System for Cooperative Data Sharing and Privacy Conservation.
Cyber-Physical Systems (CPS) [1] are key building blocks of the fourth industrial revolution. They consist of ICT systems that are embedded into the physical objects we manipulate daily and are interconnected through a complex network, to provide a wide range of innovative applications, resulting from the bridging of the physical and virtual worlds. The management of islands of CPS, which are currently geographically distributed in different countries and regions worldwide, is a challenging issue that will be of interest to both IT researchers and practitioners in the future. The challenge of moving massive datasets between locations of interest, while ensuring the secure transfer of these datasets, is another issue that needs to be resolved in order to get useful insights from the information embedded in these datasets. Therefore, the federation of these isolated digital infrastructures is a natural extension of the body of research that has been produced on CPS for the last decades. This talk focuses on the design and performance evaluation of Federated Cyber-Physical Systems (FCPS) [2,3,4,5,6] with the objective of showcasing through two use-cases how federated cloud computing (FCC) systems and federated machine learning (FML) [5,6] algorithms can be deployed as key FCPS components to build QoS-aware and privacy aware data-intensive ecosystems. Building on the two use-cases, the talk reveals that i) FCC can improve the quality of service delivered by data-intensive infrastructures through cooperative sharing of cloud resources, and ii) by moving data analytics close to where the data resides, FML can protect these infrastructures from attacks while simultaneously preserving the privacy of their data.
[1] Bagula A, Ajayi O, Maluleke H. Cyber physical systems dependability using cps-iot monitoring. Sensors. 2021 Apr 14;21(8):2761.
[2] Celesti A, Fazio M, Galán Márquez F, et al. How to develop IoT cloud e-health systems based on FIWARE: a lesson learnt. Journal of Sensor and Actuator Networks. 2019 Jan 10;8(1):7.
[3] Ajayi O, Bagula A, Ma K. “Fourth industrial revolution for development: The relevance of cloud federation in healthcare support”. IEEE Access. 2019 Dec 18;7:185322-37.
[4] Ajayi O, Bagula A, Maluleke H. “Africa 3: A continental network model to enable the African fourth industrial revolution”. IEEE Access. 2020 Oct 27;8:196847-64.
[5] Maluleke, H., Bagula, A., Ajayi, O. “Federated Cyber Physical Systems for Environment Monitoring”, ISAT Technical Report, Tech-Report-01-August 2022.
[6] Kahenga F, Bagula A, Ajayi O. “Archiving 4.0: Dataset Generation and Classification of DRC Political Figures Using Federated Transfer Learning”, ISAT Technical Report, Tech-Report-02-August 2022.
Bigomokero Antoine Bagula received a Ph.D. degree (Tech. Dr.) in Communication Systems from the Royal Institute of Technology (KTH), Stockholm, Sweden, and 2 MSc degrees (Computer Engineering – Université Catholique de Louvain (UCL), Belgium and Computer Science - University of Stellenbosch (SUN), South Africa). He is currently a full professor and head of the Department of Computer Science at the University of the Western Cape (UWC) where he also leads the Intelligent Systems and Advanced Telecommunication (ISAT) laboratory. He is also an extraordinary Professor at ESIS-Salama where he is in charge of spearheading the institution research agenda. Prof. Bagula is well-published scientist in his research field. His current research interests include Data Engineering including Big Data Technologies, Cloud/Fog Computing and Network Softwarization (e.g., NFV and SDN); The Internet of Things (IoT) including the Internet-of-Things in Motion and the Tactile Internet; Data Science including Artificial Intelligence and Machine Learning with their applications in Big Data Analytics; and Next Generation Networks including 5G/6G
