PACMNET, V2, CoNEXT3, September 2024 Editorial

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, creative use of networking technologies, and new insights made possible using analysis. The journal is strongly supported by the ACM Special Interest Group on Communications and Computer Networks (SIGCOMM) and involves top-level researchers in its Editorial Board.

This issue contains five articles that were originally submitted to the December'23 deadline, which received 82 submissions in total. Each submission underwent a rigorous review process involving more than 80 Editors coordinated by the two Associate Editors. In the first phase of the review process, each article received at least three reviews. After an online discussion phase, about half of the articles were rejected, and half were promoted to the second review phase. There, the Editors provided at least two additional reviews for each article. After a second discussion phase, the Editors selected seven long articles for a ''one-shot'' resubmission in June'24. The revised papers were then reviewed again by the same editors, resulting in five accepted papers.

This issue covers topics related to computer networks and their applications: two articles focus on network analytics, one article focuses on packet processing, one article focuses on network trace generation, and one article focuses on IP geolocation.

We want to thank the many individuals who contributed to this issue of PACMNET, in particular the authors, who submitted their best work to PACMNET, and the Associate Editors, who provided constructive feedback to the authors in their reviews and participated in the discussions. We would also like to thank the SIGCOMM Executive Committee Chair and the CoNEXT Steering Committee members who supported and guided us as usual, giving important suggestions and insights during the article selection process.