Load balancing routing scheme for wireless multimedia sensor networks using ant colony optimization

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (18): 80-84.

• 网络、通信、安全 • Previous Articles Next Articles

Load balancing routing scheme for wireless multimedia sensor networks using ant colony optimization

BI Junlei1，LI Zhiyuan2

1.Department of Computer Engineering，Henan Polytechnic Institute，Nanyang，Hennan 473009，China
2.College of Computer，Nanjing University of Posts and Telecommunications，Nanjing 210003，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-06-21 Published:2011-06-21

使用蚁群优化的WMSNs负载均衡路由方案

毕俊蕾1，李致远2

1.河南工业职业技术学院计算机工程系，河南南阳 473009
2.南京邮电大学计算机学院，南京 210003

Abstract

Abstract: Due to the characteristics of Wireless Multimedia Sensor Networks（WMSNs），such as limited resources，variable channel capacities and highly redundant data，researching on the QoS routing of WMSNs is of great challenges.Aiming at these challenges，a Ant Colony Optimization based Load Balancing Routing（ACOLBR） scheme for WMSNs is proposed.The network is divided by a novel clustering algorithm.Then on the basis of the hierarchical topology，an optimal path from cluster heads to base station is built by the ant colony optimization algorithm.The routing between cluster members and their cluster heads is built by a minimum spanning tree algorithm?within clusters.The simulation results show that ACOLBR has better scalability，adaptability，load balancing，transmission success rate and delay performance than AGRA（Ant-like Game Routing Algorithm for WMSNs） and M-IAR（Multimedia-enabled Improved Adaptive Routing） algorithms.Therefore，ACOLBR can achieve load balancing，effectively prolong the network lifetime and guarantee the QoS of the data transmission.?

Key words: Wireless Multimedia Sensor Networks（WMSNs）, QoS routing, Ant Colony Optimization（ACO）, clustering technology, load balancing

摘要： 由于无线多媒体传感器网络（WMSNs）具有资源受限、信道容量可变、数据冗余度高等特点，研究WMSNs的QoS 路由具有极大的挑战性。针对上述问题，提出了一种使用蚁群优化的WMSNs负载均衡路由方案——ACOLBR。ACOLBR采用分簇技术进行区域划分，簇间利用ACO找到一条簇首到基站的最优路径，簇内利用以簇首为根节点的最小生成树算法组织路由。仿真结果表明，与AGRA和M-IAR算法相比，ACOLBR在负载均衡、传输时延、传输成功率、可扩展性和自适应性等方面均有较大改进，实现了全网的负载均衡，有效地延长了网络生命期，保证了网络传输的QoS。

关键词: 无线多媒体传感器网络, QoS路由, 蚁群优化, 分簇技术, 负载均衡

BI Junlei1，LI Zhiyuan2. Load balancing routing scheme for wireless multimedia sensor networks using ant colony optimization[J]. Computer Engineering and Applications, 2011, 47(18): 80-84.

毕俊蕾1，李致远2. 使用蚁群优化的WMSNs负载均衡路由方案[J]. 计算机工程与应用, 2011, 47(18): 80-84.

[1]	ZHANG Ming, DENG Wenhan, LIN Juan, ZHONG Yiwen. Modified Ant Colony Optimization Algorithm for Discounted {0-1} Knapsack Problem [J]. Computer Engineering and Applications, 2021, 57(13): 85-95.
[2]	SONG Fangzhen, XU Yanyan, TANG Xin, PAN Shaoming. Emergency Communication Network Routing Protocol Based on Improved Ant Colony Algorithm [J]. Computer Engineering and Applications, 2020, 56(18): 90-96.
[3]	WANG Xia, DONG Yongquan, YU Qiao, GENG Na. Review of Structural Support Vector Machines [J]. Computer Engineering and Applications, 2020, 56(17): 24-32.
[4]	JIANG Daoyin1，2, GE Hongwei1，2, YUAN Luo1. Density dynamic partition hybrid ant colony optimization for continuous domains [J]. Computer Engineering and Applications, 2018, 54(7): 144-151.
[5]	KONG Lin1, ZHANG Guofu1，2, SU Zhaopin1，2, JIANG Jianguo1，2. Ambulance emergency rescue routing planning for improved ant colony algorithm [J]. Computer Engineering and Applications, 2018, 54(13): 153-159.
[6]	LING Haifeng1，2, GU Junhui1. Study on multi-depot open vehicle routing problem with soft time windows [J]. Computer Engineering and Applications, 2017, 53(14): 232-239.
[7]	YUAN Liqiao, YANG Xiwang, YANG Mengru. Research on QoS routing algorithm based on PSO classified by BP neural network [J]. Computer Engineering and Applications, 2015, 51(9): 98-102.
[8]	ZHU Xiaoping1, ZHANG Zeqiang2. Ant Colony Optimization for two sided assembly line balancing with station flipping task [J]. Computer Engineering and Applications, 2014, 50(6): 240-245.
[9]	XIAO Guorong. Network intrusion detection by combination of improved ACO and SVM [J]. Computer Engineering and Applications, 2014, 50(3): 75-78.
[10]	HU Hui1, HE Juhou1，2, HE Xiuqing1. Edge linking method based on fuzzy theory and ant colony algorithm [J]. Computer Engineering and Applications, 2014, 50(3): 168-172.
[11]	TIAN Haimei1, HUANG Nan2. Network traffic prediction based on LSSVM optimized by ACO [J]. Computer Engineering and Applications, 2014, 50(1): 91-95.
[12]	HUANG Yongqing1, HAO Guosheng2, ZHONG Zhishui1, HU Weicheng1, DU Juan1. Improved ant colony algorithm based on grid strategy for continuous space optimization [J]. Computer Engineering and Applications, 2013, 49(9): 61-64.
[13]	LING Haifeng1，2, CAO Rongtao1，2. Hybrid Ant Colony Algorithm for Web user session clustering [J]. Computer Engineering and Applications, 2013, 49(22): 136-138.
[14]	LIU Xuedong1, XU Feng2. Hybrid ant colony genetic algorithm based on change rate of objective function [J]. Computer Engineering and Applications, 2013, 49(18): 41-44.
[15]	YU Qianqian, DAI Yueming, LI Jingjing. Parallel ACO-K-means clustering algorithm based on MapReduce [J]. Computer Engineering and Applications, 2013, 49(16): 117-120.

Load balancing routing scheme for wireless multimedia sensor networks using ant colony optimization

使用蚁群优化的WMSNs负载均衡路由方案

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics