计算机应用 ›› 2012, Vol. 32 ›› Issue (03): 787-790.DOI: 10.3724/SP.J.1087.2012.00787

• 网络与通信 • 上一篇    下一篇

基于最小生成树的非均匀分簇路由算法

张明才,薛安荣,王伟   

  1. 江苏大学 计算机科学与通信工程学院,江苏 镇江 212013
  • 收稿日期:2011-08-17 修回日期:2011-12-09 发布日期:2012-03-01 出版日期:2012-03-01
  • 通讯作者: 张明才
  • 作者简介:张明才(1986-),男,山东临沂人,硕士研究生,CCF会员,主要研究方向:数据挖掘、无线传感器网络;薛安荣(1964-),男,江苏镇江人,教授,博士,CCF高级会员,主要研究方向:数据库、数据挖掘;王伟(1986-),男,山东滨州人,硕士研究生,CCF会员,主要研究方向:恐怖事件与行为预测。
  • 基金资助:

    高校博士点基金资助项目(20093227110005);省科技型企业创新资金资助项目(BC2010172);校高级人才启动基金资助项目(09JDG041)。

Uneven clustering routing algorithm based on minimum spanning tree

ZHANG Ming-cai, XUE An-rong, WANG Wei   

  1. School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu 212013, China
  • Received:2011-08-17 Revised:2011-12-09 Online:2012-03-01 Published:2012-03-01
  • Contact: Ming-Cai ZHANG

摘要: 发现现有的针对非均匀分簇路由算法没有充分考虑簇首与基站之间最优路径选择,而导致传输路径上的能量消耗不均衡的问题。为了更好地均衡传输路径上节点能量的消耗,提出了基于最小生成树的非均匀分簇的路由算法。该算法利用节点剩余能量和节点到基站的距离选举簇首,然后通过建立最小生成树搜寻最优传输路径,这样可以减少传输路径上的能量消耗,有效地解决能耗不均衡问题。理论分析和实验结果均表明,该算法无论在存活节点个数还是在能量消耗上都明显优于EEUC算法和EBCA。

关键词: 簇首, 非均匀分簇, 不均衡, 剩余能量, 最小生成树

Abstract: The existing uneven clustering routing algorithms do not consider the optimal path selection between cluster heads and base station, which leads to unbalanced energy consumption. In order to balance energy consumption of transmission paths, this paper proposed an uneven clustering routing algorithm based on minimum spanning tree. The algorithm utilized residual energy of nodes and the distance between nodes and base station to select cluster heads, and then generated minimum spanning tree to search the optimal transmission paths, which reduced energy consumption on the transmission paths and effectively solved unbalanced energy consumption. The theoretical analysis and experimental results show that the algorithm is better than the existing Energy Efficient Uneven Clustering (EEUC) and Energy Balancing Clustering Algorithm (EBCA) in terms of the number of live nodes and energy consumption.

Key words: cluster head, uneven clustering, unbalanced, residual energy, minimum spanning tree

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