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添加50字节 、 2020年10月31日 (六) 18:43
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本词条由Ryan初步翻译,已由Alienxj审校。
 
本词条由Ryan初步翻译,已由Alienxj审校。
   
{{redirect|Network hub|the Ethernet technology|Ethernet hub}}
 
{{redirect|Network hub|the Ethernet technology|Ethernet hub}}
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[[File:Network representation of brain connectivity.JPG|thumb|right|
 
[[File:Network representation of brain connectivity.JPG|thumb|right|
   
图1:Network representation of brain connectivity. Hubs are highlighted  
 
图1:Network representation of brain connectivity. Hubs are highlighted  
图1:大脑连接性的网络表示,其中枢纽节点被突出显示]]
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图1:大脑连接性的网络表示,其中枢纽被突出显示]]
 
      
[[File:Internet map 4096.png|thumb|150px|right|
 
[[File:Internet map 4096.png|thumb|150px|right|
   
图2:Partial map of the Internet based on the January 15, 2005. Hubs are highlighted  
 
图2:Partial map of the Internet based on the January 15, 2005. Hubs are highlighted  
图2:2005年1月15日的因特网局部图,枢纽节点被突出显示]]
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图2:2005年1月15日的因特网局部图,其中枢纽被突出显示]]
    
A hub is a component of a network with a high-degree [[Vertex (graph theory)|node]]. Hubs have a significantly larger number of links in comparison with other nodes in the network. The number of links ([[Degree (graph theory)|degrees]]) for a hub in a scale-free network is much higher than for the biggest node in a random network, keeping the size ''N'' of the network and average degree ''<k>'' constant. The existence of hubs is the biggest difference between random networks and scale-free networks. In random networks, the degree ''k'' is comparable for every node; it is therefore not possible for hubs to emerge. In scale-free networks, a few nodes (hubs) have a high degree ''k'' while the other nodes have a small number of links.
 
A hub is a component of a network with a high-degree [[Vertex (graph theory)|node]]. Hubs have a significantly larger number of links in comparison with other nodes in the network. The number of links ([[Degree (graph theory)|degrees]]) for a hub in a scale-free network is much higher than for the biggest node in a random network, keeping the size ''N'' of the network and average degree ''<k>'' constant. The existence of hubs is the biggest difference between random networks and scale-free networks. In random networks, the degree ''k'' is comparable for every node; it is therefore not possible for hubs to emerge. In scale-free networks, a few nodes (hubs) have a high degree ''k'' while the other nodes have a small number of links.
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A hub is a component of a network with a high-degree node. Hubs have a significantly larger number of links in comparison with other nodes in the network. The number of links (degrees) for a hub in a scale-free network is much higher than for the biggest node in a random network, keeping the size N of the network and average degree <k> constant. The existence of hubs is the biggest difference between random networks and scale-free networks. In random networks, the degree k is comparable for every node; it is therefore not possible for hubs to emerge. In scale-free networks, a few nodes (hubs) have a high degree k while the other nodes have a small number of links.
 
A hub is a component of a network with a high-degree node. Hubs have a significantly larger number of links in comparison with other nodes in the network. The number of links (degrees) for a hub in a scale-free network is much higher than for the biggest node in a random network, keeping the size N of the network and average degree <k> constant. The existence of hubs is the biggest difference between random networks and scale-free networks. In random networks, the degree k is comparable for every node; it is therefore not possible for hubs to emerge. In scale-free networks, a few nodes (hubs) have a high degree k while the other nodes have a small number of links.
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枢纽是拥有大度节点网络的一个组成部分。与网络中的其他节点相比,枢纽的链接数要大得多。无标度网络中枢纽的链接数(度)远远高于随机网络中链接数最大的节点,在保持网络的大小''N''和平均度 ''<k>''不变的情况下。枢纽的存在是随机网络和无标度网络的最大区别。在随机网络中,每个节点的度''k''是可比的,因此不可能出现枢纽节点。在无标度网络中,少数节点(即枢纽节点)具有高度值 ''k'',而其他节点只有少量的链接。
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枢纽是拥有大度节点网络的重要构件。与网络中的其他节点相比,枢纽拥有的链接数量明显更多。在保持网络规模''N''和平均度 ''<k>''不变的情况下,无标度网络中枢纽拥有的链接数(度)远远高于随机网络中链接数最大的节点。枢纽的存在是随机网络和无标度网络的最大区别。在随机网络中,对于每个节点而言,度''k''是相当的,因此不可能出现枢纽节点。而在无标度网络中,少数节点(即枢纽)具有较高的度值 ''k'',而其他节点则只拥有少量的链接。
 
