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1. 北京航空航天大学计算机学院,北京100191
2. 国家计算机网络应急技术处理协调中心,北京100029
[ "高壮良(1990-),男,山东菏泽人,北京航空航天大学硕士生,主要研究方向为分布式图计算。" ]
[ "吕雁飞(1984-),男,辽宁朝阳人,博士,国家计算机网络应急技术处理协调中心工程师,主要研究方向为大数据技术。" ]
[ "张鸿(1976-),男,陕西西安人,博士,国家计算机网络应急技术处理协调中心高级工程师,主要研究方向为云计算、大数据、网络安全。" ]
网络出版日期:2016-03,
纸质出版日期:2016-03-25
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高壮良, 吕雁飞, 张鸿. 基于Graphlab的网络图关键节点发现算法研究[J]. 通信学报, 2016,37(3):182-189.
Zhuang-liang GAO, Yan-fei LYU, Hong ZHANG. Key nodes discovery in network graph based on Graphlab[J]. Journal on communications, 2016, 37(3): 182-189.
高壮良, 吕雁飞, 张鸿. 基于Graphlab的网络图关键节点发现算法研究[J]. 通信学报, 2016,37(3):182-189. DOI: 10.11959/j.issn.1000-436x.2016066.
Zhuang-liang GAO, Yan-fei LYU, Hong ZHANG. Key nodes discovery in network graph based on Graphlab[J]. Journal on communications, 2016, 37(3): 182-189. DOI: 10.11959/j.issn.1000-436x.2016066.
针对桥接中心度的计算特点设计了一种分布式的网络图关键节点发现算法(DABC),并基于 Graphlab进行了实现。算法具有良好的扩展性,由于能够利用集群的内存资源,算法能处理的图规模与集群的大小成正比,并且该算法利用并行处理大幅度提升了计算速度。实验表明,与传统的基于单机实现的关键节点发现算法相比,算法可以获得高达4倍的性能提升。
A distributed key nodes discovery algorithm was proposed(DABC) which was implemented on Graphlab.Due to the good scalability
the scale of graph supported by algorithm was enlarged significantly.The parallel processing also enhances the speed of calculation.Experiment results show that proposed algorithm can achieve up to 4 times per-formance improvement compared with the traditional centralized key node discovery algorithm.
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