Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure

It is shown that community structure has a great impact on traffic transportation and epidemic spreading. The density of infected nodes and the epidemic threshold have been proven to have significant relationship with the node betweenness in traffic driven epidemic spreading method. In this paper, c...

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Main Authors: Fei Shao, Guo-Ping Jiang
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/204093
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spelling doaj-0c816b0f7b5a422fa5cd7c35faeb68832020-11-24T21:35:59ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/204093204093Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community StructureFei Shao0Guo-Ping Jiang1Jiangsu Information Analysis Engineering Laboratory, Jinling Institute of Technology, Nanjing, Jiangsu 211169, ChinaCenter for Control and Intelligence Technology, Nanjing University of Posts & Telecommunications, Nanjing, Jiangsu 211169, ChinaIt is shown that community structure has a great impact on traffic transportation and epidemic spreading. The density of infected nodes and the epidemic threshold have been proven to have significant relationship with the node betweenness in traffic driven epidemic spreading method. In this paper, considering the impact of community structure on traffic driven epidemic spreading, an effective and novel strategy to control epidemic spreading in scale-free networks is proposed. Theoretical analysis shows that the new control strategy will obviously increase the ratio between the first and the second moments of the node betweenness distribution in scale-free networks. It is also found that the more accurate the community is identified, the stronger community structure the network has and the more efficient the control strategy is. Simulations on both computer-generated and real-world networks have confirmed the theoretical results.http://dx.doi.org/10.1155/2013/204093
collection DOAJ
language English
format Article
sources DOAJ
author Fei Shao
Guo-Ping Jiang
spellingShingle Fei Shao
Guo-Ping Jiang
Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
Mathematical Problems in Engineering
author_facet Fei Shao
Guo-Ping Jiang
author_sort Fei Shao
title Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
title_short Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
title_full Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
title_fullStr Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
title_full_unstemmed Optimal Control Strategy for Traffic Driven Epidemic Spreading Based on Community Structure
title_sort optimal control strategy for traffic driven epidemic spreading based on community structure
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description It is shown that community structure has a great impact on traffic transportation and epidemic spreading. The density of infected nodes and the epidemic threshold have been proven to have significant relationship with the node betweenness in traffic driven epidemic spreading method. In this paper, considering the impact of community structure on traffic driven epidemic spreading, an effective and novel strategy to control epidemic spreading in scale-free networks is proposed. Theoretical analysis shows that the new control strategy will obviously increase the ratio between the first and the second moments of the node betweenness distribution in scale-free networks. It is also found that the more accurate the community is identified, the stronger community structure the network has and the more efficient the control strategy is. Simulations on both computer-generated and real-world networks have confirmed the theoretical results.
url http://dx.doi.org/10.1155/2013/204093
work_keys_str_mv AT feishao optimalcontrolstrategyfortrafficdrivenepidemicspreadingbasedoncommunitystructure
AT guopingjiang optimalcontrolstrategyfortrafficdrivenepidemicspreadingbasedoncommunitystructure
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