基于紧密中心性的无线mesh骨干网网关部署

郭诚欣; 李陶深; 葛志辉

doi:10.3969/j.issn.1000-0801.2015045

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基于紧密中心性的无线mesh骨干网网关部署

研究与开发 | 更新时间：2024-06-05

- 基于紧密中心性的无线mesh骨干网网关部署
- Gateway Deployment Optimization in Wireless Mesh Backbone Network Based on Closeness Centrality
- 电信科学 2015年31卷第2期页码：80-85
- 作者机构：
- 作者简介：
  
  [ "郭诚欣，男，广西大学计算机与电子信息学院硕士生，主要研究方向为无线 mesh网络。" ]
  [ "李陶深，男，博士，广西大学计算机与电子信息学院教授，主要研究方向为无线mesh网络、分布式数据库、云计算。" ]
  [ "葛志辉，男，博士，广西大学计算机与电子信息学院教授，主要研究方向为无线网络。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61363067);国家自然科学基金资助项目;The National Natural Science Foundation of China(60963022);广西自然科学基金资助项目;Guangxi Nature Science Foundation，China(2012GXNSFAA053226)
- DOI：10.3969/j.issn.1000-0801.2015045
  中图分类号：
- 网络出版日期：2015-02，
  
  纸质出版日期：2015-02-15
- 稿件说明：
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郭诚欣, 李陶深, 葛志辉. 基于紧密中心性的无线mesh骨干网网关部署[J]. 电信科学, 2015,31(2):80-85.

Chengxin Guo, Taoshen Li, Zhihui Ge. Gateway Deployment Optimization in Wireless Mesh Backbone Network Based on Closeness Centrality[J]. Telecommunication science, 2015, 31(2): 80-85.
郭诚欣, 李陶深, 葛志辉. 基于紧密中心性的无线mesh骨干网网关部署[J]. 电信科学, 2015,31(2):80-85. DOI： 10.3969/j.issn.1000-0801.2015045.

Chengxin Guo, Taoshen Li, Zhihui Ge. Gateway Deployment Optimization in Wireless Mesh Backbone Network Based on Closeness Centrality[J]. Telecommunication science, 2015, 31(2): 80-85. DOI： 10.3969/j.issn.1000-0801.2015045.

摘要

将定向天线和Delaunay图应用于无线mesh骨干网络的网关部署，提出了基于紧密中心性的无线mesh骨干网络网关部署算法。根据已知的mesh路由器和网关的最大流通量对网络进行划分，形成Delaunay子图，在划分的子图中根据欧几里德距离找出距离中心点最近的3个节点，形成候选网关集，在候选网关集中选择到其他节点总路径最短的节点作为网关的部署位置，将每个子图的网关位置输出。仿真结果表明，根据网关最大流通量进行合理网络划分后，算法能最小化网络的网关数量，由mesh路由器到网关的总路径长度优于随机算法。

Abstract

Directional antenna and Delaunay graph were used in the gateway deployment optimization of wireless mesh backbone network and a gateway deployment optimization algorithm of wireless mesh backbone network based on closeness centrality was proposed. Firstly

according to the largest traffic of mesh router and gateway

the algorithm divides the network into a few clusters forming Delaunay sub-graph. In the sub-graph

according to the Euclidean distance of each nodes to the center nodes

the algorithm find out the closest three nodes to the center nodes and form the gateway candidate set. The node in this gateway candidate set

which has the shortest route path to the other nodes

is the location of gateway of this cluster. Gateway location of each sub-graph will be achieved in the end. Simulation experimental results show that

after reasonable network partitioning according to the largest traffic of gateway

the algorithm can minimize the number of network gateway. The total path length from the mesh routers to the gateway of the algorithm is better than that of the random algorithm.

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references

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