一种基于聚类划分的IoT实体搜索方法

发布时间：2018-04-16 08:32

本文选题：物联网 + 实体　；参考：《南京邮电大学学报(自然科学版)》2017年03期

【摘要】：传统的互联网搜索引擎是对静态资源进行搜索,而物联网中的实体具有高度动态性,且资源数量远远超过互联网中的数量,因此在面对海量的、动态的物联网实体时,如何快速锁定目标实体,成为物联网搜索面临的一大挑战。针对以上问题,提出并实现了一种基于聚类划分的IoT实体搜索方法。通过对大量的物联网实体的分析,发现实体的种类远少于实体的数量,实体之间的属性有很强的相似性。利用实体之间的相似性,对实体进行聚类的划分,可以缩小搜索范围,有效地提高实时搜索的效率。
[Abstract]:The traditional Internet search engine is to search static resources, but the entities in the Internet of things are highly dynamic, and the number of resources is far more than the number of the Internet of things, so in the face of massive, dynamic Internet of things entities,How to quickly lock down the target entity has become a major challenge in Internet of things search.Aiming at the above problems, a IoT entity search method based on clustering partition is proposed and implemented.Through the analysis of a large number of entities in the Internet of things, it is found that the types of entities are far less than the number of entities, and the attributes of entities have strong similarity.By using the similarity of entities, the clustering of entities can narrow the search scope and improve the efficiency of real-time search.
【作者单位】：南京邮电大学通信与信息工程学院;
【基金】：江苏省战略性新兴产业发展专项(2015ZS01)资助项目
【分类号】：TP391.3

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