# SLA-Constrained Carbon-Aware Routing in Geo-Distributed Serverless Clouds

arXiv: https://arxiv.org/abs/2607.22806 · HTML: https://mlsanity.com/paper/2607.22806/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 22 references that are in the map.
- First posted on arXiv 24 Jul 2026.

## Builds on (most cited first, 5 of 5)

- [Carbon Explorer: A Holistic Approach for Designing Carbon Aware Datacenters](https://mlsanity.com/paper/2201.10036/) (2022)
- [CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency](https://mlsanity.com/paper/2302.08681/) (2023)
- [CASPER: Carbon-Aware Scheduling and Provisioning for Distributed Web Services](https://mlsanity.com/paper/2403.14792/) (2024)
- [EcoLife: Carbon-Aware Serverless Function Scheduling for Sustainable Computing](https://mlsanity.com/paper/2409.02085/) (2024)
- [GreenWhisk: Emission-Aware Computing for Serverless Platform](https://mlsanity.com/paper/2409.03029/) (2024)

## Abstract (arXiv)

Modern cloud deployments distribute applications across multiple geographic regions, yet standard routing mechanisms prioritize latency while ignoring the fluctuating carbon intensity of local power grids. Latency-driven routing incurs avoidable carbon emissions, particularly when cleaner regions are within acceptable latency bounds. The proposed model formulates the carbon-aware serverless routing problem as a constrained optimization over geo-distributed cloud regions and introduces an SLA-constrained carbon-aware routing policy that achieves optimal carbon reduction within the SLA-feasible region, evaluated using real carbon intensity measurements across 5 primary AWS deployments. Experimental results show that the proposed policy achieves up to 46.8% carbon reduction while maintaining zero SLA violations across all evaluated thresholds. The system reduces carbon by an average of 27.4% under mixed workloads, and the routing overhead is very low (less than 0.02% of total request latency). A scalability study across 12 AWS regions spanning 6 continents demonstrates that average carbon savings increase from 27.4% to 47.5% as routing flexibility expands under mixed workloads. The proposed work contributes to SDG 13 (Climate Action) and SDG 7 (Affordable and Clean Energy) by enabling low-carbon routing decisions. These results indicate that cloud systems can achieve significant carbon savings without compromising user experience.