Clearing Contamination in Large Networks

In this work, we study the problem of clearing contamination spreading through a large network where we model the problem as a graph searching game. The problem can be summarized as constructing a search strategy that will leave the graph clear of any contamination at the end of the searching proces...

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Bibliographic Details
Main Author: Simpson, Michael
Other Authors: Thomo, Alex
Language:English
en
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/1828/5636
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spelling ndltd-uvic.ca-oai-dspace.library.uvic.ca-1828-56362015-01-29T16:52:41Z Clearing Contamination in Large Networks Simpson, Michael Thomo, Alex Srinivasan, Venkatesh Social Networks Graph Searching Approximation Algorithms In this work, we study the problem of clearing contamination spreading through a large network where we model the problem as a graph searching game. The problem can be summarized as constructing a search strategy that will leave the graph clear of any contamination at the end of the searching process in as few steps as possible. We show that this problem is NP-hard even on directed acyclic graphs and provide an efficient approximation algorithm. We experimentally observe the performance of our approximation algorithm in relation to the lower bound on several large online networks including Slashdot, Epinions and Twitter. The experiments reveal that in most cases our algorithm performs near optimally. Graduate 2014-08-29T20:10:37Z 2014-08-29T20:10:37Z 2014 2014-08-29 Thesis http://hdl.handle.net/1828/5636 English en Available to the World Wide Web http://creativecommons.org/publicdomain/zero/1.0/
collection NDLTD
language English
en
sources NDLTD
topic Social Networks
Graph Searching
Approximation Algorithms
spellingShingle Social Networks
Graph Searching
Approximation Algorithms
Simpson, Michael
Clearing Contamination in Large Networks
description In this work, we study the problem of clearing contamination spreading through a large network where we model the problem as a graph searching game. The problem can be summarized as constructing a search strategy that will leave the graph clear of any contamination at the end of the searching process in as few steps as possible. We show that this problem is NP-hard even on directed acyclic graphs and provide an efficient approximation algorithm. We experimentally observe the performance of our approximation algorithm in relation to the lower bound on several large online networks including Slashdot, Epinions and Twitter. The experiments reveal that in most cases our algorithm performs near optimally. === Graduate
author2 Thomo, Alex
author_facet Thomo, Alex
Simpson, Michael
author Simpson, Michael
author_sort Simpson, Michael
title Clearing Contamination in Large Networks
title_short Clearing Contamination in Large Networks
title_full Clearing Contamination in Large Networks
title_fullStr Clearing Contamination in Large Networks
title_full_unstemmed Clearing Contamination in Large Networks
title_sort clearing contamination in large networks
publishDate 2014
url http://hdl.handle.net/1828/5636
work_keys_str_mv AT simpsonmichael clearingcontaminationinlargenetworks
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