基于深度布隆过滤器的NDN网络三级名字查找方法  

A Three-level Name Lookup Method Based on Deep Bloom Filter for Named Data Networking

作　　者：吴庆涛 师君如 张明川 王倩玉 朱军龙 张宏科[2] WU Qingtao;SHI Junru;ZHANG Mingchuan;WANG Qianyu;ZHU Junlong;ZHANG Hongke(School of Information Engineering,Henan University of Science and Technology,Luoyang 471023,China;National Engineering Laboratory for Next Generation Internet Interconnection Devices,Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]河南科技大学信息工程学院,洛阳471023 [2]北京交通大学下一代互联网互联设备国家工程实验室,北京100044

出　　处：《电子与信息学报》2021年第12期3597-3604,共8页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61871430,61976243);中原科技创新领军人才(214200510012);河南省教育厅基础研究专项(19zx010);河南省教育厅重点科研项目(20A520011)。

摘　　要：为提高命名数据网络(Name Data Networking,NDN)路由过程中内容名字查找的效率,该文提出一种基于深度布隆过滤器的3级名字查找方法。该方法使用长短记忆神经网络(Long Short Term Memory,LSTM)与标准布隆过滤器相结合的方法优化名字查找过程;采用3级结构优化内容名字在内容存储器(Content Store,CS)、待定请求表(Pending Interest Table,PIT)中的精确查找过程,提高查找精度并降低内存消耗。从理论上分析了3级名字查找方法的假阳性率,并通过实验验证了该方法能够有效节省内存、降低查找过程的假阳性。A three-level name lookup method based on deep Bloom filter is proposed to improve the searching efficiency of content name in the routing progress of the Named Data Networking(NDN).Firstly,in this method,the Long Short Term Memory(LSTM)is combined with standard Bloom filter to optimize the name searching progress.Secondly,a three-level structure is adopted to optimize the accurate content name lookup progresses in the Content Store(CS)and the Pending Interest Table(PIT)to promote lookup accuracy and reduce memory consumption.Finally,the error rate generated by content name searching method based on deep Bloom filter structure is analyzed in theory,and the experiment results prove that the proposed the threelevel lookup structure can compress memory and decrease the error effectively.

关 键 词：命名数据网络 内容名字查找 深度布隆过滤器 内存消耗 

分 类 号：TN919.2[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]