Utilizing Conducted Electromagnetic Interference (EMI) for Low-Cost Server-Level Power Monitoring in Data Centers

University Of Texas At Arlington, Arlington TX

Investigators

Abstract

The increasing dependence on the Internet and cloud computing has made data centers indispensable in modern society. However, operating these data centers requires a massive amount of electricity that contributes to the global energy crisis. Therefore, managing data center power usage to achieve energy efficiency is critical for a sustainable cyberinfrastructure. Towards that, server power monitoring plays a crucial role by offering valuable insights for exploring the optimization potential in data center operation. Moreover, fine-grained power monitoring can be vital in safeguarding data centers from outages and downtimes due to overloading and identifying anomalous server behaviors or malicious cyberattacks. However, server-level power monitoring has not been widely adopted due to the high cost associated with dedicated power meters at every server. This project breaks the cost barrier by developing a novel low-cost server-level power monitoring system that does not need dedicated power sensors at every server. Instead, it extracts multiple servers' power consumption data from single-point voltage measurements of the data center power distribution system. Beyond cost savings, the fine granular power monitoring achieved through this project can have a far-reaching impact by motivating data center operators to adopt more efficient and environment-friendly techniques. This project's research results and tools will be translated into educational materials for undergraduate and graduate courses. The project will also incorporate research activities for students through lab visits and summer internships. The enabling insight for this project's novel power metering approach is that the power factor correction (PFC) circuits in the server power supply reveal their power usage information into the data center power network through high-frequency (kHz level) conducted electromagnetic interference (EMI). The conducted EMIs from servers can be measured from the data center voltage for server-level power monitoring. However, there are several technical challenges to realizing a conducted EMI monitoring system in data centers. The generation and propagation of conducted EMI in a data center environment are not well understood and how the data center architecture and the environment affect the server EMI is unexplored. In addition, extracting many servers' power consumption data from a single sensor poses fundamental challenges of source separation. Lastly, high-frequency EMI extraction and source separation require extensive and high-precision computation, while developing a real-time and cost-effective sensing system is non-trivial. In light of these challenges, this project's research efforts are organized through three research thrusts. The goal of Thrust 1 is to bridge the knowledge gap in conducted EMI in data centers through foundational research into conducted EMI generation, propagation, and extraction. Thrust 2 focuses on developing novel source separation algorithms to extract server-level power from a single sensor. Thrust 3 develops computation and cost-effective sensor hardware and software tailored to real-time monitoring. This project contributes to the knowledge base of source separation techniques and efficient real-time sensor data processing. The project advances the foundational understanding of conducted EMI in data center power networks. Moreover, conducted EMI is generated by many different types of equipment requiring regulated power. Hence, this project's outcome can stimulate the development of novel techniques dealing with conducted EMI issues in other domains. To foster such developments, all experiment data, codes, and designs of this project will be made publicly available. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.