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国家自然科学基金(60973129)

作品数:6 被引量:5H指数:1
相关作者:张连明王莎廖进中唐宇凌更多>>
相关机构:湖南师范大学湖南大学更多>>
发文基金:国家自然科学基金中国博士后科学基金广东省自然科学基金更多>>
相关领域:自动化与计算机技术自然科学总论电子电信更多>>

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Internet AS拓扑的“73/27”规律
2010年
为了深入理解和认清Internet AS拓扑中节点度的分配规律,提出适合Internet AS拓扑的幂律模型,利用该模型推导Internet AS拓扑中最富有节点数占网络总节点数的比例与这些最富有节点所拥有的节点度数占网络节点总度数的比例之间的关系,分析研究幂律指数和最大节点度等拓扑参数对该比例关系的影响,通过数值分析发现Internet AS拓扑中27%的最富有节点拥有约73%的节点度数(简称为"73/27"规律),基于Internet AS拓扑经验数据对上述结果进行验证分析,结果表明该幂律模型对Internet AS拓扑是有效的,Internet AS拓扑存在"73/27"规律。
张连明
关键词:INTERNET自治系统
Virtualized Wireless SDNs:Modelling Delay Through the Use of Stochastic Network Calculus被引量:1
2014年
Software-defined networks (SDN) have attracted much attention recently because of their flexibility in terms of network management. Increasingly, SDN is being introduced into wireless networks to form wireless SDN. One enabling technology for wireless SDN is network virtualization, which logically divides one wireless network element, such as a base station, into multiple slices, and each slice serving as a standalone virtual BS. In this way, one physical mobile wireless network can be partitioned into multiple virtual networks in a software-defined manner. Wireless virtual networks comprising virtual base stations also need to provide QoS to mobile end-user services in the same context as their physical hosting networks. One key QoS parameter is delay. This paper presents a delay model for software-defined wireless virtual networks. Network calculus is used in the modelling. In particular, stochastic network calculus, which describes more realistic models than deterministic network calculus, is used. The model enables theoretical investigation of wireless SDN, which is largely dominated by either algorithms or prototype implementations.
Lianming ZhangJia LiuKun Yang
基于标签的微博人脉网络挖掘算法和结构分析被引量:2
2014年
针对互联网微博业务的广泛应用及其对大数据挖掘和分析的影响,提出一种基于标签的微博人脉网络挖掘算法。分析该网络的结构特征,利用微博用户标签,在模糊匹配过程中计算词语之间的匹配度时,主要考虑词语语素、次序和词长3个因素。为弱化以不同用户为起点对算法准确率的影响,分别以普通用户和名人用户为起点用户,挖掘微博人脉网络数据。同时,研究微博人脉网络的结构特性,通过分析发现微博人脉网络同时具有小世界和无标度特性。实验结果表明,运用该算法对名人用户和普通用户朋友中对IT感兴趣的人进行挖掘的误差率是可接受的。其中,挖掘10个名人用户朋友时算法的平均误差率为14.08%,挖掘10个普通用户朋友时算法的平均误差率为10.63%。
王莎张连明
关键词:标签数据挖掘结构特征
Degree and connectivity of the Internet's scale-free topology
2011年
This paper theoretically and empirically studies the degree and connectivity of the Internet's scale-free topology at an autonomous system (AS) level. The basic features of scale-free networks influence the normalization constant of degree distribution p(k). It develops a new mathematic model for describing the power-law relationships of Internet topology. From this model we theoretically obtain formulas to calculate the average degree, the ratios of the kmin-degree (minimum degree) nodes and the kmax-degree (maximum degree) nodes, and the fraction of the degrees (or links) in the hands of the richer (top best-connected) nodes. It finds that the average degree is larger for a smaller power-law exponent A and a larger minimum or maximum degree. The ratio of the kmin-degree nodes is larger for larger λ and smaller kmin or kmax. The ratio of the kmax-degree ones is larger for smaller λ and kmax or larger kmin. The richer nodes hold most of the total degrees of Internet AS-level topology. In addition, it is revealed that the increased rate of the average degree or the ratio of the kmin-degree nodes has power-law decay with the increase of kmin. The ratio of the kmax-degree nodes has a power-law decay with the increase of kmax, and the fraction of the degrees in the hands of the richer 27% nodes is about 73% (the 73/27 rule'). Finally, empirically calculations are made, based on the empirical data extracted from the Border Gateway Protocol, of the average degree, ratio and fraction using this method and other methods, and find that this method is rigorous and effective for Internet AS-level topology.
张连明邓晓衡余建平伍祥生
区域旅游合作—竞争网络演化建模与仿真被引量:1
2012年
基于旅游目的地和旅游者二类节点的区域旅游合作—竞争网络二分图,构建了一个基于吸引优先连接的区域旅游合作—竞争网络演化模型,用于描述各旅游目的地累积接待旅游者人数增长演化过程。以中国入境旅游系统2005~2009年数据为例,采用SPSS软件对演化模型的仿真理论值和实际值进行回归分析,探索该模型的正确性。由于F=1.005×104>F1,29(0.05)=4.18,因而从统计意义上验证吸引优先连接是该网络的关键演化机制。
唐宇凌廖进中张连明
关键词:复杂网络
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