兼容弱连通簇的Ad Hoc网络分簇算法

doi:10.3969/j.issn.1000-3428.2013.06.022

计算机工程 ›› 2013, Vol. 39 ›› Issue (6): 107-110,114.doi: 10.3969/j.issn.1000-3428.2013.06.022

兼容弱连通簇的Ad Hoc网络分簇算法

肖磊a，符云清b，钟明洋b，王兴芹a

(重庆大学 a. 计算机学院；b. 软件学院，重庆 400044)

收稿日期:2012-08-09 出版日期:2013-06-15 发布日期:2013-06-14
作者简介:肖磊(1987－)，男，硕士研究生，主研方向：无线网络技术；符云清，教授、博士；钟明洋、王兴芹，硕士研究生
基金项目:
中央高校基本科研业务费专项基金资助项目(CDJZR10090002)；重庆市自然科学基金资助项目(CSTC2010BB2248)

Clustering Algorithm for Ad Hoc Network Compatible with Weak Connection Cluster

XIAO Lei ^a, FU Yun-qing ^b, ZHONG Ming-yang^b, WANG Xing-qin ^a

(a. College of Computer Science; b. School of Software Engineering, Chongqing University, Chongqing 400044, China)

Received:2012-08-09 Online:2013-06-15 Published:2013-06-14

摘要/Abstract

摘要： 现有分簇算法生成的簇结构都是强连通的单一结构，无法充分利用节点资源。针对该问题，提出一种兼容弱连通簇的分簇算法。定义符合弱连通簇的邻居表结构，并阐述邻居表维护策略，该算法去除簇成员与簇首强连通的条件限制，从而可选择更优的节点作为簇首。分析结果表明，该算法得到的簇结构具有较好的稳定性和持续性。

关键词: 分簇算法, Ad Hoc网络, 簇首, 簇成员, 弱连通

Abstract: The clustering architectures created by the existing clustering algorithms are all single structures and strongly connected, which can not fully use nodes’ resources. To solve this problem, this paper presents an algorithm compatible with weak connection clustering algorithm. This paper defines the neighbor table corresponding with weak connected cluster and stated the maintenance strategy of the neighbor table. This algorithm can select the better node as the cluster head by ignoring the limitation of strong connectivity between cluster head and cluster members. Analysis results show that this algorithm has better stability and steadiness.

Key words: clustering algorithm, Ad Hoc network, cluster header, cluster member, weak connection

中图分类号:

TP301.6

肖磊, 符云清, 钟明洋, 王兴芹. 兼容弱连通簇的Ad Hoc网络分簇算法[J]. 计算机工程, 2013, 39(6): 107-110,114.

XIAO Lei, FU Yun-Qing, ZHONG Meng-Xiang, WANG Xin-Qin. Clustering Algorithm for Ad Hoc Network Compatible with Weak Connection Cluster[J]. Computer Engineering, 2013, 39(6): 107-110,114.

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兼容弱连通簇的Ad Hoc网络分簇算法

Clustering Algorithm for Ad Hoc Network Compatible with Weak Connection Cluster

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