Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters

TL;DR

This paper introduces LinTS, a novel carbon-aware scheduling framework that significantly reduces carbon emissions in inter-datacenter data transfers while maintaining deadlines, outperforming existing heuristics.

Contribution

LinTS is a new scheduling framework that optimizes inter-datacenter data transfers for lower carbon emissions with competitive performance.

Findings

Reduces carbon emissions by up to 66% compared to worst-case scenarios.

Achieves up to 15% emission reduction over existing solutions.

Maintains all deadline constraints during scheduling.

Abstract

Inter-datacenter communication is a significant part of cloud operations and produces a substantial amount of carbon emissions for cloud data centers, where the environmental impact has already been a pressing issue. In this paper, we present a novel carbon-aware temporal data transfer scheduling framework, called LinTS, which promises to significantly reduce the carbon emission of data transfers between cloud data centers. LinTS produces a competitive transfer schedule and makes scaling decisions, outperforming common heuristic algorithms. LinTS can lower carbon emissions during inter-datacenter transfers by up to 66% compared to the worst case and up to 15% compared to other solutions while preserving all deadline constraints.