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Volume 2, Issue CoNEXT3September 2024PACMNETCurrent Issue
Reflects downloads up to 04 Oct 2024Bibliometrics
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editorial
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PACMNET, V2, CoNEXT3, September 2024 Editorial
Article No.: 12, Page 1https://doi.org/10.1145/3676859

The Proceedings of the ACM on Networking (PACMNET) series present the highest-quality research conducted in the areas of emerging computer networks and their applications. We encourage submissions that present new technologies, novel experimentation, ...

research-article
Open Access
FAJITA: Stateful Packet Processing at 100 Million pps
Article No.: 14, Pages 1–22https://doi.org/10.1145/3676861

Data centers increasingly utilize commodity servers to deploy low-latency Network Functions (NFs). However, the emergence of multi-hundred-gigabit-per-second network interface cards (NICs) has drastically increased the performance expected from commodity ...

research-article
Geofeeds: Revolutionizing IP Geolocation or Illusionary Promises?
Article No.: 15, Pages 1–21https://doi.org/10.1145/3676869

Despite more than twenty years of efforts, the research community is still looking for a publicly available Internet-scale IP geolocation dataset with an explainable methodology. Recently, a new hope has appeared, with the emergence of geofeeds. Geofeeds ...

research-article
NetDiff: A Service-Guided Hierarchical Diffusion Model for Network Flow Trace Generation
Article No.: 16, Pages 1–21https://doi.org/10.1145/3676870

Network flow traces are fundamental to many network management workflows. In this paper, we aim to generate high-fidelity network flow traces by explicitly modeling users' dynamic network usage intents. We propose NetDiff, a service-guided hierarchical ...

research-article
RecenTo: Finding Top-K Flows of the Recent Past
Article No.: 17, Pages 1–20https://doi.org/10.1145/3676871

Recent advances in programmable networks enable network operators to perform fine-grained analysis on all of the traffic as it traverses the network. One of the most common tasks, that has been widely studied, is to find the heavy hitter flows or the top-...

research-article
Open Access
SQUID: Faster Analytics via Sampled Quantile Estimation
Article No.: 19, Pages 1–23https://doi.org/10.1145/3676873

Streaming algorithms are fundamental in the analysis of large and online datasets. A key component of many such analytic tasks is q-MAX, which finds the largest q values in a number stream. Modern approaches attain a constant runtime by removing small ...

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