MOJO: a distributed physical layer anomaly detection system for 802.11 WLANs

ABSTRACT

Deployments of wireless LANs consisting of hundreds of 802.11 access points with a large number of users have been reported in enterprises as well as college campuses. However, due to the unreliable nature of wireless links, users frequently encounter degraded performance and lack of coverage. This problem is even worse in unplanned networks, such as the numerous access points deployed by homeowners. Existing approaches that aim to diagnose these problems are inefficient because they troubleshoot at too high a level, and are unable to distinguish among the root causes of degradation. This paper designs, implements, and tests fine-grained detection algorithms that are capable of distinguishing between root causes of wireless anomalies at the depth of the physical layer. An important property that emerges from our system is that diagnostic observations are combined from multiple sources over multiple time instances for improved accuracy and efficiency.

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication

General Terms:
Algorithms, Measurement, Performance

Keywords:
anomaly detection, self-healing, wireless networks