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The AI-Orchestrated Cloud Continuum: From Edge Devices to Quantum Resources - Softcover

 
9798260000229: The AI-Orchestrated Cloud Continuum: From Edge Devices to Quantum Resources

Inhaltsangabe

Cloud computing is entering a new phase in which computational resources are increasingly distributed across edge environments, multi-cloud infrastructures, and emerging quantum platforms. Managing this heterogeneous ecosystem requires AI-driven orchestration capable of dynamically coordinating resources while maintaining security, privacy, interoperability, and sustainability. Advances in areas such as intelligent workload placement, serverless computing, federated learning, blockchain-based provenance, and energy-aware scheduling are reshaping the design of modern cloud systems. At the same time, the introduction of quantum-ready services presents new architectural and operational challenges that extend beyond the capabilities of current cloud frameworks. As a result, developing a coherent and reproducible foundation for an autonomous cloud continuum has become a critical research and practical priority for the future of cloud computing. The AI-Orchestrated Cloud Continuum: From Edge Devices to Quantum Resources defines a unified vision where AI-native orchestration manages heterogeneous resources across edge devices, multi-cloud infrastructures, and emerging quantum services, while meeting goals for security, privacy, interoperability, and sustainability. It examines the technical foundations, algorithms, architectures, and real-world deployments that enable an autonomous cloud continuum. Covering topics such as blockchain technology, ethics, and smart cities, this book is an excellent resource for academicians, researchers, graduate and postgraduate students, cloud architects, DevOps engineers, platform engineers, AI/ML practitioners, data scientists, and more.

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Über die Autorinnen und Autoren

Ruchi Doshi Research Professor Department of Computer Science & IT Universidad Azteca, Mexico Email: ruchi.doshi@univ-azteca.edu.mx Dr. Ruchi Doshi has more than 18 years of academic, research and software development experience in Asia, Europe, and Africa. Currently she is working as Research Supervisor and Associate Professor at the Universidad Azteca, Mexico. She worked at the BlueCrest University College, Liberia, Africa; BlueCrest University College, Ghana, Africa; Amity University, India; Trimax IT Infrastructure & Services, India. She is interested in the field of Machine Learning and Cloud computing framework development. She has published research papers in peer-reviewed international journals and conferences; 3 Indian Patents; 9 books on Cloud Computing, Machine Learning, Mobile Cloud computing, Intelligent IoT Systems for Big Data Analysis and Mobile application development. She is Reviewer, Advisor, Ambassador and Editorial board member of various reputed International Journals and Conferences with IEEE, Springer, and Elsevier. She is an active member in organizing many international seminars, workshops, and conferences. She is nominated by IEEE Headquarters, USA for the Chair, Women in Engineering (WIE) position in Liberia, West Africa.

Albert Gyamfi is a business analytics scholar and educator with an extensive academic and industry background in data science, machine learning, knowledge management systems, and database technologies. With a unique blend of experience in higher education and public sector analytics, Dr. Gyamfi has made substantial contributions to research and teaching at the intersection of business analytics, data science, and applied computing. His academic credentials include a PhD in Management Information Systems from Aalborg University in Denmark, an MSc in Computer Science from the University of Regina, and an MBA in Management Information Systems from the University of Ghana. Currently, Dr. Gyamfi serves as an Assistant Lecturer in the Department of Computing Science at the University of Alberta, where he teaches undergraduate courses in data science and database management. His teaching philosophy emphasizes experiential learning, interdisciplinary integration, and accessibility, with a strong commitment to preparing students for real-world applications of analytics and AI.

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