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Title: Optimal deployment of resources for maximizing impact in spreading processes

Abstract

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.

Authors:
ORCiD logo [1]; ORCiD logo [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Center for Nonlinear Studies and Theoretical Division
  2. Aston Univ., Birmingham (United Kingdom). The Nonlinearity and Complexity Research Group
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1389879
Alternate Identifier(s):
OSTI ID: 1392871
Report Number(s):
LA-UR-16-26490
Journal ID: ISSN 0027-8424
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Published Article
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Volume: 114; Journal Issue: 39; Journal ID: ISSN 0027-8424
Publisher:
National Academy of Sciences, Washington, DC (United States)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 60 APPLIED LIFE SCIENCES; Mathematics

Citation Formats

Lokhov, Andrey Y., and Saad, David. Optimal deployment of resources for maximizing impact in spreading processes. United States: N. p., 2017. Web. doi:10.1073/pnas.1614694114.
Lokhov, Andrey Y., & Saad, David. Optimal deployment of resources for maximizing impact in spreading processes. United States. doi:10.1073/pnas.1614694114.
Lokhov, Andrey Y., and Saad, David. Tue . "Optimal deployment of resources for maximizing impact in spreading processes". United States. doi:10.1073/pnas.1614694114.
@article{osti_1389879,
title = {Optimal deployment of resources for maximizing impact in spreading processes},
author = {Lokhov, Andrey Y. and Saad, David},
abstractNote = {The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.},
doi = {10.1073/pnas.1614694114},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 39,
volume = 114,
place = {United States},
year = {Tue Sep 12 00:00:00 EDT 2017},
month = {Tue Sep 12 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1073/pnas.1614694114

Citation Metrics:
Cited by: 2 works
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