Recent strides in the combination of AI, Edge computing and IoT technology have shown great potential to unlock the edge Artificial Intelligence (edge AI) era for various applications. Edge AI systems have opened new opportunities for many areas, such as smart cities, intelligent transportation systems, digital economy, and so on. These technological innovations in multiple dimensions blur the lines between the physical and digital worlds and provide more convenient smart living solutions for human society. However, the existing edge AI systems still have several challenges and drawbacks, especially in exploring the win-win solution for establishing a secure and privacy-aware edge AI system. Blockchain, an immutable, decentralized, and cryptography-based technology, could overcome the structural flaws of the edge AI designs. For example, using blockchain in the AI training protocol can provide an audit trail of various kinds of transactions, and manage data usage and data/model sharing process. The combined values of blockchain and edge AI could lead to advancement in terms of authenticity and secured automation.

The aim of this special issue is to highlight novel and high-quality research in blockchain technology and applications for edge AI systems, including the blockchain-enabled edge AI frameworks, platforms, applications, architectures, algorithms, and emerging technologies that facilitate the combination of edge computing, AI, and blockchain.

Topic areas include, but are not limited to, the following:

• Blockchain theories and algorithms for EdgeAI trust, security, and privacy;
• Trustworthy data management with blockchain;
• Secure EdgeAI system design based on smart blockchain;
• Decentralized and collaborative learning for EdgeAI;
• End-edge-cloud computing enabled by blockchain;
• Big data analytics based on blockchain in EdgeAI systems;
• Performance optimization of blockchains enabled EdgeAI.

Important Dates

• Submission deadline: 31 October 2023
• Expected acceptance deadline: 31 December 2023
• Expected publication date: 29 February 2024

Guest Editors

• Dongxiao Yu, Shandong University, China. Email: dxyu@sdu.edu.cn
  Dongxiao Yu (Senior Member, IEEE) received the BS degree from the School of Mathematics, Shandong University, in 2006, and the PhD degree from the Department of Computer Science, University of Hong Kong, in 2014. He is currently a professor with the School of Computer Science and Technology, Shandong University. His research interests include wireless networks, distributed computing, and graph algorithms.
• Shaoyong Guo, Beijing University of Posts and Telecommunications, China. Email: syguo@bupt.edu.cn
  Shaoyong Guo (Member, IEEE) received the PhD degree from the Beijing University of Posts and Telecommunication. He is currently with the Department of State Key Laboratory of Networking and Switching Technology. His research interests include blockchain application technology, edge computing, and IIoT in energy Internet. His main contribution about Blockchain and IoT is taking the lead to declare ITU-standard: Decentralized IoT communication architecture based on Information Centric Networking and Blockchain in ITU-T SG20 2018 and undertake State Grid's project Application Research of Blockchain Technology in Energy Internet.
• Peng Li, The University of Aizu, Japan. Email: pengli@u-aizu.ac.jp
  Peng Li (Senior Member, IEEE) received the BS degree from the Huazhong University of Science and Technology, China, in 2007, and the MS and PhD degrees from The University of Aizu, Japan, in 2009 and 2012, respectively. He is currently an associate professor with The University of Aizu. He has published over 100 technical papers on prestigious journals and conferences. His research interests include cloud/edge computing, the Internet of Things, machine learning systems, and related wired and wireless networking problems. He won the Young Author Award of IEEE Computer Society Japan Chapter, in 2014, and the Best Paper Award of the 2016 IEEE TrustCom. He supervised students to win the First Prize of IEEE ComSoc Student Competition, in 2016. He is an Editor of IEICE Transactions on Communications and IEEE Open Journal of the Computer Society.
• Qin Hu, Indiana University-Purdue University Indianapolis, USA. Email: qinhu@Iu.edu
  Qin Hu received the PhD degree in computer science from The George Washington University in 2019. She is currently an assistant professor with the Department of Computer and Information Science, Indiana University-Purdue University Indianapolis. She received the Best Paper Award of WASA 2020 and the Best Paper Award Runner-up of IEEE MASS 2021. She has served as the Editor for two journals, the Guest Editor for four journals, the TPC/Publicity chair for five workshops/conferences, and the TPC Member for several international conferences, such as IEEE INFOCOM 2022/2023, IEEE MASS 2022, IEEE Globecom 2019-2022, and IEEE Blockchain 2019-2022. Her research interests include wireless and mobile security, crowdsourcing/crowdsensing, and blockchain. Her research on distributed machine learning has been funded by the US NSF CRII 2021.