Time-varying networks based on activation and deactivation mechanisms

doi:10.1088/1674-1056/26/10/108902

中国物理B ›› 2017, Vol. 26 ›› Issue (10): 108902-108902.doi: 10.1088/1674-1056/26/10/108902

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Time-varying networks based on activation and deactivation mechanisms

Xue-Wen Wang(王学文), Yue-E Luo(罗月娥), Li-Jie Zhang(张丽杰), Xin-Jian Xu(许新建)

1. School of Physics and Electronic Sciences, Guizhou Education University, Guiyang 550018, China;
2. College of Sciences, Shanghai University, Shanghai 200444, China;
3. Key Laboratory of Embedded System and Service Computing(Tongji University), Ministry of Education, Shanghai 201804, China

收稿日期:2017-05-02 修回日期:2017-06-25 出版日期:2017-10-05 发布日期:2017-10-05
通讯作者: Xin-Jian Xu E-mail:xinjxu@shu.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 11665009) and the Natural Science Research Project of Guizhou Provincial Education Bureau (Grant No. KY[2015]355).

Time-varying networks based on activation and deactivation mechanisms

Xue-Wen Wang(王学文)^1,2, Yue-E Luo(罗月娥)¹, Li-Jie Zhang(张丽杰)², Xin-Jian Xu(许新建)^2,3

1. School of Physics and Electronic Sciences, Guizhou Education University, Guiyang 550018, China;
2. College of Sciences, Shanghai University, Shanghai 200444, China;
3. Key Laboratory of Embedded System and Service Computing(Tongji University), Ministry of Education, Shanghai 201804, China

Received:2017-05-02 Revised:2017-06-25 Online:2017-10-05 Published:2017-10-05
Contact: Xin-Jian Xu E-mail:xinjxu@shu.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 11665009) and the Natural Science Research Project of Guizhou Provincial Education Bureau (Grant No. KY[2015]355).

摘要/Abstract

摘要：

A class of models for activity-driven networks is proposed in which nodes vary in two states:active and inactive. Only active nodes can receive links from others which represent instantaneous dynamical interactions. The evolution of the network couples the addition of new nodes and state transitions of old ones. The active group changes with activated nodes entering and deactivated ones leaving. A general differential equation framework is developed to study the degree distribution of nodes of integrated networks where four different schemes are formulated.

关键词: time-varying networks, activity-driven, degree distribution

Abstract:

Key words: time-varying networks, activity-driven, degree distribution

中图分类号: (Networks and genealogical trees)

89.75.Hc

89.75.Fb (Structures and organization in complex systems) 89.75.-k (Complex systems)

王学文, 罗月娥, 张丽杰, 许新建. Time-varying networks based on activation and deactivation mechanisms[J]. 中国物理B, 2017, 26(10): 108902-108902.

Xue-Wen Wang(王学文), Yue-E Luo(罗月娥), Li-Jie Zhang(张丽杰), Xin-Jian Xu(许新建). Time-varying networks based on activation and deactivation mechanisms[J]. Chin. Phys. B, 2017, 26(10): 108902-108902.

参考文献 40

[1]	Albert R and Barabási A L 2002 Rev. Mod. Phys. 74 47
[2]	Pastor-Satorras R and Vespignani A 2004 Evolution and Structure of the Internet (New York:Cambridge University Press)
[3]	Keeling M J and Rohani P 2007 Modeling infectious diseases in humans and animals (New Jersey:Princeton University Press)
[4]	Boccaletti S, Latora V, Moreno Y, Chavez M and Hwang D U 2006 Phys. Rep. 424 175
[5]	Holme P and Saramäki J 2012 Phys. Rep. 519 97
[6]	Holme P 2015 Eur. Phys. J. B 88 234
[7]	Zhao K, Stehlé J, Bianconi G and Barrat A 2011 Phys. Rev. E 83 056109
[8]	Jo H H, Pan R K and Kaski K 2011 PLoS ONE 6 e22687
[9]	Nicosia V, Tang J, Musolesi M, Russo G, Mascolo C and Latora V 2012 Chaos 22 023101
[10]	Jiang Z Q, Xie W J, Li M X, Podobnik B, Zhou W X and Stanley H E 2013 Proc. Natl. Acad. Sci. USA 110 1600
[11]	Kovanen L, Kertész J and Saramäki J 2013 Proc. Natl. Acad. Sci. USA 110 18070
[12]	Cardillo A, Petri G, Nicosia V, Sinatra R, Gómez-Gardeñes J and Latora V 2014 Phys. Rev. E 90 052825
[13]	Zhang Y Q, Li X, Xu J and Vasilakos A V 2015 IEEE Trans. Syst. Man Cybernet.:Syst. 45 214
[14]	Kivelä M, Pan R K, Kaski K, Kertész J, Saramäki J and Karsai M 2012 J. Stat. Mech. 2012 P03005
[15]	Rocha L E C and Blondel V D 2013 PLoS Comput. Biol. 9 e1002974
[16]	Masuda N, Klemm K and Eguíluz V M 2013 Phys. Rev. Lett. 111 188701
[17]	Holme P and Liljeros F 2014 Sci. Rep. 4 4999
[18]	Jo H H, Perotti J I, Kaski K and Kertész J 2014 Phys. Rev. X 4 011041
[19]	Scholtes I, Wider N, Pfitzner R, Garas A, Tessone C J and Schweitzer F 2014 Nat. Commun. 5 5024
[20]	Ren G and Wang X 2014 Chaos 24 023116
[21]	Han D, Sun M and Li D 2015 Physica A 432 354
[22]	Perra N, Gonçalves B, Pastor-Satorras R and Vespignani A 2012 Sci. Rep. 2 469
[23]	Starnini M and Pastor-Satorras R 2013 Phys. Rev. E 87 062807
[24]	Hoppe K and Rodgers G J 2013 Phys. Rev. E 88 042804
[25]	Medus A D and Dorso C O 2014 J. Stat. Mech. 2014 P09009
[26]	Karsai M, Perra N and Vespignani A 2014 Sci. Rep. 4 4001
[27]	Perra N, Baronchelli A, Mocanu D, Gonçalves B, Pastor-Satorras R and Vespignani A 2012 Phys. Rev. Lett. 109 238701
[28]	Liu S Y, Baronchelli A and Perra N 2013 Phys. Rev. E 87 032805
[29]	Kotnis B and Kuri J 2013 Phys. Rev. E 87 062810
[30]	Starnini M and Pastor-Satorras R 2014 Phys. Rev. E 89 032807
[31]	Liu S, Perra N, Karsai M and Vespignani A 2014 Phys. Rev. Lett. 112 118702
[32]	Zhang Y Q and Li X 2014 Europhys. Lett. 108 28006
[33]	Barabási A L and Albert R 1999 Science 286 509
[34]	Klemm K and Eguíluz V M 2002 Phys. Rev. E 65 036123
[35]	Zhang X J and Yang H L 2016 Chin. Phys. B 25 060202
[36]	Burton R E and Kebler R W 1960 American Documentation 11 18
[37]	Van Raan A F J 2004 Scientometrics 59 467
[38]	Dorogovtsev S N, Mendes J F F and Samukhin A N 2000 Phys. Rev. Lett. 85 4633
[39]	Wang X W, Yang G H, Li X L and Xu X J 2013 Chin. Phys. B 22 018903
[40]	Backlund V P, Saramäki J and Pan R K 2014 Phys. Rev. E 89 062815

Time-varying networks based on activation and deactivation mechanisms

Time-varying networks based on activation and deactivation mechanisms

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