Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges

doi:10.21629/JSEE.2018.03.12

Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (3): 549-559.doi: 10.21629/JSEE.2018.03.12

• Systems Engineering • Previous Articles Next Articles

Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges

Yinghui YANG^1,^2,*(), Jianhua LI¹(), Di SHEN¹(), Mingli NAN^1,³(), Qiong CUI¹()

¹ Information and Navigation College, Air Force Engineering University, Xi’an 710077, China
² Unit 95899 of the PLA, Beijing 100076, China
³ Unit 95881 of the PLA, Beijing 100095, China

Received:2016-07-29 Online:2018-06-28 Published:2018-07-02
Contact: Yinghui YANG E-mail:yangyinghui.good@163.com;KGDLJH@163.com;hanshanyueyin@126.com;good@163.com;flying1990@163.com
About author:YANG Yinghui was born in 1988. He received his M.S. degree in military command from Air Force Engineering University in 2012 and Ph.D. degree in 2016 in the same university and profession. He is currently working at a military research institution and his research interests are information flowing and operations modeling. E-mail: yangyinghui.good@163.com|LI Jianhua was born in 1965. He received his M.S. degree in tactical communication from Communication Command Academy in 1994. He received his B.S. degree in military communication from Air Force Engineering University in 2005. Since 1991, he joined Air Force Early Warning Academy, where he is currently a professor and doctor postgraduate tutor. He has taken charge of over ten research subjects and has won eight prizes of army science and technology progress. He has published seven textbooks, and more than 90 papers on international and domestic academic journals. His current research interests are military information system design and construction. E-mail: KGDLJH@163.com|SHEN Di was born in 1986. He received his B.E., M.E. and Ph.D. degrees from Air Force Engineering University in 2008, 2010, 2014 respectively. His research interests include complex network modeling and simulation. E-mail: hanshanyueyin@126.com|NAN Mingli was born in 1987. She is an M.E. candidate in Air Force Engineering University and received her B.E. degree in 2012. Her research interests include network optimization and simulation. E-mail: nanmingli good@163.com|CUI Qiong was born in 1990. She is a Ph.D. candidate in Air Force Engineering University (AFEU) and received her B.E. and M.E. degrees from AFEU in 2011 and 2013 respectively. Her research interests include complex adaptive modeling. E-mail: flying1990@163.com
Supported by:
the National Natural Science Foundation of China(61573017);the National Natural Science Foundation of China(61401499);the National Natural Science Foundation of China(61174162);This work was supported by the National Natural Science Foundation of China (61573017; 61401499; 61174162)

Abstract

Abstract:

Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges (CNFNOEs) is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks (ILCN). Secondly, the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method. Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE’s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network, etc.

Key words: complex network with fusion nodes and overlap edges (CNFNOEs), interlacing layered complex networks (ILCN), local world, dynamic evolvement, split, saturation, attraction factor

Yinghui YANG, Jianhua LI, Di SHEN, Mingli NAN, Qiong CUI. Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges[J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 549-559.

