| 基于混沌粒子群优化算法的认知网络流量分类方法研究 |
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| 引用本文： | 顾成杰,张顺颐,高飞,王晓军.基于混沌粒子群优化算法的认知网络流量分类方法研究[J].计算机应用与软件,2011,28(11). |
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| 作者姓名： | 顾成杰 张顺颐 高飞 王晓军 |
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| 作者单位： | 1. 南京邮电大学信息网络技术研究所 江苏南京210003
2. 江苏省电力公司电力科学研究院 江苏南京211103 |
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| 基金项目： | 国家高技术研究发展计划项目(2009AA01Z212) |
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| 摘 要： | 针对网络的接入形式以及网络应用日益复杂、异构和泛在等特点,当前网络所提供的服务质量QoS难以满足用户的需要。认知网络被认为是提高网络整体及端到端系统的性能、简化网络管理的新途径,是下一代通信网络发展的必然趋势。提出一种混沌粒子群优化算法(CPSO-BP),并将该算法应用于认知网络环境中对网络流量进行精确分类,以实现对以业务为中心的认知网络的可管可控。实验结果表明该方法能够充分结合粒子群优化算法的全局搜索特性和BP算法的局部搜索特性,并利用混沌搜索在小空间具有较强的局部搜索能力来提高分类精度,从而具有分类精度高、稳定性强的特点,能够有效地提高网络资源利用率,保证认知网络端到端QoS效能。
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| 关 键 词： | 粒子群 混沌机制 认知网络 流量分类 |
COGNITIVE NETWORK TRAFFIC CLASSIFICATION BASED ON CHAOTIC PARTICLE SWARM OPTIMISATION |
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| Gu Chengjie,Zhang Shunyi,Gao Fei,Wang Xiaojun.COGNITIVE NETWORK TRAFFIC CLASSIFICATION BASED ON CHAOTIC PARTICLE SWARM OPTIMISATION[J].Computer Applications and Software,2011,28(11). |
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| Authors: | Gu Chengjie Zhang Shunyi Gao Fei Wang Xiaojun |
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| Affiliation: | Gu Chengjie~1 Zhang Shunyi~1 Gao Fei~2 Wang Xiaojun~1 1(Institute of Information Network Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,Jiangsu,China) 2(Jiangsu Electric Power Research Institute,Nanjing 211103,China) |
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| Abstract: | Owing to the complexity,isomerism,and ubiquity of the access mode and network applications,current networks cannot provide the QoS meeting the requirements of users.Cognitive network(CN) is considered as a new way of improving entire network performance and end-to-end system performance as well as simplifying network management.It is the trend of the next-generation communication.A novel algorithm of chaotic particle swarm optimisation(CPSO-BP) is proposed in this paper,and is applied to cognitive network e... |
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| Keywords: | Particle swarm Chaotic mechanism Cognitive network Traffic classification |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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