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<item>
  <id>06112264</id>
  <dt>j</dt>
  <an>06112264</an>
  <augroup>
    <au>Guibas, Leonidas</au>
    <au>Milosavljevi\'c, Nikola</au>
    <au>Motskin, Arik</au>
  </augroup>
  <ti>Connected dominating sets on dynamic geometric graphs.</ti>
  <so>Comput. Geom. 46, No. 2, 160-172 (2013).</so>
  <py>2013</py>
  <pu>Elsevier Science B.V. (North-Holland), Amsterdam</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>connected dominating set</ut>
    <ut>unit-ball graph</ut>
    <ut>dynamic graph</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1016/j.comgeo.2012.01.004</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We propose algorithms for efficiently maintaining a constant-approximate minimum connected dominating set (MCDS) of a geometric graph under node insertions and deletions, and under node mobility. Assuming that two nodes are adjacent in the graph if and only if they are within a fixed geometric distance, we show that an $O(1)$-approximate MCDS of a graph in $\Bbb{R}^{d}$ with $n$ nodes can be maintained in $O(log^{2d}n)$ time per node insertion or deletion. We also show that $\Omega(n)$ time per operation is necessary to maintain exact MCDS. This lower bound holds even for $d=1$, even for randomized algorithms, and even when running time is amortized over a sequence of insertions/deletions, or over continuous motion. The crucial fact is that a single operation may affect the entire exact solution, while an approximate solution is affected only in a small neighborhood of the node that was inserted or deleted. In the approximate case, we show how to compute these local changes by a few range searching queries and a few bichromatic closest pair queries.</ab>
    <rv></rv>
  </abgroup>
</item>