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    <title>EFFICIENT ALGORITHMS FOR POWER ASSIGNMENT PROBLEMS</title>
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    <namePart>Qiao, Kan</namePart>
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    <namePart>Calinescu, Gruia</namePart>
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  <abstract>Power assignment problems take as input a directed simple graph G = (V;E) and a cost function c : E ! R+. A solution to this problem assigns every vertex a nonnegative power, p(v). We use H = (V;B(p)) to denote the spanning subgraph of G created by this power assignment. Let B(p) denote the set of all the links established between pairs of nodes in V under the power assignment p. The minimization problem then is to find the minimum power assignment, Pp(v), subject to H satisfying a specific property. 4 variants of this problem are discussed in this paper (a) Min-Power Strong Connectivity: H = (V;B(p)) is strongly connected. (b) Min-Power Broadcast: H = (V;B(p)) has a path from the fixed source z to every other vertex. (c) Min-Power Connectivity with 2-level power (Symmetric): c : E ! f0; 1g and H = (V;B(p)) is connected. (d) Min- Power Strong Connectivity with 2-level power (Asymmetric): c : E ! f0; 1g and H = (V;B(p)) is strongly connected. We give the exact solution using an improved integer linear program for problem (a) and (b) (We do not have a section for the integer linear program of Min-Power Broadcast problem since it is very similar to Min-Power Strong connectivity). Then we try to speedup current best approximation algorithms while preserving their approximation ratio. For problem (a), we give a fast variant of 1:85-approximation algorithm with running time O(n2 log2 n). For problem (b), we give a fast variant of 2(1 + ln n)-approximation algorithm for the most general cost model with running time O(n3) and a fast variant of 4:2- approximation algorithm for 2-dimensional cost model with running time O(nm), where n = jV j and m = jEj. For both problem (c) and (d), We give 5 3-approximation algorithms that run in O(m (n)), where (n) is the inverse Ackermann function.</abstract>
  <note type="provenance">Submitted by Erma Thomas (thomase@iit.edu) on 2015-09-18T18:46:51Z No. of bitstreams: 1 Kan Qiao-Thesis.pdf: 8781769 bytes, checksum: 0f2a6f0c68ddc533899c097a53fb49cb (MD5)</note>
  <note type="provenance">Made available in DSpace on 2015-09-18T18:46:51Z (GMT). No. of bitstreams: 1 Kan Qiao-Thesis.pdf: 8781769 bytes, checksum: 0f2a6f0c68ddc533899c097a53fb49cb (MD5) Previous issue date: 2015-05</note>
  <note type="thesis">Ph.D. in Computer Science, May 2015</note>
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    <dateCaptured>2015</dateCaptured>
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    <dateCreated keyDate="yes">2015-05</dateCreated>
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  <identifier type="hdl">http://hdl.handle.net/10560/3565</identifier>
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    <namePart>CS / Computer Science</namePart>
    <affiliation>Illinois Institute of Technology</affiliation>
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