期刊文献+

WMN下一种差异度蚁群QoS路由算法IARQM

An Improved ACO Routing Algorithm Based on Multi-constrained Qo S for Wireless Mesh Network
在线阅读 下载PDF
导出
摘要 为了支持无线Mesh网络(Wireless Mesh Network,WMN)中多媒体实时应用,必须提供更好的服务质量(Quality of Service,Qo S).为此,提出一种基于差异度蚁群的WM N多约束Qo S路由算法(Improved ACO Routing Algorithm Based on M ulti-Constrained Qo S for Wireless M esh Netw ork,IARQM),该算法利用归一化后的路径Qo S信息和路径差异度调节信息素增量,并用其替代目标函数,在发挥最优路径激励作用的同时提高了算法效率.IARQM根据节点类型对下一跳节点选择进行调整,能充分适应WMN特点,并在链路失效后利用邻居管理提供恢复容错机制,具有很强的健壮性.实验结果表明,与ARMAN、QSS路由算法和AODV路由协议相比,IARQM能更好地支持WM N多约束Qo S路由,并有效提升网络性能. To support real-time multimedia applications for wireless mesh network ( WMN ), higher quality of service ( QoS ) should be guaranteed. In this paper, we proposed an improved ACO ( Ant colony optimization ) routing algorithm based on multi-constrained QoS for wireless mesh network( IARQM). The algorithm uses the normalized path QoS information and the degree of difference between the paths to calculate the pheromone increment. Then we substitute the pheromone increment for objective function. Our algorithm can fully adapt to WMN topology by using different methods for various node types, and provides a special local connection management. Link recovery time can be given after the failure to improve the robustness of the algorithm. Simulation results demonstrate that the proposed algorithm is more feasible and effective than ARMAN( Ant Routing for Mobile Ad Hoc Networks ), QSS (Ant Colony based Multi Constraints QoS Aware Service Selection) and AODV ( Ad hoc On-Demand Distance Vector Routing).
出处 《小型微型计算机系统》 CSCD 北大核心 2014年第12期2633-2638,共6页 Journal of Chinese Computer Systems
关键词 多约束Qo S路由 无线MESH网络 蚁群算法 差异度 邻居管理 multi-constrained QoS routing wireless mesh network ant colony optimization degree of difference neighbors management
作者简介 段汐。女,1989年生,硕士研究生,研究方向为智能优化算法、无线Mesh网络、并行计算; 杨群。女,1971年生,博士,副教授,主要研究方向为软件方法学、并行计算; 陈兵,男,1970年生,博士,教授,主要研究方向为计算机网络、无线网络、网络安全; 钱红燕。女,1973年生,博士,讲师,主要研究方向为无线网络; 李媛祯。女,1990年生,硕士研究生,主要研究方向为并行计算、智能优化算法.
  • 相关文献

参考文献4

二级参考文献67

  • 1Ramaswami R and Sivarajan K N.Optical Networks:APractical Perspective[M].San Francisco,CA,MorgmKouJkann Publishers Inc.,2002:255-380.
  • 2Chen Chien and Banerjee S.A new model for optimal routingand wavelength assignment in wavelength divisionmultiplexed optical networks[C].International Conference onComputer Communications96(INFOCOM96),San Francisco,CA,USA,1996:164-171.
  • 3Xu Shi-zhong,Li Le-min,and Wang Sheng.Dynamicrouting and assignment of wavelength algorithms inmultifiber wavelength division multiplexing network[J].IEEEJournal on Selected Areas in Communications,2000,18(10):2130-2137.
  • 4Barpanda R S,Turuk A K,Sahoo B,et al..Genetic algorithmtechniques to solve routing and ravelength assignmentproblem in wavelength division multiplexing all-opticalnetworks[C].Communication Systems and Networks(COMSNETS),Bangalore,2011,3:1-8.
  • 5Yetginer E,Liu Ze-yu,and Rouskas G N.Fast exact ILPdecompositions for ring RWA[J].Optical Communicationsand Networking,2011,3(7):557-586.
  • 6Triay J,and Cervelló-Pastor C.An ant-based algorithm fordistributed routing and wavelength assignment in dynamicoptical network[J].IEEE Journal on Selected Areas inCommunications,2010,28(4):542-552.
  • 7Dorigo M,and Stützle T著,张军,等,译.蚁群优化[M].北京:清华大学出版社,2007:21-58.
  • 8De Maesschalck S.Pan-european optical transport network:an availability-based comparison[J].Photonic NetworkCommunications,2003,5(3):203-225.
  • 9Eusuff M,Lansey K,Pasha F.Shuffled frog-leaping algorithm:A memetic meta-heuristic for discrete optimization[J].Engineering Optimization,2006,38(2):129-154.
  • 10Li Y H,Zhou J Z,Yang J J,et al.The chaos-based shuffled frog leaping algorithm and its application[C].4th Int Conf on Natural Computatione.New York:IEEE Press,2006:481-485.

共引文献131

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部