Clearing Contamination in Large Networks
| dc.contributor.author | Simpson, Michael | |
| dc.contributor.supervisor | Thomo, Alex | |
| dc.contributor.supervisor | Srinivasan, Venkatesh | |
| dc.date.accessioned | 2014-08-29T20:10:37Z | |
| dc.date.available | 2014-08-29T20:10:37Z | |
| dc.date.copyright | 2014 | en_US |
| dc.date.issued | 2014-08-29 | |
| dc.degree.department | Department of Computer Science | |
| dc.degree.level | Master of Science M.Sc. | en_US |
| dc.description.abstract | 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. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/5636 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights.temp | Available to the World Wide Web | en_US |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.subject | Social Networks | en_US |
| dc.subject | Graph Searching | en_US |
| dc.subject | Approximation Algorithms | en_US |
| dc.title | Clearing Contamination in Large Networks | en_US |
| dc.type | Thesis | en_US |