A Study on Matching Algorithm in Multilevel K-way for Partitioning Topology under The Cognitive Network Environment

被引：0
|
作者：
Zhou Anyu [1 ]
Wang Huiqiang [1 ,2 ]
Song, Peiyou [3 ]
机构：
[1] Harbin Engn Univ, Harbin, Peoples R China
[2] Harbin Univ Comm, Harbin, Peoples R China
[3] Univ New Mexico, Albuquerque, NM 87131 USA
来源：
2011 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), VOLS 1-4 | 2012年
基金：
中国国家自然科学基金;
关键词：
cognitive network; network topology; graph partitioning; multilevel k-way partitioning; matching algorithm; light-vertex matching; IRREGULAR GRAPHS; SCHEME;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to study the cognitive networks, the multilevel k-way partitioning methods and the coarsening strategies for graphs are studied. The four kinds of classic matching algorithm used in the coarsening stage for multilevel k-way partitioning an irregular graph are introduced, including random matching, heavy-edge matching, improved heavy-edge matching, and light-edge matching algorithm. The basic idea and specific process of light-vertex matching algorithm are described, which is proposed for the features of network topology. In the case of that the weight of a vertex has positive correlation with the sum edges weight connected to, the light-vertex matching algorithm works better than the other algorithms on balance and edge cuttings. Furthermore, a method to improve light-vertex matching algorithm is proposed.
引用
收藏
页码：287 / 291
页数：5
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