Computer Science Thesis Proposal
— 10:30am
Location:
4405
-
Reddy Conference Room, Gates Hillman 4405
Speaker:
YIGE HONG
,
Ph.D. Student, Computer Science Department, Carnegie Mellon University
https://www.cs.cmu.edu/~yigeh/
Understanding and Optimizing Complex Stochastic Systems Through Simple System
Complex stochastic systems that consist of a large number of interacting components naturally arise in various research domains, such as resource allocation in computing systems, congestion control in networks, wireless communication, machine maintenance, clinical trials, etc.
The scale of these systems, coupled with the interactions among the components, makes the dynamics within them highly complex. Consequently, decision-making problems for such stochastic systems are often highly challenging.
To understand and optimize these complex systems, we consider first solving a simple problem, and then converting the policy or performance bound obtained from the simple problem back to the complex problems. If the simple problem is properly constructed and the conversion is properly done, we can design a policy and prove its near-optimality.
In this thesis proposal, we will present several pieces of work that investigate some example problems through the related simple systems. These problems include restless bandits, stochastic bin-packing, optimal scheduling of the G/G/k/setup queueing model, and multiserver-job scheduling. We will also present three problems that we plan to study. Two of these problems are related to restless bandits; the third problem is about the G/G/n queueing model.
Thesis Committee:
Weina Wang (Chair)
Mor Harchol-Balter
Alan Scheller-Wolf
Jim Dai (Cornell University)
Qiaomin Xie (University of Wisconsin-Madison)
Yudong Chen (University of Wisconsin-Madison)
Information
In Person and Zoom Participation. See announcement.
For More Information:
In Person & Zoom