Data analysis, visualization and knowledge discovery in sustainable data centers

Abstract

A significant amount of energy consumption is now attributed to data centers due to their ever increasing numbers, size and power densities. Thus, there are efforts focused at making a data center more sustainable by reducing its energy consumption and carbon footprint. This requires an end-to-end management approach with requirements derived from service level agreements (SLAs) and a flexible infrastructure that can be closely monitored and finely controlled. The infrastructure can then be manipulated to satisfy the requirements while optimizing for sustainability metrics and total cost of operations. In this paper, we explore the role of data analysis, visualization and knowledge discovery techniques in improving the sustainability of a data center. We present use cases from a large, sensor-rich, state-of-the-art data center on the application of these techniques to the three main sub-systems of a data center, namely, power, cooling and compute. Furthermore, we provide recommendations for where these techniques can be used within these sub-systems for improving sustainability metrics of a data center.