Special Issue on advances in 5G/6G-enabled crowd sensing in IoT

The scope of crowd sensing is no longer confined to just the ground. Network entities, such as ground mobile terminals, cars, cameras, low altitude UAV, ocean space crafts and high dimensional space satellites, form the new Internet of Things (IoT). However, the new IoT presents heterogeneous, multidimensional and multi-objective network features. Different tasks have different spatio-temporal characteristics, equipment capabilities and incentive constraints. Existing prediction methods and incentive penalty policies cannot effectively guarantee the spatio-temporal datas’ safety, truthfulness and availability.  The hierarchical 5G/6G network topology makes the problem even more complex. Crowd sensing in IoT is confronting both opportunities and challenges with the advent of 5G/6G. It is important that we find ways to improve the success, coverage and completion rates of task assignment, make the spatio-temporal data available and invisible, and improve the self-organising and truthfulness of mobile crowd sensing in IoT.  

This special issue aims to attract recent novel advances in 5G/6G-enabled crowd sensing for IoT. In particular, we encourage original and high-quality submissions.

Topics covered:

Submissions should touch on (but not be limited to) one or more of the following topics:

• Service quality management in IoT
• Attacks on and defence of IoT data analysis
• Security, privacy and trust mechanisms in IoT
• Task assignment in IoT
• 5G/6G device-to-device communication for IoT
• Low-latency IoT data transmission in 5G/6G ultra-dense networks
• 5G/6G network planning for crowd sensing
• Software-defined 5G/6G network for IoT
• 5G/6G-assisted service management in IoT
• Crowd sensing computing in IoT
• Intelligent IoT data transmission in 5G/6G networks
• 5G/6G service computing in crowd sensing
• Security, privacy and trust mechanisms in crowd sensing
• Edge-cloud service intelligent collaboration technology in IoT
• Task assignment in 5G/6G-enabled crowd sensing
• Service quality control in crowd sensing
• Trustworthy AI for 5G/6G-enabled crowd sensing
• Development and deployment of AI in embedded systems, the IoT and the cloud
• Multi agent-based service computing in IoT
• Deep learning-based edge-cloud service discovery and recommendation
• Distributed learning for IoT data processing
• Learning-based resource management for IoT

Important dates:

• Submission deadline: 30 October 2022
• First notification: 1 January 2023
• Revised version deadline: 1 February 2023
• Final notification: 25 February 2023
• Publication date: May 2023

Submission instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online via the editorial management system; please select article type 5G/6G crowd sensing IoT.

Guest Editors:

• Yingjie Wang, Yantai University, China. Email: wangyingjie@ytu.edu.cn
• Ao Zhou,Beijing University of Post & Telecommunication, Email: aozhou@bupt.edu.cn
• Qun Li, William & Mary, USA. Email: liqun@cs.wm.edu,
• Daehee Seo, Sangmyung University, Korea. Email: daehseo@smu.ac.kr
• Honglu Jiang, The University of Texas Rio Grande Valley, USA. Email: jiang@utrgv.edu
• Zhuojun Duan, James Madison University, USA. Email: duanzx@jmu.edu