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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 923 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 909 | - |
dc.citation.title | IEEE TRANSACTIONS ON MOBILE COMPUTING | - |
dc.citation.volume | 15 | - |
dc.contributor.author | Kim, Yoora | - |
dc.contributor.author | Lee, Kyunghan | - |
dc.contributor.author | Shroff, Ness B. | - |
dc.date.accessioned | 2023-12-22T00:06:46Z | - |
dc.date.available | 2023-12-22T00:06:46Z | - |
dc.date.created | 2015-08-07 | - |
dc.date.issued | 2016-04 | - |
dc.description.abstract | Predicting spreading patterns of information or virus has been a popular research topic for which various mathematical tools have been developed. These tools have mainly focused on estimating the average time of spread to a fraction (e.g.,α) of the agents, i.e., so-called average -completion time E(T). We claim that understanding stochastic confidence on the time T rather than only its average gives more comprehensive knowledge on the spread behavior and wider engineering choices. Obviously, the knowledge also enables us to effectively accelerate or decelerate a spread. To demonstrate the benefits of understanding the distribution of spread time, we introduce a new metric G, that denotes the time required to guarantee completion (i.e., penetration) with probability . Also, we develop a new framework characterizing G, for various spread parameters such as number of seeders, contact rates between agents, and heterogeneity in contact rates. We apply our technique to a large-scale experimental vehicular trace and show that it is possible to allocate resources for acceleration of spread in a far more elaborated way compared to conventional average-based mathematical tools. | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON MOBILE COMPUTING, v.15, no.4, pp.909 - 923 | - |
dc.identifier.doi | 10.1109/TMC.2015.2431711 | - |
dc.identifier.issn | 1536-1233 | - |
dc.identifier.scopusid | 2-s2.0-84963987427 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/17081 | - |
dc.identifier.url | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7105373 | - |
dc.identifier.wosid | 000372396800010 | - |
dc.language | 영어 | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.title | On Stochastic Confidence of Information Spread in Opportunistic Networks | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems; Telecommunications | - |
dc.relation.journalResearchArea | Computer Science; Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Information spread | - |
dc.subject.keywordAuthor | CTMC analysis | - |
dc.subject.keywordAuthor | spread time analysis | - |
dc.subject.keywordAuthor | spread time distribution | - |
dc.subject.keywordPlus | KRYLOV SUBSPACE APPROXIMATIONS | - |
dc.subject.keywordPlus | MATRIX EXPONENTIAL OPERATOR | - |
dc.subject.keywordPlus | EPIDEMIC | - |
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