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Unmanned Aerial Vehicle Swarm-Enabled Edge Computing

This special issue belongs to the section “Drone 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

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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • unmanned aerial vehicle swarm
  • edge computing
  • energy efficiency
  • resource allocation
  • performance analysis
  • computing security

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Drones - ISSN 2504-446X