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
Repository Citation
Zhan, J.,
Rafalski, T.,
Stashkevich, G.,
Verenich, E.
(2017).
Vaccination Allocation in Large Dynamic Networks.
Journal of Big Data, 4(1),
http://dx.doi.org/10.1186/s40537-016-0061-4