August 15, 2025 Animesh Dangwal — UCSB
Edge computing distributes cloud functionality to task specific, resource-constrained and low-cost devices operating at data collection points, for low latency, low power and cost effective compute. This coordination requires redesigning cloud paradigms to either communicate or compute over the edge. Rather than adapting cloud technologies for edge constraints, what if we reconfigure the edge environment to enable seamless adoption of cloud research with minimal modifications to existing algorithms and runtimes? In this work, we define this transformation by modelling an edge rack analogous to server racks in the cloud to construct a high performance edge cluster. This allows us to explore the impact of cloud scheduling and runtime paradigms to the edge using metrics such as temperature, voltage fluctuations and maintenance cost such as cooling. In this talk, I present my work on exploring scheduling principles for such giant edge clusters, using UCSB’s (and unofficially the world’s) largest Raspberry Pi cluster, and reveal how metric fluctuations are magnified for edge workloads.
Animesh Dangwal is a 5th year PhD student in the Computer Science department at UC Santa Barbara, working with Professor Chandra Krintz and Professor Rich Wolski. His research interests are in edge, serverless computing and distributed systems. His recent work has been in bridging the gap between the edge and cloud by developing flexible, and sustainable deployments at the edge for diverse workloads and hardware.