Call for Chapters: Green Computing Techniques for Eco-Friendly Data Center Management

Editors

Jitendra Pandey, Middle East College, Oman

Call for Chapters

Proposals Submission Deadline: June 18, 2026
 Full Chapters Due: August 20, 2026
 Submission Date: August 20, 2026

Introduction

The transformation of the global digital landscape has positioned data centers as the central nervous system of modern civilization. However, this rapid expansion has come with a significant environmental cost. As we move deeper into the decade, the dual challenge of meeting skyrocketing computational demands fueled by generative AI and big data while adhering to strict net-zero targets has never been more pressing.

The Sustainability Imperative
Data centers are among the most energy-intensive building types, consuming vast amounts of electricity for both computation and the critical cooling systems required to maintain hardware integrity. In the current era, "business as usual" is no longer viable. The concept of Green Computing has evolved from a niche corporate social responsibility (CSR) goal into a fundamental engineering requirement. It encompasses a holistic approach to the lifecycle of IT systems, focusing on energy efficiency, renewable energy use, and electronic waste reduction.
From Efficiency to Innovation
Achieving an eco-friendly data center requires more than just high-efficiency power supplies. It demands an integrated strategy that spans multiple layers of technology:
Algorithmic Efficiency: Developing "green" software and AI models that require fewer computational cycles to achieve the same results.
Intelligent Orchestration: Utilizing machine learning to predict workload spikes and dynamically consolidate resources, allowing idle hardware to enter low-power states.
Infrastructure Synergy: Beyond the server rack, modern data centers are integrating with circular economies using waste heat for local heating systems and transitioning toward 24/7 carbon-free energy (CFE).

The Scope of this Work
This book, Green Computing Techniques for Eco-Friendly Data Center Management, serves as a comprehensive guide to this critical transition. By exploring the latest advancements in thermal management, AI-driven resource allocation, and sustainable hardware design, it provides a roadmap for building a digital infrastructure that supports innovation without compromising our planet's health. It addresses the technical, ethical, and regulatory dimensions of digital sustainability, offering insights for researchers and practitioners dedicated to the "Green Cloud" revolution.

Objective

Green Computing Techniques for Eco-Friendly Data Center Management is designed to serve as a high-level synthesis of theory and practice, addressing the critical gap between conceptual sustainability and large-scale industrial application.

The following objectives outline what this book intends to accomplish and how it advances the current state of research in the field:
1. Codifying a Multidisciplinary Framework
Current research often treats data center cooling, software optimization, and hardware design as isolated silos. This book intends to unify these domains into a single, cohesive framework. By integrating Human-in-the-Loop AI with automated infrastructure management, it moves beyond simple automation toward a more nuanced, "intelligent" sustainability model that respects both technical constraints and professional judgment.
2. Advancing "Digital Sobriety" through Quantitative Metrics
While metrics like Power Usage Effectiveness (PUE) are industry standard, they often fail to capture the full environmental impact of a data center. This work further research by proposing and exploring more granular KPIs, such as:

Carbon Usage Effectiveness (CUE): Measuring the direct carbon footprint of energy consumed.
Water Usage Effectiveness (WUE): Addressing the significant cooling-related water consumption in arid and semi-arid regions.
Energy-to-Solution (EtS): Evaluating the total energy cost of specific computational tasks, particularly in the training of large language models.
3. Bridging the Gap Between AI Innovation and Energy Ethics
As the demand for AI grows, so does its energy consumption. This book accomplishes a critical task by documenting the ethical integration of AI within computing infrastructures. It explores how AI can be the solution rather than just the cause of energy inefficiency through predictive thermal management and workload consolidation techniques. This provides a roadmap for researchers to develop AI literacy that prioritizes environmental responsibility.
4. Exploring the "Green Cloud" Lifecycle
Current research is often focused purely on the operational phase of a data center. This book adds value by extending the discussion to the entire Lifecycle Assessment (LCA), including:
Circular Economy Principles: Repurposing hardware and managing e-waste.
Sustainable Sourcing: The integration of 24/7 carbon-free energy sources.
Green Refactoring: Providing methodologies for developers to write energy-efficient code as a primary performance metric.
5. Serving as a Catalyst for Global Policy and Standards
By consolidating case studies and emerging trends, this book aims to influence international standards for data center management. It provides evidence-based insights that can assist policymakers and academic leaders in drafting regulations for digital sustainability, ensuring that the "RAPID" revolution of digital transformation does not come at the expense of ecological stability.
Contribution to the Field
Ultimately, this work further research by moving the conversation from "how to save energy" to "how to design for sustainability." It shifts the paradigm from reactive power management to a proactive, "green-by-design" philosophy, providing a foundational text for the next generation of researchers and practitioners in sustainable computing.

Target Audience

Green Computing Techniques for Eco-Friendly Data Center Management is specifically curated for a multidisciplinary audience situated at the intersection of information technology, environmental science, and corporate governance. The research contained within is designed to be accessible to those developing the technology, those managing the infrastructure, and those drafting the policies that govern them.

