to devise traffic models and analytic tools which would allow us to work with summary statistics.We explore a method to side step these problems by combining sampling, modeling, and simulation. Our hypothesis is this: if we take a sample of the input traffic and feed it into a suitably scaled version of the system, we can extrapolate from the performance of the scaled system to that of the original.Our main findings are as follows. When we scale an IP network which is shared by short- and long-lived TCP-like and UDP flows and which is controlled by a variety of active queue management schemes, then performance measures such as queueing delay and drop probability are left virtually unchanged. We show this in theory and in simulations. This makes it possible to capture the performance of large networks quite faithfully using smaller scale replicas.