专题:Age of Information Optimization

This cluster of papers focuses on optimizing the freshness of information in communication networks, particularly in the context of real-time status updates, wireless networks, energy harvesting, and scheduling policies. The research explores age of information metrics, multi-hop networks, IoT monitoring systems, and queue management to minimize the age of information and improve network performance.
最新文献
Age of Information Minimization in UAV-Assisted Covert Communication: Trajectory and Beamforming Design

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Age-Dependent Server Selection in a Dual-Server Status Update System

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AI-Empowered Channel Generation for IoV Semantic Communications in Dynamic Conditions

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Minimizing Functions of Age of Incorrect Information for Remote Estimation

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Stability-guaranteed redundant transmission scheduling over Gilbert-Elliot channels for remote state estimation: A deep reinforcement learning approach

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World Model-Based Learning for Long-Term Age of Information Minimization in Vehicular Networks

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AI-enhanced hierarchical routing with Q-learning and graph neural networks for 6G-enabled internet of vehicles

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Addressing the Start-of-Interval Contention Issue in WAVE Protocol Using Reinforcement Learning

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Information Age and Correctness for Energy Harvesting Devices with Random Access

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Goal-Oriented Status Updating for Real-Time Remote Inference Over Networks With Two-Way Delay

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近5年高被引文献
A survey of human-in-the-loop for machine learning

article Full Text OpenAlex 641 FWCI83.8511

Edge AI: A survey

article Full Text OpenAlex 417 FWCI81.1837

Joint Task Offloading and Resource Allocation for Energy-Constrained Mobile Edge Computing

article Full Text OpenAlex 365 FWCI50.2047

Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review

review Full Text OpenAlex 315 FWCI38.6396

Task Co-Offloading for D2D-Assisted Mobile Edge Computing in Industrial Internet of Things

article Full Text OpenAlex 285 FWCI39.0947

Joint Multi-Task Offloading and Resource Allocation for Mobile Edge Computing Systems in Satellite IoT

article Full Text OpenAlex 284 FWCI55.8773

Computation offloading in mobile edge computing networks: A survey

article Full Text OpenAlex 263 FWCI35.3557

Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges

review Full Text OpenAlex 254 FWCI32.9334

AI-Empowered Fog/Edge Resource Management for IoT Applications: A Comprehensive Review, Research Challenges, and Future Perspectives

article Full Text OpenAlex 232 FWCI45.1669

Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

article Full Text OpenAlex 207 FWCI26.4167