My Research Interests
I'm currently working on energy-efficient scheduling of ML Algorithms on the edge as a part of GWU Cloud Systems Lab (https://github.com/gwcloudlab). The following are my research interests.
Kubernetes
eBPF
Operating Systems
Containers
Linux Kernel
Networking
Container Network Interface (CNI)
Energy Efficiency
Benchmarking
Publications
Towards Sustainable Machine Learning with Serverless at the Edge
IEEE CloudSummit 2025
Energy consumption has received significant attention in data centers and edge environments. The growing demands of AI/ML workloads, which are highly computational and energy-intensive, further increase the importance of energyaware design. Although energy consumption has been widely studied from hardware and software perspectives to optimize it in cloud and edge environments, the rise of serverless computing presents new challenges for applying its metrics within adaptive and sustainable systems. Our research analyzes function-level energy consumption to support an adaptive, energy-aware system. This poster compares energy usage across different workloads, highlighting how application characteristics influence total energy consumption. Building on these insights, we propose a framework that enables intelligent function selection based on energy and performance trade-offs.
eBPF-Based Intrusion Prevention System for Database Servers
IEEE CloudSummit 2024
eBPF (Extended Berkeley Packet Filter) is a powerful technology enabling the execution of sandboxed programs at the kernel level. This paper investigates its potential to implement security measures for critical database statements, safeguarding them from various threats. These threats can include malicious actors, compromised containers, or even insider attempts to tamper with production data.