Big Data for Cyber-Physical Systems

Abstract

Cyber-physical systems (CPS) are characterized by deep and complex intertwining among cyber components and physical components. Due to the fast increase in system complexities, the operations of CPS involve sensing, processing and storage of massive amount of data. This nature of “big data” imposes fundamental challenges on the design and management of CPS in multiple aspects such as performance, energy efficiency, security, privacy, reliability, sustainability, fault tolerance, scalability and flexibility. Tackling these challenges necessitates innovative big data techniques for handling massive data in CPS. The articles in this special section include a few selected state-of-the-art research results on the topic of big data sensing, processing and storage for CPS, and stimulates a broad range of researchers to participate in the interdisciplinary CPS research in the future. This special issue has received a significant number of submissions while only a small portion of them are selected for publications. The selected papers showcase how interesting data analytics techniques can be leveraged to optimize different metrics in CPS, such as timing, efficiency, schedulability, power, reliability, and security, etc.