EcoKube: Simulating Carbon-Aware Scheduling Policies in Heterogeneous Edge-Cloud Environments

2026-07-10

AI Summary

This study addresses the lack of reproducible evaluation frameworks for assessing the sustainability of carbon-aware scheduling strategies in heterogeneous edge-cloud environments. To bridge this gap, we propose the first reproducible evaluation architecture supporting heterogeneous federated edge-cloud topologies, integrating an event-driven deterministic simulator, a policy hook mechanism, and heterogeneity-aware reference policies, all compatible with the Kubernetes scheduler interface. The framework holistically accounts for grid carbon intensity, power usage effectiveness (PUE), and hardware heterogeneity. Through experiments with synthetic batch workloads, we demonstrate that our approach significantly outperforms the default Kubernetes scheduler as well as state-of-the-art strategies such as KEIDS and TOPSIS/KCSS in reducing carbon emissions.

Abstract

Energy demand from cloud and edge computing is rising rapidly, with AI workloads further intensifying electricity use and associated carbon emissions. In hybrid edge-cloud settings, sustainability impact depends on time- and location-varying grid Carbon Intensity (CI), site Power Usage Effectiveness (PUE), and heterogeneous hardware characteristics. Existing carbon-aware work explores solutions such as temporal elasticity, spatio-temporal workload shifting, and carbon-aware placement across distributed sites. However, these solutions do not provide a consistent and reproducible workflow for evaluating sustainability-aware scheduling policies on heterogeneous, federated edge-cloud topologies. We present EcoKube: a configurable simulation framework for the reproducible evaluation of sustainability-aware scheduling policies in heterogeneous edge-cloud environments. The framework includes an event-driven deterministic simulator, policy hooks, and a heterogeneity-aware reference policy. We evaluate the framework with synthetic batch workloads, comparing the reference policy against the default Kubernetes scheduler, KEIDS, and TOPSIS/KCSS. The contribution is architectural and experimental: EcoKube provides a reproducible way to compare sustainability-aware policies before deployment.

Problem

• carbon-aware scheduling
• heterogeneous edge-cloud
• sustainability evaluation
• reproducible simulation
• workload placement

Innovation

• carbon-aware scheduling
• heterogeneous edge-cloud
• reproducible simulation
• sustainability-aware policies
• EcoKube