The 20th IEEE International Conference on
Mobile Ad-Hoc and Smart Systems
(MASS 2023)

ABOUT IEEE MASS 2023

IEEE MASS is a premier annual forum for sharing original, novel ideas in mobile ad-hoc networks and smart systems, defined broadly. As wireless ad-hoc networks continue to evolve and specialize into a number of application scenarios and environments, and sensor-based systems and technologies increasingly permeate our everyday life and become the inner fabric of the Internet of Things and cyber-physical systems, the unfolding of smart environments such as smart cities, smart farming, smart healthcare, and smart manufacturing, to name a few, demand integrated solutions that can make intelligent use of both cloud and edge systems, while applying machine learning and artificial intelligence tools to handle their growing complexity and to leverage the vast amount of available data created.

Sponsored by the IEEE Computer Society and IEEE Computer Society's TCDP, the 20th edition of the IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS) will be held in Toronto, Canada in September 2023, and it aims at bringing together researchers, developers, and practitioners to address recent advances in mobile ad-hoc and smart systems, covering algorithms, theory, protocols, systems & applications, experimental evaluations and testbeds, security/privacy, as well as AI/ML-based smart design.

Accepted papers for IEEE MASS 2023 will be included in IEEE Xplore Digital Library after they are presented at the conference. Information and instructions on how to prepare for a presentation will be provided. The organizing committee and the program committee will endeavor to ensure the high quality of the conference program and the excellent experience of conference authors and attendees. Thank you for your understanding and support!

Best Paper Award of IEEE MASS 2023: Towards Federated Learning on Fresh Datasets, by Chen Wu and Mingjun Xiao (University of Science and Technology of China, China); Jie Wu (Temple University, USA); Yin Xu, Jinrui Zhou and He Sun (University of Science and Technology of China, China)
Best Paper Runner-Up Award of IEEE MASS 2023: Towards Efficient Privacy-Preserving Top-k Trajectory Similarity Query, by Kelai Yi, Yuefeng Chen, Yuchen Su and Xiong Li (University of Electronic Science and Technology of China, China); Hongbo Liu (Electronic Science and Technology of China, China); Huan Dai (Suzhou University of Science and Technology, China); Xiaonan Guo (George Mason University, USA); Yingying Chen (Rutgers University, USA)
Congratulations!