WSNs routing protocol based on improved leapfrog algorithm

WU Qing; WU Kai-jun

doi:10.13873/J.1000-9787(2016)07-0126-03

Chinese

您当前的位置：

首页 >

文章列表页 >

WSNs routing protocol based on improved leapfrog algorithm

更新时间：2025-09-11

- WSNs routing protocol based on improved leapfrog algorithm
- Vol. 35, Issue 7, Pages: 126-128(2016)
- 作者机构：
  
  上海海洋大学信息学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)07-0126-03
  CLC： TP18;TN915.04;TP212.9
- Published：2016
- 稿件说明：
移动端阅览
[1]吴清,吴开军.基于改进蛙跳算法的WSNs路由协议[J].传感器与微系统,2016,35(07):126-128.

WU Qing, WU Kai-jun. WSNs routing protocol based on improved leapfrog algorithm[J]. 2016, 35(7): 126-128.
[1]吴清,吴开军.基于改进蛙跳算法的WSNs路由协议[J].传感器与微系统,2016,35(07):126-128. DOI： 10.13873/J.1000-9787(2016)07-0126-03.

WU Qing, WU Kai-jun. WSNs routing protocol based on improved leapfrog algorithm[J]. 2016, 35(7): 126-128. DOI： 10.13873/J.1000-9787(2016)07-0126-03.

摘要

在分析已有的各类分簇方法后

提出了一种改进蛙跳算法的无线传感器网络（WSNs）路由协议。将模拟退火（SA）算法的Metropolis判别准则引入到蛙跳算法中

改进蛙跳算法的局部搜索能力。该协议结合传感器节点本身剩余能量和位置建立适应度函数

通过改进蛙跳算法实现适应度函数的最优求解

从而获得合适的分簇

并在簇头节点数据传输时采用新的路由方式。仿真实验表明:该方法在降低网络能耗

延长网络的生存周期方面有明显的优势。

Abstract

After analyzing existing various clusters methods

a wireless sensor networks（ WSNs） routing protocol based on improved leapfrog algorithm is proposed. Metropolis discriminant criterion of the simulated annealing algorithm is introduced into the leapfrog algorithm

improve local search ability of leapfrog algorithm. The protocol combines residual energy and position of sensor node to establish fitness function

to achieve the optimal solution of fitness function by improving the leapfrog algorithm

so as to obtain appropriate cluster

and adopt new routing mode in data transmission of cluster head node. Simulation experiment shows that the method has obvious advantage in reducing network energy consumption and prolonging life cycle of network.

关键词

Keywords

references

基于免疫退火的WSN簇首节点选择方法研究 [J]. 陈志军,李明. 重庆师范大学学报(自然科学版) . 2014(02)

无线传感器网络中PEGASIS协议的研究与改进 [J]. 刘伟强,蒋华,王鑫. 传感技术学报 . 2013(12)

一种基于网格的无线传感器网络分簇路由协议 [J]. 钟智,樊晓平,罗大庸,刘少强,李勇周,瞿志华. 传感器与微系统 . 2011(12)

基于SFLA-FCM聚类的城市交通状态判别研究 [J]. 杨祖元,徐姣,罗兵,杜长海. 计算机应用研究 . 2010(05)

基于最佳簇数的无线传感器网络粒子群分簇协议 [J]. 郭剑,孙力娟,王汝传. 南京邮电大学学报(自然科学版) . 2010(02)

基于神经网络离散混合蛙跳算法的多用户检测 [J]. 岳克强,赵知劲,赵治栋. 计算机工程 . 2009(19)

无线传感器网络中能量有效的加权分簇算法 [J]. 朱光辉,张修如,刘卫彪. 传感器与微系统 . 2007(12)

无线传感器网络 [J]. 任丰原,黄海宁,林闯. 软件学报 . 2003(07)

无线传感器网络技术与应用[M]. 电子工业出版社 , 宋文, 2007

无线传感器网络[M]. 清华大学出版社 , 孙利民等编著, 2005

Two-phase data traffic optimization of wireless sensor networks for prolonging network lifetime [J] . Hooman Ghaffarzadeh,Ali Doustmohammadi. Wireless Networks . 2014 (4)

Comparison among five evolutionary-based optimization algorithms [J] . Emad Elbeltagi,Tarek Hegazy,Donald Grierson. Advanced Engineering Informatics . 2005 (1)

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

WSNs routing protocol based on genetic simulated annealing algorithm

A GPSR protocol for WSNs based on clustering

Multi-Sink multi-channels transmission scheme in clustered wireless sensor networks

LEACH extremum double cluster head clustering method based on CS algorithm

Research on topology evolution model for WSNs based on weight constraints in mutual selection mechanism

Related Author

CUI Xiao-yong

LIN Ning

SHEN Dan-dan

WANG Li-hua

WANG Yu

WANG Zhen-zhou

LONG Zhao-hua

BI Yun-song

Related Institution

National Marine Data & Information Service

College of Information,Shanghai Ocean University

Chinese Academy of Fishery Sciences

College of Computer Sciences and Techniques,ChongQing University of Posts andTelecommunications

School of Communication Engineering,Hangzhou Dianzi University

⁰