The following groups will benefit most from this work:
1. Academic Researchers and Students
Computer Scientists & AI Specialists: Scholars exploring "Green AI" and energy-efficient algorithms will find a wealth of data on minimizing the computational cost of large-scale models.
Environmental Engineers: Students and faculty focusing on sustainable infrastructure and lifecycle assessments (LCA) will benefit from the technical benchmarks regarding cooling and waste-heat recovery.
Information Systems Scholars: Those researching the socio-technical impacts of digital transformation and digital sobriety.
2. Data Center Professionals and IT Practitioners
Infrastructure & Operations (I&O) Leaders: CTOs and data center managers looking for actionable strategies to reduce Power Usage Effectiveness (PUE) and operational costs.
System Architects & DevOps Engineers: Professionals interested in "Green Refactoring" and energy-aware resource orchestration to optimize server utilization.
Sustainability Officers: Corporate leaders tasked with meeting Net-Zero targets and managing Scope 2 and Scope 3 emissions within the IT sector.
3. Policy Makers and Regulatory Bodies
Government Officials: Practitioners involved in drafting digital economy strategies and environmental regulations for the tech industry.
Standardization Organizations: Individuals working on global benchmarks for carbon-neutral computing and green certifications (such as LEED or Energy Star).
Public Procurement Officers: Those responsible for the sustainable sourcing of data hosting and cloud services for governmental institutions.
4. Industry Stakeholders and Investors
Hardware Manufacturers: R&D teams designing the next generation of energy-efficient CPUs, GPUs, and cooling hardware.
Renewable Energy Providers: Companies looking to understand the unique energy demands and 24/7 carbon-free energy (CFE) requirements of the "Green Cloud."
ESG Investors: Analysts seeking a deeper understanding of the technical feasibility of sustainability claims made by hyperscalers and tech giants.
How They Will Benefit
Bridging Theory and Practice: Readers will gain a clear roadmap for moving from high-level sustainability goals to granular, technical implementation.
Decision Support: The book provides evidence-based frameworks to justify investments in green technology, balancing initial capital expenditure (CapEx) against long-term operational savings (OpEx).
Future-Proofing: By highlighting emerging trends in AI and liquid cooling, the research prepares the audience for the regulatory and environmental challenges of the next decade.

Recommended Topics

To ensure this book achieves high visibility and impact in multidisciplinary publications (such as Nature Sustainability, IEEE Transactions, or MDPI Sustainability), we should emphasize the intersection of environmental science, artificial intelligence, and socio-economic policy.
The following expanded list incorporates high-interest multidisciplinary topics that attract diverse citations:
🌍 The Nexus of AI, Energy, and Climate
Carbon-Aware Computing: Shifting computational workloads geographically and temporally to follow the availability of "clean" (wind/solar) energy on the grid.
Green AI vs. Red AI: A critical analysis of the "cost of accuracy" balancing the performance of Large Language Models (LLMs) against the massive energy investment required for training.
Predictive Grid Integration: Using AI to turn data centers from passive energy consumers into active participants in "Smart Grids," helping to stabilize the power grid during fluctuations.
💧 Natural Resource & Lifecycle Management
The Water-Energy Nexus: Addressing the hidden "water footprint" of data center cooling, particularly the impact on local ecosystems and drought-prone regions.
Circular Economy for Digital Infrastructure: Research into the "cradle-to-cradle" lifecycle recovering rare earth metals from servers and repurposing "retired" hardware for less demanding edge computing tasks.
Heat-as-a-Product: Technical and economic models for "District Heating," where data center waste heat is sold as a utility to heat homes, greenhouses, or swimming pools.
📜 Socio-Technical & Regulatory Frameworks
Digital Sobriety & Ethics: Exploring the social responsibility of "sufficient" computing questioning whether every data-intensive application provides enough social value to justify its carbon cost.
Global Policy Harmonization: Comparative studies on the EU’s Energy Efficiency Directive (EED) versus other international standards, and their impact on global cloud providers.
Transparency and Reporting Standards: Developing unified, audit-proof frameworks for reporting Scope 3 emissions (indirect emissions from the supply chain) in the tech sector.
🛠️ Cross-Domain Technical Innovations
Neuromorphic & Bio-Inspired Computing: Research into energy-efficient hardware architectures that mimic the human brain’s low-power processing capabilities.
Sustainable Edge-Cloud Orchestration: Minimizing data movement and thus energy waste by processing data at the source (the "Edge") rather than transmitting it to centralized hubs.
Advanced Material Science in Cooling: The use of phase-change materials (PCMs) and nano-enhanced coolants to radically improve thermal conductivity over traditional air/water systems.
Why these are "Multidisciplinary Favorites":
Crossover Appeal: They attract interest from Environmentalists (water/carbon), Economists (heat-as-a-product/circular economy), and Engineers (neuromorphic computing/grid integration).
Addressing "Hot" Topics: The "Carbon Footprint of AI" is currently among the most-cited topics in both technical and general science journals.
Holistic Problem Solving: Modern reviewers favor "Systems Thinking" over narrow technical fixes; these topics look at the entire ecosystem.ence for the regulatory and environmental challenges of the next decade.

Submission Procedure

Researchers and practitioners are invited to submit on or before June 18, 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 July 2, 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 August 20, 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, Green Computing Techniques for Eco-Friendly Data Center Management. 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 2027.

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

June 18, 2026: Proposal Submission Deadline
July 2, 2026: Notification of Acceptance
August 20, 2026: Full Chapter Submission
September 24, 2026: Review Results Returned
October 22, 2026: Final Acceptance Notification
October 29, 2026: Final Chapter Submission

Inquiries

Dr Jitendra Pandey
Middle East College
jitenndra@gmail.com
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