The effect of data exchange policy on traffic flow between interconnected networks

被引:1
|
作者
Lazfi, S. [1 ]
Ben Haddou, N. [1 ]
Rachadi, A. [1 ]
Ez-Zahraouy, H. [1 ]
机构
[1] Univ Mohammed 5, Fac Sci, Lab Matiere & Condencee & Sci Interdisciplinaire, Rabat, Morocco
来源
关键词
Scale free; minimal traffic model; congestion; forwarding strategy; subnet; interconnection; SMALL-WORLD; DYNAMICS;
D O I
10.1142/S0129183120500357
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In order to understand and achieve an optimal functioning in real traffic systems, the problem of congestion in complex networks takes an important place in many recent researches. In this paper, we study the effect of different types of interconnections between two scale free networks on the traffic flow. Two interconnection strategies are used: in the first, we create links between nodes chosen at random from the two subnets G(1) and G(2) and, while in the second one, we link nodes selected among the hubs of the subnets. The resulting network G is under a new routing strategy inspired from the minimal traffic model introduced in [D. De Martino, Phys. Rev. E 79, 015101 (2009); S. Lamzabi, S. Lazfi, H. Ez-Zahraouy, A. Benyoussef, A. Rachadi and S. Ziti, Int. J. Mod. Phys. C 25, 1450019 (2014)]. We find that in case of this routing method, the interconnection pattern has no effect on the results. Further, to control the exchange of packets between the subnets, we propose two adjusting parameters alpha(1) and alpha(2). The study of the variation of these parameters shows that the optimal network capacity is obtained when the two subnets are allowed to exchange data more openly.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] CONGESTION CONTROL PROTOCOLS FOR INTERCONNECTED LANS SUPPORTING VOICE AND DATA TRAFFIC
    ROUSSOS, JK
    ECONOMOU, EG
    PHILOKYPROU, G
    COMPUTER COMMUNICATIONS, 1994, 17 (01) : 25 - 34
  • [42] The research of data mining in traffic flow data
    20154801606348
    Luhang, Xu (xijiesd@126.com), 2015, Science and Engineering Research Support Society (08):
  • [43] Robust Policy Iteration of Uncertain Interconnected Systems With Imperfect Data
    Qasem, Omar
    Gao, Weinan
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 21 (02) : 1214 - 1222
  • [44] EXPERIMENTAL COMPARISON OF TRAFFIC FLOW MODELS ON TRAFFIC DATA
    Hornak, Ivan
    Prikryl, Jan
    Programs and Algorithms of Numerical Mathematics 17, 2015, : 86 - 91
  • [45] Traffic data and their implications for consistent traffic flow modeling
    Helbing, D
    TRANSPORTATION SYSTEMS 1997, VOLS 1-3, 1997, : 781 - 786
  • [46] A control policy for scheduled traffic flow system
    Han Yun-xiang
    Huang Xiao-qiong
    Tang Xin-min
    Han Song-chen
    COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 112 : 238 - 245
  • [47] Traffic flow on realistic road networks with adaptive traffic lights
    de Gier, Jan
    Garoni, Timothy M.
    Rojas, Omar
    JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2011,
  • [48] Peak Traffic Flow Predictions: Exploiting Toll Data from Large Expressway Networks
    Shen, Ling
    Lu, Jian
    Geng, Dongdong
    Deng, Ling
    SUSTAINABILITY, 2021, 13 (01) : 1 - 18
  • [49] Improved Deep Hybrid Networks for Urban Traffic Flow Prediction Using Trajectory Data
    Duan, Zongtao
    Yang, Yun
    Zhang, Kai
    Ni, Yuanyuan
    Bajgain, Saurab
    IEEE ACCESS, 2018, 6 : 31820 - 31827
  • [50] Dynamic graph convolutional networks based on spatiotemporal data embedding for traffic flow forecasting
    Zhang, Wenyu
    Zhu, Kun
    Zhang, Shuai
    Chen, Qian
    Xu, Jiyuan
    Knowledge-Based Systems, 2022, 250