GRASS: Green Ranking of Autonomous SystemS

The rapid growth of the Internet has raised concerns about the carbon emissions linked to data transmission. Autonomous Systems (ASes), which make inter-domain routing decisions, influence how traffic moves through the network and, indirectly, where emissions are generated. Although carbon-aware routing is gaining interest, limited visibility into emission sources remains a key challenge. In this paper, we present GRASS (Green Ranking of Autonomous SystemS), a framework for estimating the CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> intensity of ASes based on their geographic distribution and the carbon efficiency of regional electricity grids. GRASS combines geolocation, routing, and carbon data to infer probabilistic location profiles and compute a CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> intensity score for each AS. Using GRASS, we analyze emission patterns across AS popularity tiers, and customer cone sizes, and assess the carbon intensity of AS-to-AS links based on associated organizations. Our results show that a small number of structurally central ASes and links account for a large fraction of total Internet-related emissions. We propose a novel approach to assessing the CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> intensity of ASes and their interconnections, offering insights that enable targeted interventions for greener network operations and routing policies.