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

页码：287 / 291

页数：5