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Proceedings of the ACM on Networking is a peer-reviewed journal published by ACM, covering Software-Defined Networks and 5G, Network Traffic and Congestion Control, Network Security and Intrusion Detection. Over its lifetime it has published 143 papers, which have received 508 citations.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. Proceedings of the ACM on Networking 12, 3, Article 45 (2023).
Formats any DOI in Proceedings of the ACM on Networking style. No sign-up. |
| Publishes research in | Software-Defined Networks and 5G Network Traffic and Congestion Control Network Security and Intrusion Detection Internet Traffic Analysis and Secure E-voting Cloud Computing and Resource Management |
| ISSN | 2834-5509 |
| Citation impact (2-yr) | 2.12 |
| h-index | 11 |
| i10-index | 15 |
| Top institutions publishing here | Politecnico di Torino |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
This paper explores opportunities to utilize Large Language Models (LLMs) to make network configuration human-friendly, simplifying the configuration of network devices & development of routing algorithms and minimizing errors. We design a set of benchmarks (NetConfEval) to examine the effectiveness of different models in facilitating and automating network configuration. More specifically, we focus on the…
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 diffusion model for network flow trace generation. NetDiff employs a hierarchical generation structure that includes a layer to model mobile…
The Open Radio Access Network (RAN) paradigm is transforming cellular networks into a system of disaggregated, virtualized, and software-based components. These self-optimize the network through programmable, closed-loop control, leveraging Artificial Intelligence (AI) and Machine Learning (ML) routines. In this context, Deep Reinforcement Learning (DRL) has shown great potential in addressing complex resource allocation problems. However,…
The rapid growth of satellite network operators (SNOs) has revolutionized broadband communications, enabling global connectivity and bridging the digital divide. As these networks expand, it is important to evaluate their performance and efficiency. This paper presents the first comprehensive study of SNOs. We take an opportunistic approach and devise a methodology which allows to identify…
In-network computing provides significant performance benefits, load reduction, and power savings. Still, an in-network service's functionality is strictly limited to a single hardware device. Research has focused on enabling on-device functionality, with limited consideration to distributed in-network computing. This paper explores the applicability of distributed computing to in-network computing. We present DINC, a framework enabling…
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