Events Calendar

Throughput Optimal Opportunistic Scheduling in the Presence of Flow-Level Dynamics

Abstract:
Multiuser scheduling is one of the core challenges in wireless communications. Due to channel
fading and wireless interference, scheduling algorithms need to dynamically allocate resources
based on both the demands of the users and the channel states to maximize network throughput.
Recently, it has been shown that the MaxWeight algorithm, which is throughput-optimal in
networks with a fixed number of users, fails to achieve the maximum throughput in the presence
of flow-level dynamics. In this talk, we introduce a new class of scheduling algorithms, called
workload-based scheduling with learning, which are provably throughput-optimal, require no
prior knowledge of channels and user demands, and perform significantly better than previously
suggested algorithms.
Dr. Lei Ying
Assistant Professor
Iowa State University
Bio:
Lei Ying received his B.E. degree from Tsinghua University, Beijing, in 2001, his M.S. and
Ph.D in Electrical Engineering from the University of Illinois at Urbana-Champaign in 2003 and
2007, respectively. During Fall 2007, he worked as a Postdoctoral fellow in the University of
Texas at Austin. He is currently an Assistant Professor at the Department of Electrical and
Computer Engineering at Iowa State University. His research interest is broadly in the area of
communication networks, including wireless communication networks, wireless sensor
networks, P2P networks, and distributed algorithms. He received a Young Investigator Award
from the Defense Thread Reduction Agency (DTRA) in 2009.
Host: Bhaskar Krishnamachari

Location: Frank R. Seaver Science Center (SSC) - 319

Audiences: Everyone Is Invited

Contact: Shane Goodoff