Optimizing Water Efficiency in Distributed Data Centers

The number and scale of data centers explode with the dramatically surging demand for cloud computing services, resulting in huge electricity consumption as well as an enormous impact on sustainability. While numerous efforts have been dedicated to decreasing the carbon footprint of data centers, there is a surprising and also embarrassing lack of attention to the enormity of data center water consumption despite its emergence as a critical concern for future sustainability. In this paper, we take the first step towards the data center water efficiency. We first identify two characteristics of data center water efficiency: water efficiency varies by location and also over time. Then, by exploiting these characteristics, we propose a novel geographical load balancing (GLB) algorithm, called GLB for Water Sustainability (GLB-WS), which dynamically schedules workloads to water-efficient data centers for improving the overall water usage effectiveness (an emerging metric for quantifying data center water efficiency) while satisfying the electricity cost constraint. We also perform a trace-based simulation study to validate the analysis. The result shows that compared to the state-of-the-art cost-minimizing GLB, GLB-WS significantly improves the water efficiency (by 60%) and reduces the water consumption (by 51%).