• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (04): 661-666.

• 论文 • 上一篇    下一篇

WSN中一种负载均衡的动态非均匀分簇方案

刘涛1,关亚文1,王骏2   

  1. (1.安徽工程大学计算机与信息学院,安徽 芜湖 241000;2.美国哥伦比亚大学电子工程系,纽约 10598)
  • 收稿日期:2015-04-10 修回日期:2015-10-19 出版日期:2016-04-25 发布日期:2016-04-25
  • 基金资助:

    国家自然科学基金(61300170);安徽省教育厅重点资助项目( KJ2013A040) ;安徽省自然科学基金(1308085MF88);安徽工程大学青年基金(2013YQ28)

A dynamic uneven clustering scheme with load
balancing in wireless sensor network   

LIU Tao1,GUAN Yawen1,WANG Jun2   

  1. (1.School of Computer and Information,Anhui Polytechnic University,Wuhu 241000,China;
    2.Department of Electrical Engineering,Columbia University,New York 10598,USA)
  • Received:2015-04-10 Revised:2015-10-19 Online:2016-04-25 Published:2016-04-25

摘要:

无线传感器网络(WSN)是由资源受限的传感器节点构成,节点能耗对网络的性能有着重要影响,对网络进行分簇可以有效地控制节点整体能耗。针对网络实际运行时节点状态和事件位置动态变化等特点,提出了一种负载均衡的动态非均匀分簇方案。方案主体思路是:首先网络利用OLEACH算法自组织地进行非均匀分簇,接着动态地从簇头中选举出一定数量的决策节点用于网络的数据汇聚,并根据事件发生位置和节点状态变换而动态更改决策节点角色。仿真结果表明,与CAPNet方案相比,该方案均衡了网络能耗,提高了传输效率,延长了网络生命周期。

关键词: 无线传感器网络, 非均匀分簇, 动态, 负载均衡, 决策节点

Abstract:

A wireless sensor network (WSN) consists of several sensor nodes, all of which are resource limited, and the energy consumption on every node has significant influence on the network. Clustering schemes can effectively control overall energy consumption. Based on the characteristics of the node status, the dynamic change of the event location at the actual running phase of the network, we propose a dynamic uneven clustering scheme with load balancing. The main idea is that the network completes uneven clustering using the OLEACH algorithm with self organization, and then a certain number of decision nodes from the cluster heads are selected dynamically for data aggregation. The role of decision nodes changes dynamically with the transformation of the event location and node state. Simulation results show that the scheme balances the energy consumption, improves transmission efficiently and prolongs the network life in comparison with the CAPNet scheme.

Key words: wireless sensor network;uneven clustering;dynamic;load balancing;decision nodes