IEEE Networking Letters最新文献

2025 Index IEEE Networking Letters Vol. 7 2025索引IEEE网络通讯第7卷

IEEE Networking Letters Pub Date : 2026-02-09 DOI: 10.1109/LNET.2026.3662547

引用次数: 0

AI/ML-Based QoS Recommendations for Energy Optimization in 6G Networks 基于AI/ ml的6G网络能量优化QoS建议

IEEE Networking Letters Pub Date : 2026-02-02 DOI: 10.1109/LNET.2026.3660985

Sara Ghasvarianjahromi;Abbas Kiani;Amanda Xiang;John Kaippallimalil;Tony Saboorian;Nirwan Ansari

引用次数: 0

IEEE Networking Letters Society Information IEEE网络通讯协会信息

IEEE Networking Letters Pub Date : 2026-01-16 DOI: 10.1109/LNET.2025.3636374

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IEEE Networking Letters Author Guidelines IEEE网络通讯作者指南

IEEE Networking Letters Pub Date : 2026-01-16 DOI: 10.1109/LNET.2025.3636372

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QoS-Aware Network Selection in Hybrid RF-VLC Wireless Systems: A Stackelberg Game Approach 混合RF-VLC无线系统中qos感知网络选择：一个Stackelberg博弈方法

IEEE Networking Letters Pub Date : 2026-01-13 DOI: 10.1109/LNET.2026.3653993

Muthiah Sivavelan S.;Astitva Kamble;Mahendra K. Shukla;Om Jee Pandey

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End-to-End AI Lifecycle Management for 6G: Bridging DataOps and MLOps 6G的端到端人工智能生命周期管理：桥接数据操作和mlop

IEEE Networking Letters Pub Date : 2026-01-01 Epub Date: 2026-02-03 DOI: 10.1109/LNET.2026.3661251

Menuka Perera Jayasuriya Kuranage;Ameur Mazene;Abdelkader Mekrache;Adlen Ksentini

{"title":"End-to-End AI Lifecycle Management for 6G: Bridging DataOps and MLOps","authors":"Menuka Perera Jayasuriya Kuranage;Ameur Mazene;Abdelkader Mekrache;Adlen Ksentini","doi":"10.1109/LNET.2026.3661251","DOIUrl":"https://doi.org/10.1109/LNET.2026.3661251","url":null,"abstract":"As 6G networks evolve toward a data-centric architecture with full automation capabilities, the softwarization of network functions enables access to a wide spectrum of data across technical, management, and operational domains. This rich data provides a strong foundation for building efficient, dynamic, and scalable network environments, where Artificial Intelligence (AI) and Machine Learning (ML) play a vital role in enabling data-driven intelligence within 6G networks. Consequently, streamlining AI/ML workflows becomes essential to fully harness the potential of 6G. Given the massive volume of data generated and the extensive applicability of AI/ML across various layers of the 6G architecture, including the Radio Access Network (RAN), Core, and Edge, managing AI/ML workflows at scale presents significant challenges. To address these challenges, we propose a novel microservice-oriented DataOps-MLOps framework designed to streamline AI/ML workflows across all domains. The proposed framework natively supports model training, model versioning and incorporates an automated data pipelining approach that facilitates seamless data collection and real-time inference. To validate the framework’s effectiveness, we implemented a traffic anomaly detection use case involving end-to-end (E2E) ML model training, deployment, and real-time inference. Experimental results demonstrate that the proposed framework significantly streamlines AI/ML operations, unlocking the full potential of AI/ML integration in future 6G networks.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"169-173"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerating Inter-App Communications for Time-Critical O-RAN Control Loops 加速时间关键O-RAN控制回路的应用程序间通信

IEEE Networking Letters Pub Date : 2026-01-01 Epub Date: 2026-03-04 DOI: 10.1109/LNET.2026.3670470

