Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Network simulations with OPNET
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Self-configuring network traffic generation
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Tmix: a tool for generating realistic TCP application workloads in ns-2
ACM SIGCOMM Computer Communication Review
Realistic and responsive network traffic generation
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Network Algorithmics,: An Interdisciplinary Approach to Designing Fast Networked Devices (The Morgan Kaufmann Series in Networking)
Observed structure of addresses in IP traffic
IEEE/ACM Transactions on Networking (TON)
Monkey see, monkey do: a tool for TCP tracing and replaying
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
An application-level content generative model for network applications
Proceedings of the 5th International ICST Conference on Simulation Tools and Techniques
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Network simulation and emulation environments play a crucial role in evaluating proposed protocols, applications, and networked systems. In such settings, the ability to scalably and efficiently generate traffic that has characteristics similar to those measured in the live Internet is of great importance. A key aspect of generating realistic traffic is to assign source and destination IP addresses to traffic flows such that the statistical structure of the addresses is similar to what would be seen in a live Internet setting. In this paper, we propose and evaluate an algorithm and data structure for efficient and realistic generation of IP addresses. We describe our new method and compare it with existing and prior work, while also showing that our technique is far more efficient --- both in terms of memory consumed and computation time required. We also show that the statistical structure of the generated addresses is similar to what would be measured in the live Internet. Our results show that it is possible to efficiently generate addresses over the entire IPv4 address space, and that it is feasible to generate addresses from a/64 IPv6 subnet.