Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
The scientist and engineer's guide to digital signal processing
The scientist and engineer's guide to digital signal processing
Essential COM
An integrated framework for enabling effective data collection and statistical analysis with ns-2
WNS2 '06 Proceeding from the 2006 workshop on ns-2: the IP network simulator
XAV: a fast and flexible tracing framework for network simulation
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
A performance comparison of recent network simulators
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
On modeling and simulation of game theory-based defense mechanisms against DoS and DDoS attacks
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Transparent and scalable terminal mobility for vehicular networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Optimal multipath forwarding in planned Wireless Mesh Networks
Computer Communications
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When networking researchers meet the task of doing simulations, there is always a need to evaluate the value of such models by measuring a set of well known network performance metrics. However, simulators in general and NS-3 in particular, require significant programming effort from the researcher in order to collect those metrics. This paper reports a contribution for NS-3 consisting of a new flow monitoring module that makes it easier to collect and save to persistent storage a common set of network performance metrics. The module automatically detects all flows passing through the network and stores in a file most of the metrics that a researcher might need to analyze about the flow, such as bitrates, duration, delays, packet sizes, and packet loss ratio. The value of this module is demonstrated using an easy to follow example. It is also validated by comparing the measurements of a simple scenario with the expected values. Finally, the performance of flow monitoring is characterized and shown to introduce small overheads.