J4 ›› 2012, Vol. 39 ›› Issue (3): 20-26.doi: 10.3969/j.issn.1001-2400.2012.03.004

• 研究论文 • 上一篇    下一篇

WSN中六边形集中式分簇多跳路由协议

李桢;陈健;阔永红   

  1. (西安电子科技大学 通信工程学院,陕西 西安  710071)
  • 收稿日期:2011-10-25 出版日期:2012-06-20 发布日期:2012-07-03
  • 通讯作者: 李桢
  • 作者简介:李桢(1987-),男,西安电子科技大学硕士研究生,E-mail: lizhendz@sina.com.
  • 基金资助:

    国家自然科学基金资助项目(60972072);高等学校学科创新引智计划资助项目(B08038)

Hexagonal centralized cluster-based multi-hop routing protocol for WSN

LI Zhen;CHEN Jian;KUO Yonghong   

  1. (School of Telecommunications Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2011-10-25 Online:2012-06-20 Published:2012-07-03
  • Contact: LI Zhen

摘要:

针对节点随机分布的大规模无线传感器网络,提出了一种六边形集中式分簇多跳路由协议(HCCM).基站根据能耗确定簇内平均节点数,并以合适的边长确定六边形完成初步分簇; 根据簇内的节点数进行分簇优化;依据节点剩余能量选择簇头及传输路径,分配合适的时隙以多跳形式完成信息的传输.仿真结果表明,与LEACH协议及其改进的协议(DE-LEACH)相比,在小规模网络中,协议HCCM延长了网络寿命,但接收的数据包数较少,性能略差; 在大规模网络中,协议HCCM提高了网络性能,比改进的协议(EECT)网络寿命延长了15%,接收的数据包增加了9.5%.

关键词: 无线传感器网络, 路由协议, 随机分布, 六边形, 分簇

Abstract:

For random distribution of large-scale wireless sensor networks (WSNs), a hexagonal centralized cluster-based multi-hop routing protocol (HCCM) is proposed. The base station divides clusters with the lowest energy consumption by choosing the length of a hexagon, and then optimizes clusters according to the number of nodes in practice. Based on the received energy information, the cluster head and multi-hop transmission path are determined with suitable slots being allotted to transmit data. Simulation results show that compared with the low energy adaptive cluster hierarchy (LEACH) and differential evolution-based routing algorithm (DE_LEACH), this protocol prolongs the network life with fewer packets being received in the small scale network. But in large scale networks, this protocol prolongs the network life by 15% and receives 9.5% more packets compared with the energy-efficient clustering technique(EECT), thus improving the network performance, which verifies that this protocol is suitable for large-scale WSNs.

Key words: wireless sensor networks, routing protocol, random distribution, hexagonal, clustering

中图分类号: 

  • TP393