Data-driven resource allocation for controlling spreading processes
Cameron Nowzari, George Pappas, Shuo Han

Citation
Cameron Nowzari, George Pappas, Shuo Han. "Data-driven resource allocation for controlling spreading processes". Talk or presentation, 29, October, 2014; Poster presented at the 2014 TerraSwarm Annual Meeting.

Abstract
We propose a novel mathematical framework, based on conic geometric programming, to control viral spreading processes in an unknown contact network. We assume that the spreading process takes place in an unknown weighted, directed network and that we only have access to empirical measurements of the temporal behavior of the spreading process over a finite time interval. In most practical cases, identifying the network structure from dynamic observations is an ill-posed problem, in the sense that there are generally many networks that are consistent with the observed dynamics. In this work we take an approach in line with behavioral systems theory and propose a novel optimization framework in which we exactly characterize the set of all networks that are consistent with the empirical measurements as a cone of feasible networks and solve a conic geometric program to design robust controllers able to contain the spreading process for all networks in the cone.

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Citation formats  
  • HTML
    Cameron Nowzari, George Pappas, Shuo Han. <a
    href="http://www.terraswarm.org/pubs/392.html"><i>Data-driven
    resource allocation for controlling spreading
    processes</i></a>, Talk or presentation,  29,
    October, 2014;  Poster presented at the <a
    href="http://www.terraswarm.org/conferences/14/annual"
    >2014 TerraSwarm Annual Meeting</a>.
  • Plain text
    Cameron Nowzari, George Pappas, Shuo Han. "Data-driven
    resource allocation for controlling spreading
    processes". Talk or presentation,  29, October, 2014; 
    Poster presented at the <a
    href="http://www.terraswarm.org/conferences/14/annual"
    >2014 TerraSwarm Annual Meeting</a>.
  • BibTeX
    @presentation{NowzariPappasHan14_DatadrivenResourceAllocationForControllingSpreading,
        author = {Cameron Nowzari and George Pappas and Shuo Han},
        title = {Data-driven resource allocation for controlling
                  spreading processes},
        day = {29},
        month = {October},
        year = {2014},
        note = { Poster presented at the <a
                  href="http://www.terraswarm.org/conferences/14/annual"
                  >2014 TerraSwarm Annual Meeting</a>.},
        abstract = {We propose a novel mathematical framework, based
                  on conic geometric programming, to control viral
                  spreading processes in an unknown contact network.
                  We assume that the spreading process takes place
                  in an unknown weighted, directed network and that
                  we only have access to empirical measurements of
                  the temporal behavior of the spreading process
                  over a finite time interval. In most practical
                  cases, identifying the network structure from
                  dynamic observations is an ill-posed problem, in
                  the sense that there are generally many networks
                  that are consistent with the observed dynamics. In
                  this work we take an approach in line with
                  behavioral systems theory and propose a novel
                  optimization framework in which we exactly
                  characterize the set of all networks that are
                  consistent with the empirical measurements as a
                  cone of feasible networks and solve a conic
                  geometric program to design robust controllers
                  able to contain the spreading process for all
                  networks in the cone.},
        URL = {http://terraswarm.org/pubs/392.html}
    }
    

Posted by Cameron Nowzari on 20 Oct 2014.
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