Collection
Emerging Trends in Future Intelligent and Reliable Service Systems
This topical collection seeks contributions at the intersection of advances in AI, IoT and service computing. We are interested in innovative techniques, systems, and applications that address the needs for intelligence, efficiency, reliability, and trust in emerging service systems and applications. Articles demonstrating the use of real sensing infrastructure will be given priority. Topics of interest include but are not limited to:
- Intelligence and personalization of services in various intelligent environment, e.g., smart city, smart ocean, smart home, smart farm, autonomous cars, etc.
- Explainability and fairness in intelligent algorithms for reliable intelligent environment
- Quality assurance in cloud-native and serverless architectures
- Computing paradigms specialized for next-generation services in reliable intelligent environment
- Convergence of cloud, edge, IoT and decentralized paradigms
- Convergence of IoT big data and business process management paradigms
- Large language model-based AI agents and services, LLM-augmented services/agents orchestration in reliable intelligent environment
- Reliability engineering for emerging applications like 6G, cyber-physical and blockchain based applications
- Security, privacy and provenance in services and distributed data
- Service/Microservice governance for reliability
- Case studies of future intelligent and reliable service applications and systems
Please find the call for papers at https://link.springer.com/journal/40860/updates/26517476
Editors
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Dr Jian Yu
Dr Jian Yu is an Associate Professor in Department of Computer Science, Auckland University of Technology (Top 250 in THE World University Ranking 2022) and is leading the Ubiquitous Web Computing research lab. His current research interests include deep learning for recommender systems, graph neural networks, complex networks, Web and ubiquitous computing, and service-oriented computing. jian.yu@aut.ac.nz
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Dr Guiling Wang
Dr Guiling Wang is a professor at Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, School of Information Science and Technology, North China University of China. She obtained her Ph.D. at DCST of Tsinghua University in 2007. She was previously an assistant professor in Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS). Her research interests include data integration, services composition, Mashup technologies, Cloud services and large-scale streaming data integration and processing. wangguiling@ncut.edu.cn
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Dr. Marc Hesenius
Dr. Marc Hesenius is a postdoc researcher at the Institute for Software Engineering, University of Duisburg-Essen, where he also obtained his Ph.D. in Computer Science in 2018. His research revolves around the engineering aspects of modern Human-Computer Interaction and Artificial Intelligence. He published about 70 articles in journals and conferences and also has experience as a PI in projects funded by the German Research Foundation (DFG). marc.hesenius@uni-due.de
