Using Budgets to Reduce Application Emissions

2026-04-13

AI Summary

This work addresses the challenge of balancing emission constraints, operational cost, and service quality in dynamic power grids where carbon intensity varies over time. Traditional fixed emission rate strategies prove inadequate under such conditions. To overcome this limitation, the authors propose a time-window-based emission budgeting mechanism that replaces static rates, enabling applications to accrue emission allowances during low-carbon periods and flexibly consume them during high-carbon intervals. Integrated within a MAPE-K adaptive control architecture, the approach leverages real-time monitoring of grid carbon intensity and system power consumption to dynamically schedule resources while adhering to long-term emission caps. Simulations using six weeks of real-world data from Germany, France, and Poland demonstrate that the method improves task completion rates by up to 36% in volatile grids while matching the performance of existing approaches in stable grids, achieving effective co-optimization of emissions, cost, and performance.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

As carbon pricing mechanisms like the EU Emissions Trading System are set to increase prices of energy consumption, software architects face growing pressure to design applications that operate within financially predictable emission constraints. Existing approaches typically enforce rigid per-interval emission rates, which prove unsuitable in electrical grids with highly dynamic carbon intensity, which is common in grids with growing renewable energy adoption. We propose the use of emissions budgets, an approach that replaces fixed emission rates with time-bound budgets, enabling applications to dynamically save unused emission allowances during low carbon intensity periods and expend them during high carbon intensity periods. We describe emissions-aware applications using a MAPE-K feedback loop that continuously monitors application power consumption and grid carbon intensity, then adapts resource allocation through vertical scaling or migration to maintain long-term emission limits while maximizing performance. Through simulation using six weeks of real-world carbon intensity data from Germany, France, and Poland, we demonstrate that budget-based management improves task fulfillment by up to 36% in variable grids compared to fixed rates. Crucially, budgets achieve parity with fixed rates in stable grids, making them a safe replacement. We show that emissions budgets are a practical mechanism to balance environmental constraints, operational costs, and service quality when emissions directly translate to financial penalties.

Problem

• carbon intensity
• emissions budget
• software architecture
• carbon pricing
• dynamic grid

Innovation

• emissions budgets
• carbon intensity
• MAPE-K loop
• dynamic resource allocation
• green software architecture