Figures/Tables 7

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References 32

1	CASTET J F, SALEH J H. Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks. PLoS One, 2013, 8 (4): e60402. doi: 10.1371/journal.pone.0060402
2	WANG Z, SZOLNOKI A, PERC M. Self-organization towards optimally interdependent networks by means of coevolution. New Journal of Physics, 2014, 16 (3): 033041. doi: 10.1088/1367-2630/16/3/033041
3	BARABASI A L, ALBERT R. Emergence of scaling in random networks. Science, 1999, 286 (5439): 509- 512. doi: 10.1126/science.286.5439.509
4	WATTS D J, STROGATZ S H. Collective dynamics of smallworld networks. Nature, 1998, 393 (6684): 440- 442. doi: 10.1038/30918
5	AXELROD R, HAMILTON W D. The evolution of cooperation. Science, 1981, 211 (4489): 1390- 1396. doi: 10.1126/science.7466396
6	OHTSUKI H, HAUERT C, LIEBERMAN E, et al. A simple rule for the evolution of cooperation on graphs and social networks. Nature, 2006, (441): 502- 505.
7	KURANT M, THIRAN P. Layered complex networks. Physical Review Letters, 2006, 96 (13): 138701. doi: 10.1103/PhysRevLett.96.138701
8	AOKI T, YAWATA K, AOYAGI T. Self-organization of complex networks as a dynamical system. Physical Review E, 2015, 91 (1): 012908.
9	GOMEZ-GARDENES J, GRACIA-LAZARO C, FLORA L M, et al. Evolutionary dynamics on interdependent populations. Physical Review E, 2012, 86 (2): 056113.
10	NICOSIA V, BIANCONI G, LATORA V, et al. Growing multiplex networks. Physical Review Letters, 2013, 111 (5): 058701. doi: 10.1103/PhysRevLett.111.058701
11	GAO J, BULDYREV S V, STANLEY H E, et al. Networks formed from interdependent networks. Nature Physics, 2012, 8 (1): 40- 48. doi: 10.1038/nphys2180
12	BULDYREV S V, SHERE N W, CWILICH G A. Interdependent networks with identical degrees of mutually dependent nodes. Physical Review E, 2011, 83 (1): 016112.
13	GOMEZ-GARDENES J, REINARES I, ARENAS A, et al. Evolution of cooperation in multiplex networks. Scientific Reports, 2012, (2): 620.
14	ZOU S R, ZHOU T, LIU A F. Topological relation of layered complex network. Physics Letters A, 2010, 374 (43): 4406- 4410. doi: 10.1016/j.physleta.2010.08.073
15	ROCA C P, CUESTA J A, SANCHEZ A. Effect of spatial structure on the evolution of cooperation. Physical Review E, 2009, 80 (4): 046106. doi: 10.1103/PhysRevE.80.046106
16	OHTSUKI H, NOWAK M A, PACHECO J M. Breaking the symmetry between interaction and replacement in evolutionary dynamics on graphs. Physical Review Letters, 2007, 98 (10): 108106. doi: 10.1103/PhysRevLett.98.108106
17	NOWAK M A. Five rules for the evolution of cooperation. Science, 2006, 314 (5805): 1560- 1563. doi: 10.1126/science.1133755
18	JIANG J, LI W, CAI X. The effect of interdependence on the percolation of interdependent networks. Physica A, 2014, 410 (12): 573- 581.
19	TIAN L X, HE Y H, HUANG Y. A novel local-world-like evolving bipartite network model. Acta Physica Sinica, 2012, 61 (22): 228903.
20	VALDEZ L D, MACRI P A, STANLEY H E, et al. Triple point in correlated interdependent networks. Physical Review E, 2013, 88 (5): 050803. doi: 10.1103/PhysRevE.88.050803
21	WANG J W, JIANG C, QIAN J F. Robustness of interdependent networks with different link patterns against cascading failures. Physica A, 2014, 393 (1): 535- 541.
22	SANTOS M D, DOROGOVTSEV S N, MENDES J F F. Biased imitation in coupled evolutionary games in interdependent networks. Scientific Reports, 2014, 4 (4): 4436.
23	PARSHANI R, ROZENBLAT C, IETRI D, et al. Intersimilarity between coupled networks. Europhysics Letters, 2010, 92 (6): 68002. doi: 10.1209/0295-5075/92/68002
24	SHEN D, LI J H, ZHANG Q, et al. Interlacing layered complex networks. Acta Physica Sinica, 2014, 63 (19): 190201.
25	GU C G, ZOU S R, XU L. Onset of cooperation between layered networks. Physical Review E, 2011, 84 (2): 026101.
26	DOROGOVTSEV S N, MENDES J F. Evolution of networks. Advances in Physics, 2003, 51 (4): 1079- 1187.
27	SHAO S, HUANG X Q, STANLEY H E, et al. Robustness of a partially interdependent network formed of clustered networks. Physical Review E, 2014, 89 (3): 032812. doi: 10.1103/PhysRevE.89.032812
28	ESQUIVEL-GO’MEZ J, STEVENS-NAVARRO E, PINEDARICO U, et al. A growth model for directed complex networks with power-law shape in the out-degree distribution. Scientific Reports, 2015, (5): 7670.
29	TAO S H, ZHAO H Y, PING Y, et al. Attractive factors based scale-free networks evolving model. Complex Systems and Complexity Science, 2008, 5 (2): 88- 92.
30	WANG B K, PEI Z H, WANG L. Evolutionary dynamics of cooperation on interdependent networks with the prisoner’s dilemma and snowdrift game. Europhysics Letters, 2014, (107): 58006.
31	JALILI M, SICHANI O A, YU X H. Optimal pinning controllability of complex networks: dependence on network structure. Physical Review E, 2015, 91 (1): 012803.
32	WANG Z, SZOLNOKI A, PERC M. Evolution of public cooperation on interdependent networks: the impact of biased utility functions. Europhysics Letters, 2012, (97): 48001.

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Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges

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