Vaccination Allocation in Large Dynamic Networks

Document Type

Article

Publication Date

1-1-2017

Publication Title

Journal of Big Data

Volume

4

Issue

1

Abstract

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. © 2017, The Author(s).

Language

english

UNLV article access

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