A Review on Air-Ground Coordination in Mobile Edge Computing: Key Technologies, Applications and Future Directions
S Li, G Liu, L Li, Z Zhang, W Fei… - Tsinghua Science and …, 2024 - ieeexplore.ieee.org
In recent years, Mobile Edge Computing (MEC) has received extensive research attention
due to its characteristics, such as real-time data processing and flexible application …
due to its characteristics, such as real-time data processing and flexible application …
Energy-Efficient Ground-Air-Space Vehicular Crowdsensing by Hierarchical Multi-Agent Deep Reinforcement Learning with Diffusion Models
The integrated ground-air-space (GAS) communications system can enhance post-disaster
rescue and management efforts when traditional networks fail, by navigating unmanned …
rescue and management efforts when traditional networks fail, by navigating unmanned …
Fairness-Aware Dynamic Ride-Hailing Matching Based on Reinforcement Learning
Y Liang - Electronics, 2024 - mdpi.com
The core issue in ridesharing is designing reasonable algorithms to match drivers and
passengers. The ridesharing matching problem, influenced by various constraints such as …
passengers. The ridesharing matching problem, influenced by various constraints such as …
Indoor Periodic Fingerprint Collections by Vehicular Crowdsensing via Primal-Dual Multi-Agent Deep Reinforcement Learning
Indoor localization is drawing more and more attentions due to the growing demand of
various location-based services, where fingerprinting is a popular data driven techniques …
various location-based services, where fingerprinting is a popular data driven techniques …
AGCoTrack: A Communication-efficient Independent Reinforcement Learning Method for Aerial-Ground Collaborative Tracking
In the realm of the Internet of Things, a multitude of interconnected and intelligent devices
enable profound interaction with the physical world. Within this context, a combination of …
enable profound interaction with the physical world. Within this context, a combination of …
Optimizing UAV-UGV coalition operations: A hybrid clustering and multi-agent reinforcement learning approach for path planning in obstructed environment
One of the most critical applications undertaken by Unmanned Aerial Vehicles (UAVs) and
Unmanned Ground Vehicles (UGVs) is reaching predefined targets by following the most …
Unmanned Ground Vehicles (UGVs) is reaching predefined targets by following the most …
Towards Privacy-preserving Spatial Crowdsourcing: from Offline to Online
Recent years have seen Spatial Crowdsourcing (SC) becoming a promising paradigm of
collecting large amounts of location-aware data for various network applications. Its …
collecting large amounts of location-aware data for various network applications. Its …
Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach
Collaborative tasks often require the cooperation of multiple individuals to be completed in
mobile crowdsensing (MCS). However, previous task recommendations predominantly …
mobile crowdsensing (MCS). However, previous task recommendations predominantly …