IoT Search Method for Entity Based on Advanced Density Clustering

The mass deployment of Internet of Things (IoT) entities brings great value to IoT applications and users. However, massive, heterogeneous and dynamic IoT entities make IoT search difficult. Application-oriented deployment of entities results in uneven distribution of entities, which brings challenges to IoT search. Considering the non-uniformity of IoT entity deployment, an IoT search method for entity based on advanced density clustering is proposed. This method first performs density clustering based on location, then performs k-means secondary division on large-scale entity clusters, and processes noise points, which greatly reduces the scope of entity search. Experimental results show that this method has less searching time and higher accuracy than other methods in the case of uneven distribution of entities.