采用主成分策略的传感器网络路由评估算法

刘逵 1; 2; 刘三阳 2

doi:10.7652/xjtuxb201706008

您当前的位置：

首页 >

文章列表页 >

采用主成分策略的传感器网络路由评估算法

更新时间：2025-07-09

- 采用主成分策略的传感器网络路由评估算法
- Optimal Route Evaluation Method Based on Principal Component Analysis for Wireless Sensor Networks
- 西安交通大学学报 2017年51卷第6期页码：47-53
- 作者机构：
  
  1. 河南师范大学数学与信息科学学院,河南,新乡,453002
  2. 西安电子科技大学数学与统计学院,西安,710071
- 作者简介：
- 基金信息：
  
  : 2016-10-28。作者简介: 刘逵(1980—),男,博士,副教授;刘三阳(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(61373174,U1404105);河南省科技攻关计划资助项目(142102210058);河南省高等学校重点科研资助项目(16A510006);河南师范大学青年基金资助项目(2015QK02,2013QK02)
- DOI：10.7652/xjtuxb201706008
  中图分类号： TN915
- 网络首发：2017-06-10，
  
  纸质出版：2017
- 稿件说明：
移动端阅览
刘逵 1, 2, 刘三阳 2. 采用主成分策略的传感器网络路由评估算法[J]. 西安交通大学学报, 2017,51(6):47-53.

Optimal Route Evaluation Method Based on Principal Component Analysis for Wireless Sensor Networks[J]. 2017, 51(6): 47-53.
刘逵 1, 2, 刘三阳 2. 采用主成分策略的传感器网络路由评估算法[J]. 西安交通大学学报, 2017,51(6):47-53. DOI： 10.7652/xjtuxb201706008.

Optimal Route Evaluation Method Based on Principal Component Analysis for Wireless Sensor Networks[J]. 2017, 51(6): 47-53. DOI： 10.7652/xjtuxb201706008.

摘要

针对传感器网络路由在最优性评估过程中呈现的排序问题

提出了一种采用主成分策略的路由评估算法(OREPCA)。首先利用蚁群策略寻找传感器网络中的样品路由; 接着再根据实际的布网环境构建出相应的路由评价指标集; 然后对样品路由按指标集中各指标出现的顺序进行逐项打分获得评价指标向量; 最后借助主成分策略构造一个传输路由综合评价指标函数

从而实现在不同的监测环境中对网络路由的多元化评价

规避了人为选取权重因子带来的主观随意性。仿真结果表明

与基于负载均衡策略的路由优化算法及基于多目标优化的交互式路由算法相比

OREPCA算法能将网络寿命提高14%

并能有效降低网络的通信延迟。

Abstract

A novel optimal route evaluation method based on principal component analysis(OREPCA)is proposed to solve the transmission route sequencing problem appeared in the optimality evaluation process of wireless sensor networks. Sample routes information is firstly collected in a discrete time domain by using an ant colony algorithm. Then

a relevant evaluation index system of routes is constructed based on the deployment environment of the network

and a positive dimensionless method is given and is applied to the indicators of the set. The priority of all indicators is used to score each sample route and to obtain a vector of evaluation indicators. Finally

a correlation coefficient matrix among different indicators in the vector is calculated

and the principal component approach is used to obtain a route evaluation function and the weighting factor of each evaluation indicator in the function. The algorithm avoids the problem of subjective randomness caused by manually selecting weighting factors based on experience. Moreover

the evaluation function generated by the proposed method achieves the diversified evaluation and prompts dynamic server load balance in different monitoring environments. Comparisons with the multi-objective routing algorithm and the cluster based route optimisation and load balancing protocol

OREPCA can increase the lifetime of network by 14% and put down the delay of communication notably.

关键词

Keywords

references

ZHANG Degan, LI Guang, ZHENG Ke, et. al. An energy-balanced routing method based on forward-aware factor for wireless sensor networks [J]. IEEE Transactions on Industrial Information, 2010, 10(1): 63-83.

孙泽宇, 伍卫国, 曹仰杰, 等. 无线传感器网络中能量均衡参数可控覆盖算法 [J]. 西安交通大学学报, 2016, 50(8): 77-83.

SUN Zeyu, WU Weiguo, CAO Yangjie, et. al. EBPCC: energy balance parameters controlled covering algorithm for wireless sensor networks [J]. Journal of Xi'an Jiaotong University, 2016, 50(8): 77-83.

SHAH R, RABAEY J. Energy aware routing for low energy Ad Hoc sensor networks [C]∥Proceedings of IEEE International Conference for Wireless Communications and Networking. Piscataway, NJ, USA: IEEE, 2002: 350-355.

KO R S. A load-balancing routing algorithm for wireless sensor networks based on domain decomposition [J]. Ad Hoc Networks, 2015, 30(4): 63-83.

ZHU Yihua, SHEN Dandan, WU Wandeng, et al. Dynamic routing algorithms optimizing lifetime of wireless sensor networks [J]. Acta Electronica Sinica, 2009, 37(5): 1041-1045.

HAMMOUDEH M, NEWMAN R. Adaptive routing in wireless sensor networks: QoS optimization for enhanced application performance [J]. Information Fusion, 2015, 22(1): 2-15.

WANG Kun, GAO Hui, XU Xiaoling, et al. An energy-efficient reliable data transmission scheme for complex environmental monitoring in underwater acoustic sensor networks [J]. IEEE Sensors Journal, 2016, 16(11): 4051-4061.

刘逵, 刘三阳, 冯海林. 双信道无线传感器网络移动代理路由算法 [J]. 西安交通大学学报, 2012, 46(2): 113-118.

LIU Kui, LIU Sanyang, FENG Hailin. A mobile agent combination optimization routing algorithm in dual-channel wireless sensor networks [J]. Journal of Xi'an Jiaotong University, 2012, 46(2): 113-118.

XUE F, SANDERSON A, GRAVES R. Multi-objective routing in wireless sensor networks with a differential evolution algorithm [C]∥Proceedings of IEEE International Conference for Networking, Sensing and Control. Piscataway, NJ, USA: IEEE, 2006: 880-885.

MAGAIA N, HORTA N, NEVES R. A multi-objective routing algorithm for wireless multimedia sensor networks [J]. Applied Soft Computing, 2015, 30(5): 104-112.

MARCOD T. Ant colony optimization [M]. Cambridge, MA, USA: MIT press, 2006: 49-59.

BERTRAND A, MOONEN M. Distributed adaptive estimation of covariance matrix eigenvectors in wireless sensor networks with application to distributed PCA [J]. Signal Processing, 2014, 104(2): 120-135.

YIN Yihang, LIU Fengzheng, ZHOU Xiang, et. al. An efficient data compression model based on spatial clustering and principal component analysis in wireless sensors networks [J]. Sensors, 2015, 15(8): 19443-19465.

JOLLIFFE I T. Principal component analysis [M]. New York, USA: Springer Verlay New York Inc., 2010: 338-372.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

利用蚁群优化的非均匀分簇无线传感器网络路由算法

延长实时无线传感器网络生命周期的能量平衡路由

基于随机密钥预分布模型的安全定向扩散协议

基于动态门限的定向扩散算法

预测修正下的动态数据传送机制