Towards a Sustainable Age of Information Metric: Carbon Footprint of Real-Time Status Updates

2026-02-12

AI Summary

This work addresses the limitation of traditional Age of Information (AoI) metrics, which neglect the carbon footprint associated with status updates and thus fall short in supporting green communication design. For the first time, carbon emissions are integrated into the AoI optimization framework, yielding a carbon-aware real-time status updating model that jointly optimizes scheduling policies and signal-to-noise ratio (SNR) under dynamic carbon intensity constraints. Leveraging M/M/1 and M/M/1* queueing models, closed-form expressions for average AoI are derived under both fixed and time-varying carbon intensity scenarios. The analysis reveals a non-trivial trade-off between AoI and carbon emissions: minimizing AoI does not necessarily reduce carbon footprint, and dynamic carbon intensity significantly impacts achievable information freshness. These insights provide a theoretical foundation and practical guidance for designing low-carbon real-time communication systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Agent Communication
• Constraint Satisfaction and Optimization: Constraint Optimization

Application Category

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

Abstract

The timeliness of collected information is essential for monitoring and control in data-driven intelligent infrastructures. It is typically quantified using the Age of Information (AoI) metric, which has been widely adopted to capture the freshness of information received in the form of status updates. While AoI-based metrics quantify how timely the collected information is, they largely overlook the environmental impact associated with frequent transmissions, specifically, the resulting Carbon Footprint (CF). To address this gap, we introduce a carbon-aware AoI framework. We first derive closed-form expressions for the average AoI under constrained CF budgets for the baseline $M/M/1$ and $M/M/1^*$ queuing models, assuming fixed Carbon Intensity (CI). We then extend the analysis by treating CI as a dynamic, time-varying parameter and solve the AoI minimization problem. Our results show that minimizing AoI does not inherently minimize CF, highlighting a clear trade-off between information freshness and environmental impact. CI variability further affects achievable AoI, indicating that sustainable operation requires joint optimization of CF budgets, Signal-to-noise Ratio (SNR), and transmission scheduling. This work lays the foundation for carbon-aware information freshness optimization in next-generation networks.

Problem

• Age of Information
• Carbon Footprint
• Environmental Impact
• Information Freshness
• Sustainable Communication

Innovation

• Carbon-aware Age of Information
• Carbon Footprint
• Time-varying Carbon Intensity
• Sustainable Networking
• Information Freshness Optimization