Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Mitigating routing misbehavior in mobile ad hoc networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Interactive visualization of large graphs and networks
Interactive visualization of large graphs and networks
Strategies for sound internet measurement
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
A high-throughput path metric for multi-hop wireless routing
Wireless Networks - Special issue: Selected papers from ACM MobiCom 2003
Troubleshooting wireless mesh networks
ACM SIGCOMM Computer Communication Review
Understanding congestion in IEEE 802.11b wireless networks
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Experiences from the design, deployment, and usage of the UCSB MeshNet testbed
IEEE Wireless Communications
MeshMon: a multi-tiered framework for wireless mesh networkmonitoring
Proceedings of the 2009 MobiHoc S3 workshop on MobiHoc S3
Understanding and improving the diagnostic workflow of MapReduce users
CHIMIT '11 Proceedings of the 5th ACM Symposium on Computer Human Interaction for Management of Information Technology
FMN'10 Proceedings of the Third international conference on Future Multimedia Networking
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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 contextual overview of network performance. A network operator can interactively focus on problem regions and zoom to progressively reveal more detailed contexts 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 expedites health diagnosis. Further, we implement SCUBA on a 15-node testbed, demonstrate its ability to diagnose a problem within a sample scenario, and discuss its deployment challenges in a larger mesh. Our work leads to several future research directions on focus and context visualization and efficient metrics collection for fast and efficient mesh network health diagnosis.