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Title: Control plane for situation-awareness applications on geo-distributed resources
Enrique Saurez
Ph.D. Candidate
School of Computer Science
College of Computing
Georgia Institute of Technology
https://www.cc.gatech.edu/~esaureza/
Date: Friday, April 22, 2022
Time: 1:00 pm – 3:00 pm (ET)
Location (virtual): join here
Committee:
Dr. Kishore Ramachandran (Advisor, School of Computer Science, Georgia Institute of Technology)
Dr. Mostafa Ammar (School of Computer Science, Georgia Institute of Technology)
Dr. Ada Gavrilovska (School of Computer Science, Georgia Institute of Technology)
Dr. Alexandros Daglis (School of Computer Science, Georgia Institute of Technology)
Dr. Bharath Balasubramanian (Google)
Abstract:
Situation-awareness applications generate actionable knowledge from sensor and user data. Two trends are unlocking new situation-awareness applications: geo-distributed resources and pervasive sensors. Geo-distributed computing infrastructure is now available worldwide, ranging from multi-region cloud deployments to newer 5G edge deployments. On the other hand, pervasive sensors have seen a boom, with examples like geo-distributed camera deployments, smart cities, and users' gadgets (smartphones). Having computational resources closer to the data sources improves the response time and the efficient use of the available resources. Geo-distributed resources reduce the physical distance to the data source, cutting the time it takes to transmit, filter, and process information, reducing unnecessary data transmission. However, efficient management of resources is challenging for densely geo-distributed resources while also providing spatio-temporal context and latency quality-of-service objectives.
This dissertation proposes a control plane that makes three contributions for efficiently managing situation awareness applications running on geo-distributed computational resources:
