内容中心网络中基于关键词的数据检索方案

Data Retrieval Scheme Based on Keywords in Content-centric Networks

内容中心网络提高了用户访问被发布信息的灵活性,然而现有的数据检索方案大多不支持关键词检索,影响了检索效率,导致了较高的检索开销。为此,提出了基于独立搜索和融合(ISM)和基于集成关键词搜索(IKS)的两种数据检索方案。它们支持发布方将内容标识符嵌入到用于描述内容的独立关键词中,用户们可根据关键词来提交他们的搜索/兴趣。中间内容路由器可检索与关键词相匹配的内容标识符。然后,用户设备上的客户端程序将检索出来的所有内容标识符汇集起来,获得他们想到的内容标识符最终列表。此后,用户便可检索这些与他们的搜索/兴趣相匹配的数据内容。最后的仿真实验也验证了本文方案的有效性。

Content-centric networks have been proposed to improve the flexibility of published information for users.However,most of the existing data retrieval schemes cannot support the keyword retrieval,which has the effect on the retrieval efficiency,resulting in the higher retrieval overhead.To solve this problem,two data retrieval schemes based on the independent search and merge(ISM) scheme and the Integrated Keyword Search(IKS) are proposed,which allow publishers to insert content identifiers together with independent keywords that are used to describe the content.Users can submit their searches/ interests based on keywords.Intermediate content routers retrieve content identifiers that match different keywords.The client programs in users' devices then do an intersection of all retrieved content identifiers to obtain a final list of content identifiers that match their interests.After that,users can retrieve these matched data contents.Finally,the effectiveness of the scheme is verified by the simulation experiments.