Title: Optimization algorithms for network resource management
Speaker:Dongmei Zhao
Time: 10:00 AM, July 2, 2026
Venue: Room 834, Information Building,
School of Information Science and Engineering,
Southeast University
Abstract: Optimization problems in network traffic scheduling and resource management are often challenging due to uncertainty, nonconvexity, and large-scale decision spaces. In this talk, I will present mathematical algorithms developed to solve three such problems.
The first problem studies computation offloading over time-varying wireless channels and seeks the optimal offloading start time to satisfy task deadlines. A time-dilated absorbing Markov model is constructed, and optimal stopping theory for Markov decision processes is employed to derive the optimal offloading policy.
The second problem investigates synchronization between physical systems (PSs) and digital twins (DTs) under shared communication and computation resources. An integer optimization problem is formulated to select feature models that maximize synchronization accuracy subject to resource constraints. The problem is decomposed into multiple subproblems, each reducible to a modified knapsack problem, and solved using a polynomial-time approximation algorithm.
The third problem considers privacy-preserving channel resource sharing using federated optimization and digital twins. A mixed-integer continuous optimization problem is formulated and relaxed into a continuous problem. An approximate solution is then obtained through dependent rounding followed by re-optimization.
Bio: Dongmei Zhao received the Ph.D degree in Electrical and Computer Engineering from University of Waterloo, Waterloo, Ontario, Canada in June 2002. In July 2002 she joined the Department of Electrical and Computer Engineering at McMaster University, where she is a professor. She is currently an Associate Editor for the IEEE Internet of Things Journal and a Distinguished Lecturer of IEEE Vehicular Technology Society. Her recent research interests focus on autonomous networking and digital twins.
