BibTeX for a paper by David Kotz at Dartmouth College.
For more information about this paper, visit this web page:
https://www.cs.dartmouth.edu/~kotz/research/nanda-thesis/index.html

@PhdThesis{nanda:thesis,
  author =        {Soumendra Nanda},
  title =         {{Mesh-Mon: a Monitoring and Management System for Wireless Mesh Networks}},
  school =        {Dartmouth Computer Science},
  year =          2008,
  month =         {May},
  copyright =     {Soumendra Nanda},
  address =       {Hanover, NH},
  URL =           {https://www.cs.dartmouth.edu/~kotz/research/nanda-thesis/index.html},
  note =          {Available as Dartmouth Computer Science Technical Report TR2008-619},
  abstract =      {A mesh network is a network of wireless routers that employ multi-hop routing and can be used to provide network access for mobile clients. Mobile mesh networks can be deployed rapidly to provide an alternate communication infrastructure for emergency response operations in areas with limited or damaged infrastructure. \par  In this dissertation, we present Dart-Mesh: a Linux-based layer-3 dual-radio two-tiered mesh network that provides complete 802.11b coverage in the Sudikoff Lab for Computer Science at Dartmouth College. We faced several challenges in building, testing, monitoring and managing this network. These challenges motivated us to design and implement Mesh-Mon, a network monitoring system to aid system administrators in the management of a mobile mesh network. Mesh-Mon is a scalable, distributed and decentralized management system in which mesh nodes cooperate in a proactive manner to help detect, diagnose and resolve network problems automatically. Mesh-Mon is independent of the routing protocol used by the mesh routing layer and can function even if the routing protocol fails. We demonstrate this feature by running Mesh-Mon on two versions of Dart-Mesh, one running on AODV (a reactive mesh routing protocol) and the second running on OLSR (a proactive mesh routing protocol) in separate experiments. \par  Mobility can cause links to break, leading to disconnected partitions. We identify critical nodes in the network, whose failure may cause a partition. We introduce two new metrics based on social-network analysis: the Localized Bridging Centrality (LBC) metric and the Localized Load-aware Bridging Centrality (LLBC) metric, that can identify critical nodes efficiently and in a fully distributed manner. \par  We run a monitoring component on client nodes, called Mesh-Mon-Ami, which also assists Mesh-Mon nodes in the dissemination of management information between physically disconnected partitions, by acting as carriers for management data. \par  We conclude, from our experimental evaluation on our 16-node Dart-Mesh testbed, that our system solves several management challenges in a scalable manner, and is a useful and effective tool for monitoring and managing real-world mesh networks.},
}