Throughput-optimal opportunistic scheduling in the presence of flow-level dynamics

Shihuan Liu; Lei Ying; R. Srikant

doi:10.1109/TNET.2010.2100826

Throughput-optimal opportunistic scheduling in the presence of flow-level dynamics

Shihuan Liu, Lei Ying, R. Srikant

Arizona State University

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

We consider multiuser scheduling in wireless networks with channel variations and flow-level dynamics. 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 paper, we propose a new algorithm, called Workload-based Scheduling with Learning, which is provably throughput-optimal, requires no prior knowledge of channels and user demands, and performs significantly better than previously suggested algorithms.

Original language	English (US)
Article number	5696792
Pages (from-to)	1057-1070
Number of pages	14
Journal	IEEE/ACM Transactions on Networking
Volume	19
Issue number	4
DOIs	https://doi.org/10.1109/TNET.2010.2100826
State	Published - Aug 1 2011

Keywords

Flow-level dynamics
throughput-optimal scheduling
wireless cellular networks

ASJC Scopus subject areas

Software
Computer Science Applications
Computer Networks and Communications
Electrical and Electronic Engineering

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