Unmanned Aerial Vehicle Swarm-Enabled Edge Computing
A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Communications".
Deadline for manuscript submissions: 31 March 2025 | Viewed by 1342
Special Issue Editors
Interests: UAV swarm intelligence; mobile edge computing and edge intelligence; machine learning; wireless communication
Interests: cognitive radio; cognitive intelligence; knowledge graph; semantic communications; edge intelligence
Interests: cognitive wireless network; cognitive IOT; large-scale array signal processing; data mining method; optimization theory; machine learning; unmanned aerial vehicle (UAV) cognitive-communication
Interests: wireless communications; security; edge computing; deep learning; federated learning; IoT networks
Special Issues, Collections and Topics in MDPI journals
Interests: game-theoretic cognitive radio networks; cooperative communications; multiuser communications theory; physical-layer security; massive MIMO; energy-harvesting wireless communications
Interests: next generation wireless communications and networking; AI and Machine Learning, Internet of Things; big data and cloud/fog computing; wireless sensor networks; smart grid communications
Special Issue Information
Dear Colleagues,
Unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) has emerged as a promising technique for wireless devices to realize low latency and high reliability communication and computation services in a more flexible and cost-effective manner. However, the small-scale UAVs enabled edge computing networks are incompetence in handling more complex missions, such as earth monitoring, precision agriculture and large-scale military deployment. As a result, UAV swarm-enabled edge computing has attracted great attention from academia and industry in recent years. It is envisioned that UAV swarm-enabled edge computing can provide strong support for us to embrace the forthcoming era of “Internet of Drones (IoD)” and gain wide popularity in supporting future human activities. In order to facilitate the implementation of UAV swarm-enabled edge computing, several preliminary research work have been carried out including resource allocation of UAV swarm-enabled edge computing and dynamic spectrum management of UAV swarm-enabled edge computing. Although these emerging issues have drawn considerable attention and have been studied recently, there are still many open theoretical and practical problems to be addressed. Specifically, in order to ensure low execution latency and high energy efficiency of UAV swarm-enabled edge computing, how to reduce UAV-to-ground and UAV-to-UAV interference, need to be further investigated. In addition, note that the severe intra-swarm wireless interference, the uncertainty of wireless channel and data processing latency will inevitably cause response delay of UAV, which impairs the stability of the UAV swarm. Therefore, more research efforts are needed to investigate the effective robust automatic networking technologies for keeping stability of large-scale UAV swarm. Furthermore, computing task sharing has a huge risk of privacy leakage, which prompts the computational security in the UAV swarm-enable edge computing network to be an attentional issue.The aim of this special issue is to provide a new comprehensive overview on UAV swarm and create more ideas on UAV swarm-enabled edge computing, which will bring together researchers from academia, industry and governmental agencies to promote the research and development needed to address the major challenges that pertain to this cutting-edge research topic.
Dr. Wei Wu
Prof. Dr. Fuhui Zhou
Prof. Dr. Qihui Wu
Prof. Dr. Lisheng Fan
Prof. Dr. Kai Kit Wong
Prof. Dr. Rose Hu
Guest Editors
Manuscript Submission Information
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Keywords
- unmanned aerial vehicle swarm
- edge computing
- energy efficiency
- resource allocation
- performance analysis
- computing security
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