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Geerd-Dietger Hoffmann

Publications and source records attributed to Geerd-Dietger Hoffmann.

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Measure Once, Model Everywhere: Model-Based Per-Request Resource Consumption for HTTP

Recent proposals for HTTP-based sustainability disclosure focus on \textbf{what} environmental information should be transmitted at the protocol boundary, for example through response headers, but leave open the practical question of \textbf{how} such per-request values can be generated in realistic deployments. This paper addresses that implementation gap. We present a model-based approach for estimating resource consumption and $CO_2e$ per HTTP request without requiring fine-grained production power telemetry. The approach benchmarks endpoints offline under controlled conditions, derives compact endpoint-specific energy models from observable request features, and evaluates these models online at the HTTP server boundary. We implement this mechanism as an nginx extension that loads a JSON model registry and emits per-request metadata for energy, grid intensity, embodied emissions, and total request-level impact. We show that heterogeneous request classes can be represented with constant, linear, and piecewise models, and that the same approach extends to endpoints whose dominant cost driver is only visible at the application layer through inputs such as token counts. Our evaluation indicates that the approach is operationally feasible and introduces only low runtime overhead.

cs.CY

Green Metrics Tool: Measuring for fun and profit

The environmental impact of software is gaining increasing attention as the demand for computational resources continues to rise. In order to optimize software resource consumption and reduce carbon emissions, measuring and evaluating software is a first essential step. In this paper we discuss what metrics are important for fact base decision making. We introduce the Green Metrics Tool (GMT), a novel framework for accurately measuring the resource consumption of software. The tool provides a containerized, controlled, and reproducible life cycle-based approach, assessing the resource use of software during key phases. Finally, we discuss GMT features like visualization, comparability and rule- and LLM-based optimisations highlighting its potential to guide developers and researchers in reducing the environmental impact of their software.

cs.SE