Call for Chapters: The AI-Orchestrated Cloud Continuum: From Edge Devices to Quantum Resources

Editors

Ruchi Doshi, Universidad Azteca, India
Albert Gyamfi, Athabasca University, Canada

Call for Chapters

Proposals Submission Deadline: March 21, 2026
 Full Chapters Due: May 23, 2026
 Submission Date: May 23, 2026

Introduction

Autonomous Cloud Continuum: AI-Driven Orchestration from Edge to Quantum frames a timely, interdisciplinary agenda for the next decade of cloud research and practice. The publication 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 combines rigorous research, reproducible artifacts, and practitioner case studies to serve both scholarly and operational communities. This edited volume examines the technical foundations, algorithms, architectures, and real world deployments that enable an autonomous cloud continuum. Chapters will cover AI driven autoscaling and placement, advanced serverless and function meshes, edge cloud orchestration, federated and privacy preserving ML, blockchain based provenance, energy aware scheduling, and quantum ready cloud APIs. Each chapter will include methodology, experimental results, and reproducible artifacts (code, datasets, evaluation scripts) or detailed deployment notes.

Objective

This volume aims to define and formalize the concept of an Autonomous Cloud Continuum by unifying AI driven orchestration, edge to cloud integration, multi cloud interoperability, and quantum ready services into a coherent framework; advance research by synthesizing state of the art methods across distributed systems, AI, security, and quantum computing while identifying open problems and proposing novel algorithms; raise experimental rigor through standardized, reproducible benchmarks, datasets, and evaluation scripts that enable fair comparison and energy aware metrics; accelerate practical adoption by delivering actionable architectures, blueprints, and deployment case studies for cloud architects and industry teams; support education and capacity building with ready to use teaching modules, lab exercises, and instructor materials; and inform policy and sustainability decisions by providing evidence based analyses and carbon aware scheduling frameworks that guide responsible cloud governance.

Target Audience

Primary audience: Academic researchers and graduate students in distributed systems, cloud computing, and artificial intelligence who need state of the art methods, reproducible datasets, and evaluation frameworks for advancing research on autonomous cloud orchestration. Secondary audience: Cloud architects, DevOps engineers, and platform engineers in industry seeking actionable architectures, autoscaling strategies, multi cloud orchestration patterns, and energy aware deployment blueprints that can be prototyped and operationalized. Tertiary audience: AI/ML practitioners and data scientists implementing federated and distributed learning pipelines; security and compliance professionals interested in zero trust models, provenance, and blockchain backed auditability; and quantum computing researchers exploring hybrid quantum classical workflows. Educational and policy users: Course instructors and training providers who will adopt chapters as modules, lab exercises, and instructor slide packs; curriculum designers building cloud native and edge computing courses; and policy makers and sustainability strategists evaluating carbon aware SLAs, procurement guidelines, and governance frameworks.

Recommended Topics

The book will cover, but is not limited to, the following topics: AI driven Cloud Orchestration and Autoscaling — architectures; reinforcement learning for autoscaling; predictive placement; Serverless Evolution and Function Meshes — advanced FaaS patterns; cold start mitigation; observability; Edge Cloud Continuum and Fog Architectures — latency aware placement; hybrid orchestration; Federated Learning and Privacy Preserving Cloud ML — secure aggregation; differential privacy at scale; Quantum Ready Cloud Services and APIs — hybrid quantum classical workflows; middleware; Green Cloud and Energy Aware Scheduling — carbon aware placement; renewable aware SLAs; Cloud Security Innovations and Zero Trust Models — confidential computing; hardware roots of trust; Blockchain and Provenance for Cloud Workflows — immutable provenance; auditability; Blockchain for Educational Credentialing and Data Integrity — verifiable credentials; tamper proof transcripts; Cloud in Education and Digital Learning Platforms — scalable LMS; virtual labs; AI tutors and adaptive learning; Interoperability, Multi Cloud Orchestration, and Portability — standards; service meshes across providers; Reproducibility, Benchmarks, and Evaluation Methodologies — datasets; energy and performance benchmarks; Case Studies and Industry Applications — healthcare; finance; smart cities; manufacturing.

Submission Procedure

Researchers and practitioners are invited to submit on or before March 21, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by April 4, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by May 23, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, The AI-Orchestrated Cloud Continuum: From Edge Devices to Quantum Resources. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2026.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

March 21, 2026: Proposal Submission Deadline
April 4, 2026: Notification of Acceptance
May 23, 2026: Full Chapter Submission
June 27, 2026: Review Results Returned
July 25, 2026: Final Acceptance Notification
August 1, 2026: Final Chapter Submission

Inquiries

Ruchi Doshi, PhD Universidad Azteca ruchi.doshi@univ-azteca.edu.mx; doshiruchi18@gmail.com Albert Gyamfi, PhD Athabasca University alparties@gmail.com
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