基于拥塞控制的无线传感网蚁群最优化路由协议

doi:10.3969/j.issn.1007-2861.2012.06.001

上海大学学报(自然科学版)

• 通信与信息工程 • 下一篇

基于拥塞控制的无线传感网蚁群最优化路由协议

金彦亮，张勇，薛用，郭灿，徐丽娜

上海大学特种光纤与光接入网省部共建重点实验室,上海 200072

收稿日期:2011-11-08 出版日期:2012-12-28 发布日期:2012-12-28
作者简介:金彦亮（1973—），男，副教授，博士，研究方向为无线传感网等. E-mail：jinyanliang@staff.shu.edu.cn
基金资助:
上海市重点学科建设资助项目（S30108）；上海市科委重点实验室资助项目（08DZ2231100）；上海市科委重点资助项目（10511501303）

Ant Colony Optimization Routing Based on Congestion Control in WSNs

JIN Yan-liang,ZHANG Yong,XUE Yong,GUO Can,XU Li-na

Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200072, China

Received:2011-11-08 Online:2012-12-28 Published:2012-12-28

摘要/Abstract

摘要： 无线传感网络（wireless sensor network，WSN）存在网络拥塞问题，并且网络的拥塞会造成丢包和能量的急剧损耗.针对网络拥塞问题，在高效节能蚁群路由(energy-efficient ant-based routing，EEABR)算法的基础上，提出基于拥塞控制的EEABR路由协议的改进的EEABR(improved EEABR，IEEABR)算法，该算法的核心是利用媒体访问控制（media access control，MAC）层上的包队列长路信息作为衡量拥塞度的标准，并作为寻找最优路径的判据之一.仿真结果表明，该算法具有投递率高和端到端时延小的特点，适合作为WSN的路由协议.

关键词: 改进的EEABR, 高效节能蚁群路由, 无线传感网络, 拥塞信息

Abstract: Wireless sensor network (WSN) suffer from the problems of congestion, leading to packet loss and excessive energy consumption. This paper propose an improved energy-efficient ant-based routing (IEEABR) algorithm to find optimization path by taking into account the packet queue length of media access control (MAC) layer, which is the degree of congestion information. Simulation results show that IEEABR has several features such as high packet delivery ratio, low overall latency and high throughput, therefore is suitable for WSN routing protocol.

Key words: congestion information, energy-efficient ant-based routing (EEABR), improved EEABR (IEEABR), wireless sensor network (WSN)

中图分类号:

TP 393

金彦亮，张勇，薛用，郭灿，徐丽娜. 基于拥塞控制的无线传感网蚁群最优化路由协议[J]. 上海大学学报(自然科学版), doi: 10.3969/j.issn.1007-2861.2012.06.001.

参考文献

1］PERKINS C E, ROYER E M. Adhoc ondemand distance vector routing ［C］∥ Second IEEE Workshop on Mobile Computing Systems and Applications (WMCSA’99). 1999:90-100.

［2］〖JP2〗COLORMI A, DORIGO M, MANIEZZO V. Distributed optimization by ant colonies ［C］∥ European Conference on Artificial Life (Proceedings of ECAL). 1991:134-142.

［3］LIU Z, KWIATKOWSKA M. A biologically inspired QoS routing algorithm for mobile ad hoc networks ［C］∥ 19th International Conference on Advanced Information Networking and Applications (AINA). 2005:426-431.

［4］SCHOONDERWOERD R, HOLLAND O, BRUTEN J, et al. Antbased load balancing in telecommunicationsnetworks ［J］. Adapt Behavior, 1996(5):169-207.

［5］IYENGAR S, WU H C, BALAKRISHNAN N, et al. Biologically inspired cooperative routing for wireless mobile sensor networks ［J］. IEEE System Journal, 2007, 9(1):29-37.

［6］LIAO W H, KAO Y, FAN C M. An ant colony algorithm for data aggregation in wireless sensor networks ［C］∥ International Conference on Sensor Technologies and Applications. 2007:101-106. 

［7］CAMILO T, CARRETO C, SILVA J, et al. An energyefficient ant base routing algorithm for wireless sensor networks ［C］∥ ANTS 2006Fifth International Workshop on Ant Colony Optimization and Swarm Intelligence. 2006:49-59.

［8］DI CARO G, DORIGO M. AntNet: Distributed stigmergetic〖JP〗 control for communications networks ［J］. Journal of Artificial Intelligence Research, 1998, 9:317-365.

［9］YAN J F, GAO Y, YANG L. Ant colony optimization for wireless sensor networks routing ［C］∥ Machine Learning and Cybernetics (ICMLC) 2011 International Conference. 2011:400-403. 

［10］ HUANG R, CHEN Z H, XU G H. Energyaware routing algorithm in WSN using predicationmode ［C］∥Communications, Circuits and Systems (ICCCAS). 2010:103-107.

［11］ BHUIYAN M M, GONDAL I, KAMRUZZAMAN J. Location aided congestion aware routing in wireless sensor networks ［C］∥ Wireless Communications and Networking Conference (WCNC). 2010:1-6.

基于拥塞控制的无线传感网蚁群最优化路由协议

Ant Colony Optimization Routing Based on Congestion Control in WSNs

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