Team for Research in
Ubiquitous Secure Technology

Citation
O. Patrick Kreidl, Alan S. Willsky. "Decentralized Detection in Undirected Network Topologies". IEEE 2007 Statistical ignal Processing Workshop, August, 2007.

Abstract
Consider the well-studied decentralized Bayesian detection problem with the twist of an undirected network topology, each edge representing a bidirectional (and perhaps unreliable) finite-rate communication link between two distributed sensor nodes. Every node operates in parallel, processing any particular local measurement in two (discrete) decision stages: the first selects the symbols (if any) transmitted to its immediate neighbors and the second, upon receiving the symbols (or lack thereof) from the same neighbors, decides the value of its local state. We adapt the team solution already known for directed acyclic networks and establish conditions such that the iterative numerical algorithm to collectively optimize the local decision rules admits an efficient message-passing interpretation, featuring an asynchronous distributed implementation in which total computation and communication overhead scales only linearly with the number of nodes. In sharp contrast to the directed case, this message-passing algorithm retains its global correctness and convergence guarantees without restrictions on the network topology.

Electronic downloads

• http://web.mit.edu/~opk/www/res.html

• HTML

  O. Patrick Kreidl, Alan S. Willsky. <a
  href="http://www.truststc.org/pubs/264.html"
  >Decentralized Detection in Undirected Network
  Topologies</a>, IEEE 2007 Statistical ignal Processing
  Workshop, August, 2007.

• Plain text

  O. Patrick Kreidl, Alan S. Willsky. "Decentralized
  Detection in Undirected Network Topologies". IEEE 2007
  Statistical ignal Processing Workshop, August, 2007.

• BibTeX

  @inproceedings{KreidlWillsky07_DecentralizedDetectionInUndirectedNetworkTopologies,
      author = {O. Patrick Kreidl and Alan S. Willsky},
      title = {Decentralized Detection in Undirected Network
                Topologies},
      booktitle = {IEEE 2007 Statistical ignal Processing Workshop},
      month = {August},
      year = {2007},
      abstract = {Consider the well-studied decentralized Bayesian
                detection problem with the twist of an undirected
                network topology, each edge representing a
                bidirectional (and perhaps unreliable) finite-rate
                communication link between two distributed sensor
                nodes. Every node operates in parallel, processing
                any particular local measurement in two (discrete)
                decision stages: the first selects the symbols (if
                any) transmitted to its immediate neighbors and
                the second, upon receiving the symbols (or lack
                thereof) from the same neighbors, decides the
                value of its local state. We adapt the team
                solution already known for directed acyclic
                networks and establish conditions such that the
                iterative numerical algorithm to collectively
                optimize the local decision rules admits an
                efficient message-passing interpretation,
                featuring an asynchronous distributed
                implementation in which total computation and
                communication overhead scales only linearly with
                the number of nodes. In sharp contrast to the
                directed case, this message-passing algorithm
                retains its global correctness and convergence
                guarantees without restrictions on the network
                topology.},
      URL = {http://www.truststc.org/pubs/264.html}
  }
  

Posted by O. Patrick Kreidl on 16 Jul 2007.
For additional information, see the Publications FAQ or contact webmaster at www truststc org.