Cyber Physical Social Intelligence (CPSI) is an emerging concept which amalgamates the cyber world, physical world, and social world into a cohesive, interconnected entity. This convergence enables a profound level of intelligence, paving the way for smart systems, advanced manufacturing, intelligent transportation systems, and more. The massive CPSI Big Data is diverse, dynamic, and large-scale, making it essential to employ advanced Big Data computing techniques for extracting valuable information and knowledge. However, dealing with such massive, heterogenous, and complex data introduces numerous challenges, necessitating breakthroughs in Big Data computing.

Big Data computing for CPSI not only demands effective and efficient storage, processing, and analysis of large-scale data, but also requires real-time or near real-time response, high performance computing, and intelligent decision-making. Dealing with these complex requirements is no easy feat. Distributed and parallel computing techniques, which allow for simultaneous processing of substantial amounts of data across multiple machines, become crucial. However, this also introduces concerns, such as data consistency, synchronization, scaling, and communication overhead management. Ensuring robust performance while balancing load, scheduling, and managing resources is another challenging area in the context of CPSI.

This special issue aims to address the most recent developments and research findings related to Big Data computing for CPSI, focusing on areas like parallel and distributed Big Data processing, intelligent data analysis, real-time data management, resource allocation, load balancing, etc. This issue strives to provide a platform for researchers and practitioners worldwide, encouraging the innovation of new solutions that can tackle the unique challenges associated with CPSI and Big Data computing. It endeavors to promote discussions, stimulate ideas, and foster collaborations towards developing advanced, scalable, and intelligent CPSI systems.

This call for papers invites researchers and practitioners to submit original contributions on the topic of Big Data computing for Cyber Physical Social Intelligence (CPSI). Topics of interest include but are not limited to:

• Parallel & distributed CPSI algorithms
• High-performance CPSI algorithms
• System architecture design for CPSI
• Hardware accelerators for CPSI
• Distributed and cooperative learning for CPSI
• Hardware-aware algorithms for CPSI
• Parallel & distributed computing for emerging CPSI applications
• Offloading & scheduling strategy for efficient and high-performance CPSI
• Data and model parallelism for CPSI
• Efficient training and inference strategies for CPSI algorithms

The authors are requested to submit their full research papers complying with the general scope of the journal. The submitted papers will undergo peer review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

IMPORTANT DATES

Deadline for submissions: 1 May 2024

GUEST EDITORS

Prof. Xiaokang Wang, Hainan University, China. E-mail: xkwang@hainanu.edu.cn.

Prof. Cen Chen, South China University of Technology, China. E-mail: chencen@scut.edu.cn.

Dr. Joey Tianyi Zhou, A*STAR, Singapore. E-mail: joey.tianyi.zhou@gmail.com.

Prof. Hai Jiang, Arkansas State University, USA. E-mail: hjiang@astate.edu.

Prof. Weiwei Xing, Beijing Jiaotong University, China. E-mail: wwxing@bjtu.edu.cn.