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20102026
most citedConvergence of Edge Computing and Deep Learning: A Comprehensive Survey

1.5k citations · 13.5k across the 438 of their papers we have counts for

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135 papers · 1 filter

cs.NI2026

Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks

Ziye Jia, Sijie He, Ligang Yuan +4

Due to the scalability and portability, low-altitude intelligent networks (LAINs) are essential in various fields such as surveillance and disaster rescue. However, in LAINs, unman…

cs.NI2025

RIS-assisted Data Collection and Wireless Power Transfer in Low-altitude Wireless Networks

Wenwen Xie, Geng Sun, Jiahui Li +5

Low-altitude wireless networks (LAWNs) have become effective solutions for collecting data from low-power Internet-of-Things devices (IoTDs) in remote areas with limited communicat…

cs.NI2025★ 2 cited

Safeguarding ISAC Performance in Low-Altitude Wireless Networks Under Channel Access Attack

Jiacheng Wang, Jialing He, Geng Sun +5

The increasing saturation of terrestrial resources has driven the exploration of low-altitude applications such as air taxis. Low altitude wireless networks (LAWNs) serve as the fo…

cs.NI2025

HybridRAG-based LLM Agents for Low-Carbon Optimization in Low-Altitude Economy Networks

Jinbo Wen, Cheng Su, Jiawen Kang +5

Low-Altitude Economy Networks (LAENets) are emerging as a promising paradigm to support various low-altitude services through integrated air-ground infrastructure. To satisfy low-l…

cs.NI2025

Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing

Minrui Xu, Dusit Niyato, Jiawen Kang +5

Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and…

cs.NI2025

Efficient Twin Migration in Vehicular Metaverses: Multi-Agent Split Deep Reinforcement Learning with Spatio-Temporal Trajectory Generation

Junlong Chen, Jiawen Kang, Minrui Xu +5

Vehicle Twins (VTs) as digital representations of vehicles can provide users with immersive experiences in vehicular metaverse applications, e.g., Augmented Reality (AR) navigation…