认知网络基于跨层感知的接入选择机制

王慧强; 陈晓明; 吕宏武; 冯光升; 朱强

doi:10.11959/j.issn.1000-436x.2015214

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认知网络基于跨层感知的接入选择机制

学术论文 | 更新时间：2024-06-05

- 认知网络基于跨层感知的接入选择机制
- Access point selection mechanism based on cross-layer awareness for cognitive networks
- 通信学报 2015年36卷第10期页码：188-199
- 作者机构：
  
  1. 哈尔滨工程大学计算机科学与技术学院，黑龙江哈尔滨150001
  2. 哈尔滨理工大学管理学院，黑龙江哈尔滨 150080
- 作者简介：
  
  [ "王慧强（1960-），男，河南周口人，博士，哈尔滨工程大学教授、博士生导师，主要研究方向为可信计算、自律计算、认知网络、网络技术与信息安全、网络安全态势感知等。" ]
  [ "陈晓明（1983-），女，黑龙江哈尔滨人，哈尔滨工程大学博士生，主要研究方向为认知网络、跨层设计、异构网络接入、网络体系结构等。" ]
  [ "吕宏武（1983-），男，山东日照人，博士，哈尔滨工程大学讲师，主要研究方向为自律计算与可信计算、自省模型研究等。" ]
  [ "冯光升（1980-），男，山东德州人，博士，哈尔滨工程大学讲师、硕士生导师，主要研究方向为异构网络接入、自律计算、网络安全态势感知。" ]
  [ "朱强（1986-），男，山东招远人，哈尔滨工程大学博士生，主要研究方向为网络虚拟化和云计算。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61370212);国家自然科学基金资助项目(61402127);国家自然科学基金资助项目(61502118);教育部博士点基金优先发展领域基金资助项目(20122304130002);黑龙江省自然科学基金资助项目(ZD201102);中央高校基本科研业务费专项资金项目(HEUCF100601);中央高校基本科研业务费专项资金项目(HEUCFZ1213);黑龙江省博士后基金资助项目(LBH-210204);黑龙江省自然科学基金资助项目(F2015029)
- DOI：10.11959/j.issn.1000-436x.2015214
  中图分类号： TP393
- 网络出版日期：2015-10，
  
  纸质出版日期：2015-10-25
- 稿件说明：
移动端阅览
王慧强, 陈晓明, 吕宏武, 等. 认知网络基于跨层感知的接入选择机制[J]. 通信学报, 2015,36(10):188-199.

Hui-qiang WANG, Xiao-ming CHEN, Hong-wu LV, et al. Access point selection mechanism based on cross-layer awareness for cognitive networks[J]. Journal on communications, 2015, 36(10): 188-199.
王慧强, 陈晓明, 吕宏武, 等. 认知网络基于跨层感知的接入选择机制[J]. 通信学报, 2015,36(10):188-199. DOI： 10.11959/j.issn.1000-436x.2015214.

Hui-qiang WANG, Xiao-ming CHEN, Hong-wu LV, et al. Access point selection mechanism based on cross-layer awareness for cognitive networks[J]. Journal on communications, 2015, 36(10): 188-199. DOI： 10.11959/j.issn.1000-436x.2015214.

摘要

选择最优接入网络是确保网络资源有效分配和提高网络整体性能的有效手段。提出一种基于跨层感知的接入选择方法CN_CLA，构建跨层感知框架模型以获取影响接入网性能的主要评估参数，采用模糊理论对可接入网络的性能进行综合评测，应用量子遗传算法对评判权值进行优化，最终实现接入网络的智能选择。实验结果表明，CN_CLA能够在无用户干涉情况下合理地选择接入网络，并在吞吐量、时延、会话完成率、分组丢失率等方面优于链路容量法、H_RSSI_S及AS_FTM接入选择算法。

Abstract

Accessing to the optimal network was an effective way of ensuring the efficiency of network resources utilization and improving network performance.An access point selection mechanism based on cross-layer awareness for cognitive networks(CN_CLA)was proposed.Firstly

a cross-layer cognitive framework was constructed for obtaining the primary evaluation parameters that influence the performance of network access.Secondly

the fuzzy theory was applied for evaluating the access network performance comprehensively

and the weights in each layer were optimized using the quantum genetic algorithm

and then the access point was selected intelligently.Simulation results show that the proposed method chooses reasonable access networks without intervention of users.Furthermore

it is superior to the traditional methods

including the link capacity scheme

H_RSSI_S and AS_FTM

in terms of throughput

delay

session completion rate

packet loss and other performance indicators.

关键词

Keywords

references

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The Network Simulator-ns-2 [EB/OL ] . http://www.isi.edu/nsnam/ns/ http://www.isi.edu/nsnam/ns/ , 2013 .

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