Automating cross-layer diagnosis of enterprise wireless networks

Abstract

Modern enterprise networks are of sufficient complexity that even simple faults can be difficult to diagnose - let alone transient outages or service degradations. Nowhere is this problem more apparent than in the 802.11-based wireless access networks now ubiquitous in the enterprise. In addition to the myriad complexities of the wired network, wireless networks face the additional challenges of shared spectrum, user mobility and authentication management. Not surprisingly, few organizations have the expertise, data or tools to decompose the underlying problems and interactions responsible for transient outages or performance degradations. In this paper, we present a set of modeling techniques for automatically characterizing the source of such problems. In particular, we focus on data transfer delays unique to 802.11 networks - media access dynamics and mobility management latency. Through a combination of measurement, inference and modeling we reconstruct sources of delay - from the physical layer to the transport - layer as well as the interactions among them. We demonstrate our approach using comprehensive traces of wireless activity in the UCSD Computer Science building.