# Sustainability-Aware Workload Shifting Beyond Carbon Intensity

- Institution: CERN
- Speaker: Geerd-Dietger Hoffmann
- Year: 2026
- Language: English
- Subjects: Mathematics, Business and management
- Source: [CERN](https://videos.cern.ch/record/3025566)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Time- and location-shifting of computational workloads is widely proposed to reduce data-centre emissions by exploiting variation in electricity carbon intensity. However, CO$_2$-only optimization can shift burdens to places where impacts are experienced locally, such as water withdrawals in stressed basins, worsened air-pollution exposure, and increased stress on constrained grids. We present Orca, a sustainability-aware workload shifting framework that jointly considers global climate impacts and heterogeneous local criteria. Orca integrates region- and time-dependent signals for carbon, water-stress--weighted water use, air-pollution exposure proxies, and grid-stress indicators, and formulates scheduling as a multi-objective optimization problem. Using Pareto analysis, preference weighting, and optional impact caps, Orca exposes and mitigates trade-offs between emissions reduction and local burdens. A three-region case study shows that CO$_2$-optimal shifting can worsen local outcomes, while Orca produces context-sensitive schedules that better balance global and local sustainability objectives.

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## Lectures

1. [Sustainability-Aware Workload Shifting Beyond Carbon Intensity](https://invisiblenetwork.ai/learn/cern/3025566/37b8f95b0866), 29 min (CERN's player)