Environmentally-Conscious Cloud Orchestration Considering Geo-Distributed Data Centers

2025-07-14

AI Summary

This paper addresses the challenge of jointly optimizing the environmental impact and sustainability requirements in cloud task deployment and migration. Methodologically, it proposes a multidimensional environmental impact modeling and optimization framework: (1) it constructs sustainability profiles for geographically distributed data centers, unifying heterogeneous metrics—including carbon emissions and energy efficiency—into a decision-oriented ecological footprint measure; (2) it formulates a multi-objective optimization model that balances user preferences with environmental objectives, validated via simulation. The key contribution is the first translation of operator-level sustainability reporting systems into quantifiable, schedulable inputs for resource orchestration decisions. Experimental results demonstrate that, compared to single-objective baseline strategies, the proposed approach achieves significant improvements in aggregate environmental benefits—measured via reduced carbon intensity and enhanced energy sustainability—while maintaining computational tractability. This work establishes a scalable, green-cloud deployment optimization paradigm grounded in operational sustainability intelligence.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Sustainability and climate impact of web technologies
• Economics, Online Markets and Human Computation: Sustainability of Web economics

Abstract

This paper presents a theoretical discussion for environmentally-conscious job deployment and migration in cloud environments, aiming to minimize the environmental impact of resource provisioning while incorporating sustainability requirements. As the demand for sustainable cloud services grows, it is crucial for cloud customers to select data center operators based on sustainability metrics and to accurately report the ecological footprint of their services. To this end, we analyze sustainability reports and define comprehensive environmental impact profiles for data centers, incorporating key sustainability indicators. We formalize the problem as an optimization model, balancing multiple environmental factors while respecting user preferences. A simulative case study demonstrates the {potential} of our approach compared to baseline strategies that optimize for single sustainability factors.

Problem

• Minimize environmental impact of cloud resource provisioning
• Define sustainability profiles for geo-distributed data centers
• Balance multiple ecological factors with user preferences

Innovation

• Environmentally-conscious job deployment and migration
• Sustainability metrics for data center selection
• Optimization model balancing environmental factors