Driven by the rapid advancement of artificial intelligence and large model technologies, Cyber-Physical Social Systems (CPSS) have become a core infrastructure supporting smart cities, intelligent manufacturing, intelligent transportation, and industrial Internet applications. CPSS tightly couples physical equipment operation, network cyber interaction, and complex human social behaviors, generating massive volumes of multi-source heterogeneous and dynamically evolving cyber-physical-social big data at an unprecedented scale. Nevertheless, traditional big data mining and analytical paradigms suffer from prominent limitations in processing large-scale CPSS datasets, including excessive computational latency, insufficient parallel processing capability, unreasonable system resource scheduling, and deficient privacy-preserving mechanisms. Such drawbacks severely restrict efficient, real-time, reliable, and secure big data mining and analytics, failing to meet the high-standard requirements of industrial-grade CPSS application scenarios.

Against this background, High Performance Computing and Communications (HPCC) has become the core driving technology to break through the computational bottlenecks of CPSS big data intelligent analysis. Advanced HPCC technologies, including parallel distributed computing, edge-cloud collaborative acceleration, and hardware-software collaborative computing architectures, provide powerful support for efficient processing, real-time mining, and trustworthy analysis of massive and complex CPSS big data. Combined with cutting-edge big data mining theories, intelligent analytical methods, and AI security mechanisms, HPCC enables accurate implicit rule discovery, real-time CPSS system state perception, robust risk early warning, and intelligent collaborative decision-making. This Special Issue aims to collect state-of-the-art research focusing on high-performance computing enabled cyber-physical-social big data mining and analytics. It particularly focuses on HPCC-oriented theoretical innovations, high-performance algorithm optimization, system performance tuning, and secure and robust analytical schemes for CPSS big data, as well as practical industrial application cases. The issue intends to promote the in-depth interdisciplinary integration of high-performance computing, big data mining and analytics, and CPSS intelligent applications, so as to further boost sustainable technological innovation and industrial development of high-efficiency and trustworthy CPSS big data analytical systems.

Topics of Interest

This special issue welcomes original research articles and comprehensive review papers covering (but not limited to) the following topics closely integrated with high-performance computing, secure big data analytics and CPSS applications:

• Parallel and distributed high-performance algorithms for CPSS big data mining
• Intelligent optimization of distributed mining algorithms adapting to CPSS multi-dimensional heterogeneous data characteristics
• Lightweight high-performance data mining schemes for resource-constrained edge CPSS devices
• Edge-cloud collaborative computing frameworks and task offloading strategies for real-time CPSS data analysis
• High-throughput and low-latency real-time big data analysis frameworks for dynamic CPSS streaming data
• System performance modeling, benchmark testing and adaptive tuning for CPSS big data analytics workloads
• Hardware acceleration (GPU/TPU/FPGA) technologies for CPSS data mining and data intelligence computation
• Cross-network data analysis and intelligent data placement strategies for multi-data-center CPSS scenarios
• Network load balancing and throughput performance optimization for multi-node cluster CPSS computing systems
• Security and robustness enhancement technologies for distributed CPSS data mining systems
• High-robustness and high-security data mining schemes for industrial-grade intelligent CPSS scenarios
• Blockchain and AI security assisted trusted computing for HPCC-driven CPSS big data analysis

Important Dates

• Manuscript Submission Deadline: 30 December 2026
• First Round Review Notification: 15 March 2027
• Revision Submission Deadline: 15 May 2027
• Final Acceptance Notification: 15 July 2027

Submission Guidelines

Authors should submit manuscripts via the journal’s official online submission system. Please select the special issue titled “High Performance Computing and Communications for Cyber-Physical-Social Big Data Mining and Analytics” during submission. All manuscripts will undergo strict, double-blind peer review by international authoritative experts in high-performance computing and communications, big data mining and analytics, and cyber-physical-social systems, adhering to the principles of fairness, impartiality and academic rigor. For submission questions or consultation, please contact the journal editorial office or the special issue guest editors.

Guest Editors

Prof. Xiaokang Wang (kxwang@zzu.edu.cn), Zhengzhou University, China.

Dr. Steve Drew (steve.drew@ucalgary.ca), University of Calgary, Canada.

Prof. Lizhen Deng (denglizhen@njupt.edu.cn), Nanjing University of Posts and Telecommunications, China.

Prof. Hai Jiang (hai.jiang@bupt.edu.cn), Beijing University of Posts and Telecommunications, China.

Prof. Parimala Thulasiraman (parimala.thulasiraman@umanitoba.ca), University of Manitoba, Canada.