Green Orchestration and Energy-Aware AI
グリーンオーケストレーションとエネルギー認識AI (AI 翻訳)
Hecker, Artur
🤖 gxceed AI 要約
日本語
本論文は、AIネイティブな6Gシステムにおける持続可能性の課題に取り組み、グリーンオーケストレーションによりAIワークロードの配置・実行をエネルギー状況に適応させる手法を提案する。インセンティブ機構と連携した協調制御により、システム全体の炭素排出削減を実現する。
English
This paper addresses sustainability challenges in AI-native 6G systems, proposing green orchestration that adapts AI workload placement and execution to real-time energy conditions. It introduces incentive mechanisms and federated coordination to achieve system-wide carbon footprint reduction across heterogeneous infrastructures.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本は6G研究とカーボンニュートラルを推進しており、通信事業者にとってAIワークロードのエネルギー効率化は重要。本研究成果は、ネットワーク全体の協調制御による持続可能性向上の指針となる。
In the global GX context
As 6G networks emerge globally, the energy consumption of AI workloads becomes critical. This paper provides a framework for carbon-aware orchestration, aligning with sustainability targets like net-zero emissions in telecom sectors.
👥 読者別の含意
🔬研究者:Federated orchestration mechanisms for sustainable 6G AI workloads offer a novel system-level perspective.
🏢実務担当者:Telecom operators can apply these concepts to reduce energy costs and carbon footprint in future network deployments.
📄 Abstract（原文）
The rapid transition of ICT towards AI-native operation is fundamentally reshaping the sustainability landscape of future 6G systems. While AI has long been seen as an enabler of decarbonisation through digitalisation, the proliferation of large-scale AI workloads, distributed training, and inference services now poses significant challenges in terms of energy consumption and carbon footprint. This joint talk brings together complementary perspectives from the EXIGENCE and NATWORK projects to address these challenges through coordinated, system-level approaches to sustainable operation. The contribution explores how green orchestration can align AI workload placement, partitioning, and execution with real-time energy conditions, network capabilities, and service constraints, enabling adaptive and carbon-aware operation across training and inference phases. Building on this, incentive mechanisms are introduced as AI-native tools to align individual user and stakeholder decisions with system-wide sustainability objectives, balancing performance, quality of experience, and environmental impact. At the system level, the talk highlights the need for federated orchestration across autonomous domains and stakeholders, enabling sustainable service delivery through interoperable data exchange, adaptive coordination, and cross-domain decision making. By combining green orchestration, incentive-driven optimisation, and federated coordination mechanisms, the joint contribution illustrates how AI-native 6G systems can move towards truly operationally sustainable architectures that scale across heterogeneous infrastructures and organisational boundaries. Presentation done at EuCNC & 6G Summit 2026 - Workshop 11: "Sustainable by Design, Sustainable in Operation: The 6G Perspective"
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20721390first seen 2026-06-17 04:14:57 · last seen 2026-06-26 04:24:58
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