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Vaccination allocation in large dynamic networks

Network infections that are already in progress cause challenges to those officers trying to preserve those nodes not yet infected. Static solutions can take advantage of global knowledge of the network to produce quick and approximate answers for those members who should be vaccinated. In dynamic s...

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Published in:Journal of big data 2017-01, Vol.4 (1), p.1-17, Article 2
Main Authors: Zhan, Justin, Rafalski, Timothy, Stashkevich, Gennady, Verenich, Edward
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Language:English
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description Network infections that are already in progress cause challenges to those officers trying to preserve those nodes not yet infected. Static solutions can take advantage of global knowledge of the network to produce quick and approximate answers for those members who should be vaccinated. In dynamic situations however, small changes can severely alter those static solutions making them irrelevant. Yet in dynamic situations it can not be known with certainty which small changes will affect the solution and those that will not. Computational resources are wasted recalculating a global solution for the entire network, when a local recalculation may be enough. This paper presents a dynamic node vaccination solution that seeks to take advantage of these local recalculations.
doi_str_mv 10.1186/s40537-016-0061-4
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subjects Big Data
Communications Engineering
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Database Management
Immunization
Information Storage and Retrieval
Knowledge management
Mathematical Applications in Computer Science
Networks
title Vaccination allocation in large dynamic networks
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