Lorenzo Rosa;Andrea Garbugli;Domenico Scotece;Luca Foschini

{"title":"Accelerating Inter-App Communications for Time-Critical O-RAN Control Loops","authors":"Lorenzo Rosa;Andrea Garbugli;Domenico Scotece;Luca Foschini","doi":"10.1109/LNET.2026.3670470","DOIUrl":"https://doi.org/10.1109/LNET.2026.3670470","url":null,"abstract":"The Open Radio Access Network (O-RAN) is reshaping cellular architectures through disaggregation, openness, and programmability, enabling intelligent control across modular RAN components. A growing ecosystem of user-defined control-plane applications, namely rApps, xApps, and the emerging dApps, operates at different timescales and unlocks advanced control loop capabilities, but introduces diverse and stringent Quality of Service (QoS) requirements for communication. Current implementations typically rely on cloud-based messaging systems, which privilege transparency and ease of use for developers and limit support for time-sensitive workloads. In this letter, we propose that O-RAN control loops base their internal communication on INSANE, a cloud-native, data-centric middleware that supports multiple networking stacks, including kernel-bypass option such as eBPF XDP, DPDK, and RDMA. Our preliminary evaluation shows that INSANE achieves nearly <inline-formula> <tex-math>$2times $ </tex-math></inline-formula> higher throughput than widely used alternatives, while reducing 99.9th-percentile latency of over an order of magnitude for small messages. At the same time, INSANE preserves a uniform and easy-to-use programming interface. These results highlight INSANE as a promising foundation for faster, more predictable control loops, a significant step toward the ultimate goal of enabling AI-driven RAN optimizations in O-RAN systems.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"140-143"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11421355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Differential Privacy on Federated Learning: A Correlated Equilibrium and Simulated Annealing Approach 联邦学习中的差分隐私：一种相关均衡和模拟退火方法

IF 3.3

IEEE Networking Letters Pub Date : 2026-01-01 Epub Date: 2026-04-03 DOI: 10.1109/LNET.2026.3680523

Sávio Miranda;Luiz Moreira;Aruzhan Sabyrbek;André Riker;Eirini Eleni Tsiropoulou

引用次数: 0

A SPEA-Based Algorithm for Finding Recovery Path in a Network Under Malware Attack 基于spea的恶意软件攻击下网络恢复路径查找算法

IF 3.3

IEEE Networking Letters Pub Date : 2026-01-01 Epub Date: 2026-08-20 DOI: 10.1109/LNET.2026.3724588

Sanghamitra De;Chinmoy Ghorai;Indrajit Banerjee

引用次数: 0

Relay Selection in Wireless Networks as Restless Bandits 无线网络中的中继选择如同不安宁的强盗

IF 3.3

IEEE Networking Letters Pub Date : 2026-01-01 Epub Date: 2026-02-27 DOI: 10.1109/LNET.2026.3668871

Mandar R. Nalavade;Ravindra S. Tomar;Gaurav S. Kasbekar

{"title":"Relay Selection in Wireless Networks as Restless Bandits","authors":"Mandar R. Nalavade;Ravindra S. Tomar;Gaurav S. Kasbekar","doi":"10.1109/LNET.2026.3668871","DOIUrl":"https://doi.org/10.1109/LNET.2026.3668871","url":null,"abstract":"We consider a wireless network in which a source node needs to transmit a large file to a destination node. The direct wireless link between the source and the destination is assumed to be blocked. Multiple candidate relays are available to forward packets from the source to the destination. A holding cost is incurred for each packet stored at every relay in each time slot. The objective is to design a policy for selecting a relay in each time slot to which the source attempts to send a packet, so as to minimize the expected long-run time-averaged total packet holding cost at the relays. This problem is an instance of the restless multi-armed bandit (RMAB) problem, which is provably hard to solve. We establish the Whittle indexability of this relay selection problem and propose a computationally efficient policy to compute the Whittle index of each relay in every time slot. In each time slot, our relay selection policy transmits a packet to the relay with the smallest Whittle index. Using simulations, we show that our proposed policy outperforms several relay selection policies proposed in prior work in terms of the average cost, delay, as well as throughput.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"8 ","pages":"115-119"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148491845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0