ENABLING ENERGY AND WATER SUSTAINABILITY THROUGH OUT-OF-BAND EMI SENSING AND INFRASTRUCTURE MODELING
Graduation Semester and Year
Summer 2025
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computer Engineering
Department
Computer Science and Engineering
First Advisor
Mohammad Atiqul Islam
Second Advisor
VP Nguyen
Third Advisor
Jia Rao
Fourth Advisor
Ming Li
Abstract
As demand for Internet and cloud services surges, data centers have emerged as critical infrastructure—but they are also among theworld’s most energy- andwater-intensive facilities. Effective power management, particularly at the server level, is essential for improving efficiency, reliability, and sustainability. However, server-level power monitoring remains uncommon due to the high cost of hardware instrumentation and the intrusiveness of software-based solutions, especially in shared colocation environments. My research introduces a novel, low-cost, and non-intrusive method for server-level power monitoring using conducted electromagnetic interference (EMI). By analyzing EMI signals captured from higher levels in the power distribution network, this approach estimates individual server power consumption without direct server access. The method is scalable, retrofittable, and better suited to colocation scenarios than other side-channel techniques, offering improved signal separation and stability. Building on this framework, I extended EMI-based sensing to the residential energy domain. Utilities struggle to monitor behind-the-meter (BTM) distributed energy resources
(DERs), such as rooftop solar, due to limited visibility into customer-owned systems. I demonstrate how EMI signatures from grid-tied inverters can be used to passively monitor real-time solar generation from the utility side—without invading customer privacy or modifying infrastructure. Finally,mywork addresses the overlookedwater footprint of data centers. I developed a large-scale dataset capturing both direct (cooling systems) and indirect (electricity generation) water usage across U.S. regions from 2019–2023. This resource supports data-driven water-aware workload scheduling and sustainable infrastructure planning. Together, these contributions advance the state of cyber-physical systems by enabling energy- and water-aware operation through EMI-based sensing and infrastructure modeling, with broad implications for sustainable computing and utility monitoring.
Keywords
EMI, AI, Solar, Water footprint, Power monitoring, PFC, Side channel
Disciplines
Hardware Systems | Other Computer Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Gupta, Pranjol Sen, "ENABLING ENERGY AND WATER SUSTAINABILITY THROUGH OUT-OF-BAND EMI SENSING AND INFRASTRUCTURE MODELING" (2025). Computer Science and Engineering Dissertations. 418.
https://mavmatrix.uta.edu/cse_dissertations/418