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IEEE Transactions on Networking is a peer-reviewed journal published by IEEE, covering Software-Defined Networks and 5G, Cloud Computing and Resource Management, IoT and Edge/Fog Computing. Over its lifetime it has published 660 papers, which have received 735 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Networking, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Networking style. No sign-up. |
| Abbreviation (ISO-4) | TON |
| Publishes research in | Software-Defined Networks and 5G Cloud Computing and Resource Management IoT and Edge/Fog Computing Network Traffic and Congestion Control Privacy-Preserving Technologies in Data |
| ISSN | 2998-4157 |
| Citation impact (2-yr) | 1.11 |
| h-index | 9 |
| i10-index | 9 |
| Top institutions publishing here | Tsinghua University |
| 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.
Internet-connected devices generate service function chain (SFC) requests for reliability-sensitive applications such as smart factories and intelligent healthcare. To facilitate reliable SFC provisioning, one can employ dedicated SFC protection approaches to protect the primary service function path (SFP) by constructing a fault-disjointed backup SFP. Notably, the construction processes of the fault-disjointed primary and backup SFPs…
As a key technique for future networks, the performance of emerging multi-edge caching is often limited by inefficient collaboration among edge nodes and improper resource configuration. Meanwhile, achieving optimal cache hit rates poses substantive challenges without effectively capturing the potential relations between discrete user features and diverse content libraries. These challenges become further sophisticated when…
Collaborative perception systems leverage multiple edge devices, such as surveillance cameras or autonomous cars, to enhance sensing quality and eliminate blind spots. Despite their advantages, challenges such as limited channel capacity and data redundancy impede their effectiveness. To address these issues, we introduce the Prioritized Information Bottleneck (PIB) framework for edge video analytics. This framework…
The increasing complexity of deep neural networks poses significant barriers to democratizing AI to resource-limited edge devices. To address this challenge, split federated learning (SFL) has emerged as a promising solution that enables device-server co-training through model splitting. However, although system optimization substantially influences the performance of SFL, the problem remains largely uncharted. In this…
Assessing the vulnerability of mega-constellation networks (MCNs) to large-scale failure is challenging, due to the time-varying three-dimensional constellation. In this paper, we propose a geometrical method to assess the vulnerability of the MCNs under large-scale geographical failure based on the standard +<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Grid</i> inter-satellite connectivity pattern, using hop count as the metric. We first…
