• Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 20 Feb 2026] Title:Green by Design: Constraint-Based Adaptive Deployment in the Cloud Continuum View PDF HTML (experimental)Abstract:The environmental sustainability of Information Technology (IT) has emerged as a critical concern, driven by the need to reduce both energy consumption and greenhouse gas (GHG) emissions. • In the context of cloud-native applications deployed across the cloud-edge continuum, this challenge translates into identifying energy-efficient deployment strategies that consider not only the computational demands of application components but also the environmental impact of the nodes on which they are executed. • Generating deployment plans that account for these dynamic factors is non-trivial, due to fluctuations in application behaviour and variations in the carbon intensity of infrastructure nodes. • In this paper, we present an approach for the automatic generation of deployment plans guided by green constraints. • These constraints are derived from a continuous analysis of energy consumption patterns, inter-component communication, and the environmental characteristics of the underlying infrastructure. • This paper introduces a methodology and architecture for the generation of a set of green-aware constraints that inform the scheduler to produce environmentally friendly deployment plans.
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- Summary
A new approach for environmentally‑aware cloud‑native application deployment has been proposed, targeting the cloud‑edge continuum. The method automatically generates “green” constraints-derived from real‑time monitoring of energy consumption, inter‑component communication, and the carbon intensity of infrastructure nodes-to guide a scheduler toward energy‑efficient placement. Constraints are continuously learned and updated, enabling adaptive, energy‑aware orchestration that responds to fluctuating application workloads and varying node emissions. Validation on realistic deployment scenarios demonstrates that the technique can reduce overall energy usage and associated greenhouse‑gas emissions, offering a practical pathway for greener IT operations.
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