Carbon-Aware End-to-End Data Movement

Jacob Goldverg; Hasibul Jamil; Elvis Rodriguez; Tevfik Kosar

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arXiv · 2406.09650

Carbon-Aware End-to-End Data Movement

Jacob Goldverg·Hasibul Jamil·Elvis Rodriguez·Tevfik Kosar

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Abstract

The latest trends in the adoption of cloud, edge, and distributed computing, as well as a rise in applying AI/ML workloads, have created a need to measure, monitor, and reduce the carbon emissions of these compute-intensive workloads and the associated communication costs. The data movement over networks has considerable carbon emission that has been neglected due to the difficulty in measuring the carbon footprint of a given end-to-end network path. We present a novel network carbon footprint measuring mechanism and propose three ways in which users can optimize scheduling network-intensive tasks to enable carbon savings through shifting tasks in time, space, and overlay networks based on the geographic carbon intensity.

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BibTeX RIS

Jacob Goldverg, Hasibul Jamil, Elvis Rodriguez, Tevfik Kosar. 2024-06-14. Carbon-Aware End-to-End Data Movement. https://arxiv.org/abs/2406.09650

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