How bad are the rogues' impact on enterprise 802.11 network performance?
In this paper, we describe the design and implementation of an automated 802.11 wireless network diagnostic system called Shaman. Since the end-to-end performance of user traffic is some combination of factors across all network layers, Shaman incorporates comprehensive, cross-layer models of 802.11 network behavior and performance. These models include broadband interference at the physical layer, perpacket link layer media access delays and losses, network layer device mobility and association management, and transport layer congestion and flow control. No one anomaly, failure or interaction is singularly responsible for all network problems, and that a holistic analysis is necessary to cover the range of problems experienced in real networks. When users experience unsatisfactory performance at a particular time, they can query Shaman for a diagnosis. Shaman will then profile a user’s traffic at that time, determine the network events that shape the performance profile, infer the causal sources of those events, and report the results to the user. We demonstrate the use of Shaman on an enterprise wireless network deployed in a university campus building, and illustrate the underlying analysis Shaman performs on real network trouble reports submitted by users of the enterprise network.