@inproceedings{243895f0a80c419ab4db750f147acc6a,
title = "Poster: Empirically Testing the PacketLab Model",
abstract = "PacketLab is a recently proposed model for accessing remote vantage points. The core design is for the vantage points to export low-level network operations that measurement researchers could rely on to construct more complex measurements. Motivating the model is the assumption that such an approach can overcome persistent challenges such as the operational cost and security concerns of vantage point sharing that researchers face in launching distributed active Internet measurement experiments. However, the limitations imposed by the core design merit a deeper analysis of the applicability of such model to real-world measurements of interest. We undertook this analysis based on a survey of recent Internet measurement studies, followed by an empirical comparison of PacketLab-based versus native implementations of common measurement methods. We showed that for several canonical measurement types common in past studies, PacketLab yielded similar results to native versions of the same measurements. Our results suggest that PacketLab could help reproduce or extend around 16.4% (28 out of 171) of all surveyed studies and accommodate a variety of measurements from latency, throughput, network path, to non-timing data.",
keywords = "packetlab, poster",
author = "Yan, {Tzu Bin} and Zesen Zhang and Bradley Huffaker and Ricky Mok and Kc Claffy and Kirill Levchenko",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 23rd ACM Internet Measurement Conference, IMC 2023 ; Conference date: 24-10-2023 Through 26-10-2023",
year = "2023",
month = oct,
day = "24",
doi = "10.1145/3618257.3624999",
language = "English (US)",
series = "Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC",
publisher = "Association for Computing Machinery",
pages = "724--725",
booktitle = "IMC 2023 - Proceedings of the 2023 ACM on Internet Measurement Conference",
address = "United States",
}