Article(id=1242132420280001390, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242132405067264043, articleNumber=null, orderNo=10, doi=10.3981/j.issn.1000-7857.2014.24.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1400774400000, receivedDateStr=2014-05-23, revisedDate=1404230400000, revisedDateStr=2014-07-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1409128492610, onlineDateStr=2014-08-27, pubDate=1409155200000, pubDateStr=2014-08-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1409128492610, onlineIssueDateStr=2014-08-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774077046696, creator=sys-migrate, updateTime=1774077046696, updator=sys-migrate, issue=Issue{id=1242132405067264043, tenantId=1146029695717560320, journalId=1146031591421210625, year='2014', volume='32', issue='24', pageStart='1', pageEnd='95', issueExtLink='null', onlineDate='null', pubDate='1409155200000', pubDateStr='2014-08-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774077043069, creator='sys-migrate', updateTime=1774077043069, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=56, endPage=59, ext={EN=ArticleExt(id=1242132422964359279, articleId=1242132420280001390, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Phase Transition of Network Based on Traffic Routing Model, columnId=1242116080374710456, journalTitle=Science & Technology Review, columnName=Articles, runingTitle=null, highlight=null, articleAbstract=With the development of complex networks, more and more attentions are paid to the phase transition. The phase transition is a process of transition from a stable state to a congested state. In this process, three kinds of variations of loads on the network are involved, which are the total loads on the network, the loads removed from the network and the loads waiting for passing through some node. Firstly, based on the traffic routing model, an order parameter is introduced to characterize the phase transition. With the increase of R (the number of loads which enter into the network per unit time), this parameter experiences a transition from zero to non-zero. That is to say, there will be a critical value of R c that characterizes the traffic phase transition from a stable state to a congested state. Secondly through the simulation, the variations of different kinds of loads on a scale-free network are identified. The node with the maximum betweenness is easily to be congested, which results in an unbalance between the loads that enter into the network and the loads that are removed from the network, and eventually results in the network congestion; When R <R c , the number of loads that are removed from the network increases synchronously with R . When R >R c , the ratio of the number of the loads removed from the network and R decreases gradually, which means that it is more and more difficult for the loads to reach their destination. Understanding the variations of the key indicators in the phase-transition process is beneficial for the effective prevention and intervention against the network., authors=SUN Lei1 , LI Rong2 , CHEN Xiaoguo3 , authorsList=SUN Lei, LI Rong, CHEN Xiaoguo, authorCompany=1. School of Mechanics and Civil Engineering, China University of Mining & Technology(Beijing), Beijing 100083, China;R 的变化规律。为此建立了无标度网络上的输运模型，用于定量计算这3 种负荷数的变化规律。仿真结果表明：最大介数节点最先产生拥堵，导致网络的进入和消失负荷数出现不平衡，进而导致网络进入拥堵状态；当R 小于临界值R c 时，网络上的消失负荷数随R同步增长。当R超过临界值R c 时，消失负荷数与R的比值持续下降，表明随着R 的增加，负荷到达目的地越来越困难。, authors=孙磊1 , 李荣2 , 陈孝国3 , authorsList=孙磊, 李荣, 陈孝国, authorCompany=1. 中国矿业大学(北京)力学与建筑工程学院, 北京 100083;
科技导报
|研究论文
2014
, 32
(24) :
56
-59
基于输运模型的网络相变过程
全屏
孙磊1 , 李荣2 , 陈孝国3
作者信息
1. 中国矿业大学(北京)力学与建筑工程学院, 北京 100083;
通讯作者:
李荣，讲师，研究方向为复杂网络上的动力学，电子信箱：lrlr1212@sina.com
作者简介:
孙磊，博士研究生，研究方向为工程管理，电子信箱：cumtb_sunlei@163.com
Phase Transition of Network Based on Traffic Routing Model
SUN Lei1 , LI Rong2 , CHEN Xiaoguo3
Affiliations
1. School of Mechanics and Civil Engineering, China University of Mining & Technology(Beijing), Beijing 100083, China;
出版时间: 2014-08-28
doi: 10.3981/j.issn.1000-7857.2014.24.008
文章导航
网络相变过程需重点关注网络上的总负荷数、网络上的消失负荷数、节点的排队负荷数等指标随单位时间进入网络的负荷数R 的变化规律。为此建立了无标度网络上的输运模型，用于定量计算这3 种负荷数的变化规律。仿真结果表明：最大介数节点最先产生拥堵，导致网络的进入和消失负荷数出现不平衡，进而导致网络进入拥堵状态；当R 小于临界值R c 时，网络上的消失负荷数随R同步增长。当R超过临界值R c 时，消失负荷数与R的比值持续下降，表明随着R 的增加，负荷到达目的地越来越困难。
With the development of complex networks, more and more attentions are paid to the phase transition. The phase transition is a process of transition from a stable state to a congested state. In this process, three kinds of variations of loads on the network are involved, which are the total loads on the network, the loads removed from the network and the loads waiting for passing through some node. Firstly, based on the traffic routing model, an order parameter is introduced to characterize the phase transition. With the increase of R (the number of loads which enter into the network per unit time), this parameter experiences a transition from zero to non-zero. That is to say, there will be a critical value of R c that characterizes the traffic phase transition from a stable state to a congested state. Secondly through the simulation, the variations of different kinds of loads on a scale-free network are identified. The node with the maximum betweenness is easily to be congested, which results in an unbalance between the loads that enter into the network and the loads that are removed from the network, and eventually results in the network congestion; When R <R c , the number of loads that are removed from the network increases synchronously with R . When R >R c , the ratio of the number of the loads removed from the network and R decreases gradually, which means that it is more and more difficult for the loads to reach their destination. Understanding the variations of the key indicators in the phase-transition process is beneficial for the effective prevention and intervention against the network.
complex network
/
traffic routing model
/
phase transition
/
simulation
孙磊, 李荣, 陈孝国.
基于输运模型的网络相变过程.
科技导报,
2014
, 32
(24)
: 56
-59
.
DOI: 10.3981/j.issn.1000-7857.2014.24.008
SUN Lei, LI Rong, CHEN Xiaoguo.
Phase Transition of Network Based on Traffic Routing Model[J].
Science & Technology Review ,
2014
, 32
(24)
: 56
-59
.
DOI: 10.3981/j.issn.1000-7857.2014.24.008
2014年第32卷第24期
PDF下载
585
139
引用本文
BibTeX
文章信息
doi: 10.3981/j.issn.1000-7857.2014.24.008
接收时间：2014-05-23
首发时间：2014-08-27
出版时间：2014-08-28
收稿日期：2014-05-23
修回日期：2014-07-02
通讯作者:
李荣，讲师，研究方向为复杂网络上的动力学，电子信箱：lrlr1212@sina.com
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2014.24.008
引用本文
BibTeX
2种不同金属材料的力学参数
科 属数 种数 占总种数比例 属 种数 占总种数比例 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
关闭全屏
BibTeX
EndNote
RefWorks
TxT
PDF下载
全屏
585
139
关闭全屏
北京市海淀区学院南路86号
010-62199257（仅加盟咨询）
qkjq@cast.org.cn
