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| Identification on Spatio-temporal Characteristics of the Traffic of Communication System Based on Coupling Bipartite Network |
| TAN Guimin1, WANG Lina1,2, ZANG Chenrui3
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1. College of Sciences, Inner Mongolia University of Technology, Hohhot 010051, China;
2. Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling, Hohhot 010051, China;
3. Inner Mongolia Branch, China Unicom, Hohhot 010050, China |
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Abstract In order to identify the spatio-temporal characteristics of the traffic of communication system, Network model and core-periphery model is used to analyze the traffic data. Considering both the temporal information and the spatial information, we construct a data-voice coupled bipartite network. The edge weight distribution of the temporal network is lognormal. The maximal connected subgraph of the spatial network is denoted as S-network and it is a small world network. The edge weight of the S-network obeys power-law distribution. The frequency of coupling events in core is higher than that in periphery. The core-periphery model can effectively identifies spatio-temporal areas where data-voice coupling events occur intensively.
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Received: 16 March 2021
Published: 23 May 2022
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