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作 者:郭瑞彬 GUO Ruibin(School of Electronic Information Engineering, Beijng Jiaotong University, Beijing 100044, China)
机构地区:[1]北京交通大学电子信息工程学院
出 处:《铁路计算机应用》2019年第5期15-21,共7页Railway Computer Application
基 金:国家重点基础研究发展计划(973计划)(2013CB329100)
摘 要:命名数据网络在物联网应用方面具有天然优势。但其设计之初的一些特点对其在物联网方面的应用具有阻碍。因此,学术界提出在网络层面和应用层面添加一个中间件,增加命名数据网络(NDN)对多维数据的支持能力。基于这一思想,以车联网为场景,验证中间件及其配套算法的有效性,并对相关机制的缺陷提出改进措施。通过实验仿真,分析名字翻译优化算法和改进机制的性能。实验结果表明,优化算法和改进机制有效提高了NDN应对多维数据请求的性能表现。Named data networks have natural advantages in the application of the Internet of Things. However, some of its characteristics at the beginning of its design hindered its application in the Internet of Things. Therefore, academia proposes to add a middleware at the network level and application level to increase the support ability of named data network (NDN) for multi-dimensional data. Based on this idea, this paper took Internet of vehicles as scenario to validate the validity of middleware and its supporting algorithms, and propose improvement measures for the defects of relevant mechanisms. Through experimental simulation, the performance of the name translation optimization algorithm and the improved mechanism are analyzed. The experimental results show that the optimization algorithm and improvement mechanism effectively improved the performance of NDN in dealing with multi-dimensional data requests.
分 类 号:U29[交通运输工程—交通运输规划与管理] TP393[交通运输工程—道路与铁道工程]
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