A Distributed Tree-Based Energy-Efficient Algorithm for Precise Data Gathering in Wireless Sensor Networks

CHEN Ling; WANG Jian-xin; ZHANG Shi-geng; KUI Xiao-yan

doi:10.3969/j.issn.0372-2112.2013.09.011

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A Distributed Tree-Based Energy-Efficient Algorithm for Precise Data Gathering in Wireless Sensor Networks

更新时间：2025-07-16

- A Distributed Tree-Based Energy-Efficient Algorithm for Precise Data Gathering in Wireless Sensor Networks
- Acta Electronica Sinica Vol. 41, Issue 9, Pages: 1738-1743(2013)
- 作者机构：
  
  中南大学信息科学与工程学院,湖南,长沙,410083
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61173169);Youth Fund of National Natural Science Foundation of China (No.61103203, No.61204294);Key Project of National Natural Science Foundation of China (No.61232001)
- DOI：10.3969/j.issn.0372-2112.2013.09.011
  CLC： TP301
- Published：2013
- 稿件说明：
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CHEN Ling, WANG Jian-xin, ZHANG Shi-geng, et al. A Distributed Tree-Based Energy-Efficient Algorithm for Precise Data Gathering in Wireless Sensor Networks[J]. Acta Electronica Sinica, 2013, 41(9): 1738-1743.
DOI：

CHEN Ling, WANG Jian-xin, ZHANG Shi-geng, et al. A Distributed Tree-Based Energy-Efficient Algorithm for Precise Data Gathering in Wireless Sensor Networks[J]. Acta Electronica Sinica, 2013, 41(9): 1738-1743. DOI： 10.3969/j.issn.0372-2112.2013.09.011.

摘要

在大规模节点密集的多跳传感器网络中

精确数据收集存在着"热区"问题:越靠近Sink节点的传感器节点

其承担的数据转发量就越多

能量消耗也越快

从而成为瓶颈节点

缩短整个网络的生命周期.最大生命周期数据收集树的构建已被证明是NP完全问题.已有算法大多是集中式算法

不适用于大规模节点密集的传感器网络.本文提出一种分布式精确数据收集算法EEDAT

在大规模节点密集的传感器网络中

不仅能够保证每个节点到Sink的路径是最短路径(最少跳数)

而且能有效延长网络生命周期.EEDAT分为两个基本步骤

首先随机生成一棵数据收集树

然后根据各个传感器节点的孩子数和剩余能量

对已生成的数据收集树进行调整

使得各个节点的负载尽量均衡

从而达到延长网络生命周期的目的.实验结果表明

与已有分布式算法LMST相比

EEDAT所构造的数据收集树能延长网络生命周期平均20%.

Abstract

In this paper

we propose a distributed tree-based algorithm for precise data gathering in wireless sensor networks called EEDAT

which achieves longer network lifetime than existing distributed algorithms.The EEDAT algorithm has two steps.In the first step

a shortest path tree is constructed in a distributed manner.In the second step

EEDAT adjusts the load of nodes in the generated tree to balance energy consumption of different nodes

which effectively extends the lifetime of the network.In the adjustment

both the number of children of a node and its residual energy are considered.Simulation results show that EEDAT achieves longer lifetime than the LMST algorithm.On average

compared with LMST

EEDAT prolongs the lifetime by 20%.

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