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Linux-like Socket Statistics Utility for ns-3

Published:28 June 2023Publication History

ABSTRACT

Collecting statistics in network experiments is crucial for understanding the behavior of the network protocols and identifying any anomalies or performance issues. Without accurate and comprehensive statistics, it is difficult to analyze network traffic, identify bottlenecks, and make informed decisions about network protocol improvements. One of the key features of ns-3 is its ability to collect detailed statistics about network behavior during simulations. It supports various modules to collect statistics, such as Flow Monitor to collect flow level statistics, trace sources to collect information about specific events that occur during simulation, packet captures (PCAP) that can be read and analyzed using various PCAP-compatible tools and ASCII traces for debugging and generating custom reports. Besides, ns-3 also provides a flexible and extensible framework for users to create their own custom statistics collection modules. Nevertheless, collecting and analyzing data from simulations using these tools can be a complex process and requires a good understanding of the ns-3 simulation framework and its internal data structures. This paper discusses the design and development of a Linux-like socket statistics (ss) utility for ns-3 which makes the task of gathering network statistics much simpler. The main objective of this work is to develop a user-friendly API that enables ns-3 users to easily generate socket statistics. We validate the proposed API by comparing the results obtained from the trace sources already present in ns-3, and observe a high degree of consistency between our API and the trace source results. In addition, we analyze the impact of the proposed API on ns-3 performance in terms of resource consumption.

References

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      cover image ACM Other conferences
      WNS3 '23: Proceedings of the 2023 Workshop on ns-3
      June 2023
      134 pages
      ISBN:9798400707476
      DOI:10.1145/3592149

      Copyright © 2023 ACM

      Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 June 2023

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