一种基于聚类划分的IoT实体搜索方法

Searching method for entity in Internet of Things based on clustering

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。

The traditional Internet search engine aiming at searching static resources does not apply to search Internet of Things（IoT） entity because of its highly dynamic and enormous resources. How to obtain the target entity quickly in massive and dynamic networking resources has become a major challenge in the IoT search. To solve above problems, this paper proposes and implements an IoT＇ s entity search method based on clustering. By the analysis of a large number of IoT,it can be found that the kind of entity are far less than the quantity, and a strong similarity between entities. With the similarity between entities,the clustering of entities can narrow down the scope and save the time of real-time search.