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SCUBA: Focus and Context for Real-Time Mesh Network Health Diagnosis

Summary: SCUBA: Focus and Context
for Real-Time Mesh Network Health Diagnosis
Amit P. Jardosh, Panuakdet Suwannatat, Tobias H¨ollerer, Elizabeth M. Belding,
and Kevin C. Almeroth
Department of Computer Science, UC Santa Barbara
Abstract. Large-scale wireless metro-mesh networks consisting of hundreds of
routers and thousands of clients suffer from a plethora of performance problems.
The sheer scale of such networks, the abundance of performance metrics, and the
absence of effective tools can quickly overwhelm a network operators' ability to
diagnose these problems. As a solution, we present SCUBA, an interactive focus
and context visualization framework for metro-mesh health diagnosis. SCUBA
places performance metrics into multiple tiers or contexts, and displays only the
topmost context by default to reduce screen clutter and to provide a broad con-
textual overview of network performance. A network operator can interactively
focus on problem regions and zoom to progressively reveal more detailed con-
texts only in the focal region. We describe SCUBA's contexts and its planar and
hyperbolic views of a nearly 500 node mesh to demonstrate how it eases and ex-
pedites health diagnosis. Further, we implement SCUBA on a 15-node testbed,
demonstrate its ability to diagnose a problem within a sample scenario, and dis-
cuss its deployment challenges in a larger mesh. Our work leads to several future


Source: Almeroth, Kevin C. - Department of Computer Science, University of California at Santa Barbara


Collections: Computer Technologies and Information Sciences