一种面向传感器网络的蚁群优化路径恢复算法

郑巍 1; 刘三阳 2; 寇晓丽 2

您当前的位置：

首页 >

文章列表页 >

一种面向传感器网络的蚁群优化路径恢复算法

更新时间：2025-07-09

- 一种面向传感器网络的蚁群优化路径恢复算法
- A Route Restoration Algorithm for Sensor Network via Ant Colony Optimization
- 西安交通大学学报 2010年44卷第1期页码：83-86
- 作者机构：
  
  西安电子科技大学计算机学院,西安,710071
- 作者简介：
- 基金信息：
  
  : 2009-05-25. 作者简介: 郑巍(1982-),男,博士生;刘三阳(联系人),男,教授,博士生导师. 基金项目: 国家自然科学基金资助项目(60674108,60703118);ISN重点实验室基金资助项目(ISN0208003)
- DOI：
  中图分类号： TN393
- 网络首发：2010-01-10，
  
  纸质出版：2010
- 稿件说明：
移动端阅览
郑巍 1, 刘三阳 2, 寇晓丽 2. 一种面向传感器网络的蚁群优化路径恢复算法[J]. 西安交通大学学报, 2010,44(1):83-86.

A Route Restoration Algorithm for Sensor Network via Ant Colony Optimization[J]. 2010, 44(1): 83-86.
郑巍 1, 刘三阳 2, 寇晓丽 2. 一种面向传感器网络的蚁群优化路径恢复算法[J]. 西安交通大学学报, 2010,44(1):83-86. DOI：

A Route Restoration Algorithm for Sensor Network via Ant Colony Optimization[J]. 2010, 44(1): 83-86. DOI：

摘要

为了找到动态传感器网络中的能量有效路径

提出了一种基于蚁群优化的传感器网络路径恢复算法.设计了一种新的路径选择概率模型

使得能够找到一条从源节点到sink的能量有效路径

该路径兼顾了路径能量消耗和节点剩余能量情况.为了适应网络动态变化

提出了局部信息素再初始化规则

利用该规则可在网络失效节点的附近进行局部信息素再初始化

在保留大部分原有最优路径的信息的同时

还能进行局部搜寻

以寻找新的路径

从而达到快速路径恢复的目的.仿真实验表明

所提算法在寻找路径上所消耗的能量最少

节点的剩余能量最大

在网络存在失效节点的情况下能够快速恢复路径.

Abstract

A route restoration algorithm based on the ant colony optimization(RRACO)is presented to find an energy-efficient route in dynamic sensor networks. A novel probabilistic model is constructed to find an energy-efficient route from the source node to the sink node. Both the overhead and the residual energy of nodes on routes are taken into account in the selection of the route. A new re-initialization rule for local pheromone is also presented to adapt the dynamic change of sensor networks. The rule reinitializes the local pheromone in the area where a nodes failure occurs. Most of the information for the original optimization route can be reserved and the local area can be searched. Hence the optimization route can be restored quickly. Simulation results show that the proposed method generates a route with the least overhead and the largest residual energy of the nodes

and that a new optimization route can be found very quickly when some nodes fail.

关键词

Keywords

references

ESTRIN D, GIROD L, POTTIE G, et al. Instrumenting the world with wireless sensor networks [C]∥ Proceedings of International Conference on Acoustics, Speech, and Signal Processing: ICASSP 2001. Piscataway, NJ, USA: IEEE, 2001: 2033-2036.

AKYILDIZ I F, SU W, SANKARASUBRAMANIAM Y, et al. Wireless sensor network: a survey [J]. Computer Networks, 2002, 38(4): 393-422.

AKKAYA K, YOUNIS M. A survey on routing protocols for wireless sensor network [J]. Ad Hoc Networks, 2005, 3(3): 325-349.

WU Q, RAO N S V, Barhen J, et al. On computing mobile agent routes for data fusion in distributed sensor networks [J]. IEEE Transactions on Knowledge and Data Engineering, 2004, 16(6): 740-753.

WANG Shu, YAN Yu-jie. The mobile agent-based data fusion in sensor network [J]. Chinese Journal of Sensors and Actuators, 2006, 19(3): 926-932.

LI Zhi-yu, SHI Hao-shan. A data aggregation algorithm based on grid and mobile agent in WSN [J]. Chinese Journal of Sensors and Actuators, 2008, 21(7): 1232-1236.

LIANG Hua-wei, CHEN Wan-ming. ACO-based routing for wireless sensor network [J]. Chinese Journal of Sensors and Actuators, 2007, 20(11): 2450-2455.

TIAGO C, CARLOS C, JORGE S S, et al. An energy-efficient ant-based routing algorithm for wireless sensor networks [M]. DORIGO M, GAMBARDELLA L M, BIRATTARI M, et al. LNCS, vol. 4150. Berlin, Germany: Springer, 2006: 49-59.

HEINZELMAN W R. An application-specific protocol architecture for wireless microsensor networks [J]. IEEE Trans on Wireless Communication, 2002, 1(4): 660-670.

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

蚁群优化属性约简算法

三塔合一间接空冷系统结构参数对夏季运行特性的影响研究

扇贝仿生密封腔室内超临界二氧化碳泄漏流湍动能耗散机理研究

混合电解槽阵列协同的风光耦合制氢系统双层多目标优化

隧道内燃料电池汽车氢气泄漏扩散特性及影响因素