CAREER: Automating Wireless Network Management: Lessons from Managing Wireless LANs and Sensor Networks

University Of Connecticut, Storrs CT

Investigators

Abstract

Wireless networks, by virtue of their untethered nature, ease of set-up, and mobility support, have been heartily welcomed into our daily work and lives. Crucial to the continuing success and even wider deployment of wireless networks is automatic management of these networks. The goal of this research is to investigate two fundamental questions of fault management in wireless networks: (1) What are suitable management architectures and what data/measurements need to be collected for effective management? (2) What are suitable techniques for fault management? To be focused, this research mainly investigates two ?extreme? forms of wireless networks -- wireless LANs (WLANs) and sensor networks. More specifically, it proposes a novel management architecture and develops a series of fault management techniques for WLANs. It also develops a suite of diagnostic tools for static and mobile sensor networks, respectively. The techniques for the various management tasks utilize statistical analysis, optimization, stochastic modeling, and machine learning techniques, and will be evaluated using a combination of analysis, simulation and experiments. Although necessarily focused on a subspace in the large realm of wireless network management, by synthesizing lessons learned from this subspace, this project aims to provide insights into wireless network management in general. The outcome of this project will greatly advance the state of the art in wireless network management, potentially impacting many aspects of our daily lives. The education plan includes developing one undergraduate lab course on WLANs, and one graduate-level course on wireless network measurement and inference.