Paper Info
Title
Distributed Artificial Intelligence Enabled Aerial-Ground Networks: Architecture, Technologies and Challenges
Abstract
Artificial intelligence (AI) provides a promising and novel direction to design future time-varying wireless networks by leading to significantly superior performances compared to conventional methods. In addition, the advanced deployment of unmanned aerial vehicles (UAVs) has boosted extensive novel research results and industrial products in terms of aerial-ground networks. However, with the rapid development of mobile networks and growing requirements for low-latency services, the conventional centralized aerial-ground network has failed to meet the time-varying expectations of mobile users in the dynamic network environment. To cope with the problems, the marriage of the aerial-ground network and innovative AI techniques, i.e., distributed artificial intelligence enabled aerial-ground network (DAIAGN), is proposed in this article, which consists of three vital components: deep reinforcement learning enabled distributed information sharing, edge intelligence enabled distributed security management, and multi-agent reinforcement learning enabled distributed decision making. The functions of the three components are elaborated, and recent related advances are surveyed in detail. A specific case study is also provided with respect to multi-agent reinforcement learning enabled distributed decision making. Furthermore, key challenges and open issues are also discussed to provide some guidances for potential future directions.
Year
DOI
Venue
2022
10.1109/ACCESS.2022.3210337
IEEE ACCESS
Keywords
DocType
Volume
Access control, Optimization, Information sharing, Reinforcement learning, Artificial intelligence, Distributed decision making, Internet of Things, Edge computing, Distributed network, aerial-ground network, artificial intelligence, reinforcement learning, edge intelligence
Journal
10
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Zhaoyue Xia100.34
Jun Du2215.67
Yong Ren3104499.99
Zhu Han411215760.71