Effective traffic-flow assignment strategy on multilayer networks

被引:37
作者
Gao, Lei [1 ,4 ]
Shu, Panpan [5 ]
Tang, Ming [2 ,3 ]
Wang, Wei [6 ]
Gao, Hui [4 ]
机构
[1] Shandong Agr Univ, Coll Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China
[2] East China Normal Univ, Sch Math Sci, Shanghai Key Lab PMMP, Shanghai 200241, Peoples R China
[3] East China Normal Univ, Shanghai Key Lab Multidimens Informat Proc, Shanghai 200241, Peoples R China
[4] Univ Elect Sci & Technol China, Web Sci Ctr, Chengdu 610054, Sichuan, Peoples R China
[5] Xian Univ Technol, Sch Sci, Xian 710054, Shaanxi, Peoples R China
[6] Sichuan Univ, Cybersecur Res Inst, Chengdu 610065, Sichuan, Peoples R China
基金
上海市自然科学基金; 中国国家自然科学基金;
关键词
DYNAMICS; EVOLUTION;
D O I
10.1103/PhysRevE.100.012310
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
An efficient flow assignment strategy is of great importance to alleviate traffic congestion on multilayer networks. In this work, by considering the roles of nodes' local structures on the microlevel, and the different transporting speeds of layers in the macrolevel, an effective traffic-flow assignment strategy on multilayer networks is proposed. Both numerical and semianalytical results indicate that our proposed flow assignment strategy can reasonably redistribute the traffic flow of the low-speed layer to the high-speed layer. In particular, preferentially transporting the packets through small-degree nodes on the high-speed layer can enhance the traffic capacity of multilayer networks. We also find that the traffic capacity of multilayer networks can be improved by increasing the network size and the average degree of the high-speed layer. For a given multilayer network, there is a combination of optimal macrolevel parameter and optimal microlevel parameter with which the traffic capacity can be maximized. It is verified that real-world network topology does not invalidate the results. The semianalytical predictions agree with the numerical simulations.
引用
收藏
页数:9
相关论文
共 73 条
[51]   Traffic congestion in interconnected complex networks [J].
Tan, Fei ;
Wu, Jiajing ;
Xia, Yongxiang ;
Tse, Chi K. .
PHYSICAL REVIEW E, 2014, 89 (06)
[52]   Self-adjusting routing schemes for time-varying traffic in scale-free networks [J].
Tang, Ming ;
Liu, Zonghua ;
Liang, Xiaoming ;
Hui, P. M. .
PHYSICAL REVIEW E, 2009, 80 (02)
[53]   Asymmetrically interacting spreading dynamics on complex layered networks [J].
Wang, Wei ;
Tang, Ming ;
Yang, Hui ;
Do, Younghae ;
Lai, Ying-Cheng ;
Lee, GyuWon .
SCIENTIFIC REPORTS, 2014, 4
[54]   Abrupt transition to complete congestion on complex networks and control [J].
Wang, Wen-Xu ;
Wu, Zhi-Xi ;
Jiang, Rui ;
Chen, Guanrong ;
Lai, Ying-Cheng .
CHAOS, 2009, 19 (03)
[55]   Collective dynamics of 'small-world' networks [J].
Watts, DJ ;
Strogatz, SH .
NATURE, 1998, 393 (6684) :440-442
[56]   Bounded-rationality based day-to-day evolution model for travel behavior analysis of urban railway network [J].
Wu, Jianjun ;
Sun, Huijun ;
Wang, David Z. W. ;
Zhong, Ming ;
Han, Linghui ;
Gao, Ziyou .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2013, 31 :73-82
[57]   Transport in weighted networks: Partition into superhighways and roads [J].
Wu, ZH ;
Braunstein, LA ;
Havlin, S ;
Stanley, HE .
PHYSICAL REVIEW LETTERS, 2006, 96 (14)
[58]   Traffic dynamics in scale-free networks with limited buffers and decongestion strategy [J].
Wu, Zhi-Xi ;
Wang, Wen-Xu ;
Yeung, Kai-Hau .
NEW JOURNAL OF PHYSICS, 2008, 10
[59]   Optimal capacity distribution on complex networks [J].
Xia, Yongxiang ;
Hill, David .
EPL, 2010, 89 (05)
[60]  
Xiang L., 2013, CHINESE PHYS B, V22