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== Emergence 涌现==
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== Emergence 出现==
    
[[Image:Scale-free network sample.png|thumb|Example of a random network and a scale-free network|400px|right|
 
[[Image:Scale-free network sample.png|thumb|Example of a random network and a scale-free network|400px|right|
 
图3:Random network (a) and scale-free network (b). In the scale-free network, the larger hubs are highlighted.  
 
图3:Random network (a) and scale-free network (b). In the scale-free network, the larger hubs are highlighted.  
随机网络(a)和无标度网络(b),在无标度网络中,大型枢纽被突出显示]]
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图3:随机网络(a),无标度网络(b)。在无标度网络中,大型枢纽被突出显示。]]
 
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Emergence of hubs can be explained by the difference between scale-free networks and random networks. Scale-free networks ([[Barabási–Albert model]]) are different from random networks ([[Erdős–Rényi model]]) in two aspects: (a) growth, (b) preferential attachment.<ref name=RMP>{{Cite journal
 
Emergence of hubs can be explained by the difference between scale-free networks and random networks. Scale-free networks ([[Barabási–Albert model]]) are different from random networks ([[Erdős–Rényi model]]) in two aspects: (a) growth, (b) preferential attachment.<ref name=RMP>{{Cite journal
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Emergence of hubs can be explained by the difference between scale-free networks and random networks. Scale-free networks (Barabási–Albert model) are different from random networks (Erdős–Rényi model) in two aspects: (a) growth, (b) preferential attachment.<ref name=RMP>{{Cite journal
 
Emergence of hubs can be explained by the difference between scale-free networks and random networks. Scale-free networks (Barabási–Albert model) are different from random networks (Erdős–Rényi model) in two aspects: (a) growth, (b) preferential attachment.<ref name=RMP>{{Cite journal
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枢纽节点的出现可以用无标度网络和随机网络的区别来解释。'''<font color="#ff8000">无标度网络 Scale-Free Networks Barabási-Albert model</font>''''''<font color="#ff8000">随机网络 Random Networks Erdős–Rényi model</font>'''在两个方面有所不同: (a)'''<font color="#ff8000">增长 Growth</font>''',(b)'''<font color="#ff8000">优先连接 Preferential Attachment</font>'''。{ Cite journal
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枢纽的出现可以用无标度网络和随机网络的区别来解释。'''<font color="#ff8000">无标度网络 Scale-Free Networks</font>'''(Barabási-Albert模型)与'''<font color="#ff8000">随机网络 Random Networks</font>'''(Erdős–Rényi model)的不同主要存在于如下两个方面: (a)'''<font color="#ff8000">增长 Growth</font>''',(b)'''<font color="#ff8000">优先连接 Preferential Attachment</font>'''。{ Cite journal
    
  | url = http://www.nd.edu/~networks/Publication%20Categories/03%20Journal%20Articles/Physics/StatisticalMechanics_Rev%20of%20Modern%20Physics%2074,%2047%20(2002).pdf
 
  | url = http://www.nd.edu/~networks/Publication%20Categories/03%20Journal%20Articles/Physics/StatisticalMechanics_Rev%20of%20Modern%20Physics%2074,%2047%20(2002).pdf
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