Résumé:
In recent years, the development of technology and the increase in heterogeneous data received by IOT sensors have caused the traditional processing systems to be incompetent to process and store this large data. And this issue has opened the door for researchers to design new systems and models.
There are several indexing structures but the best known ones that have proven their effectiveness are : tree indexing where the BCCF tree is located, BCCF* and graphical indexing where the Voronoi diagram is located. Despite the advantages of these structures, there remains the problem of search process performance and index quality. And as long as the combination makes the strength this study aims to combine the two structures to make the system capable of processing and storing the massive data of the IOT. Pour cela, nous proposons l’utilisation de graphe de Voronoi sur un échantillant comme prétraitement et complété l’indexation par l’utilisation du principe de l’arbre BCCF, to minimise the cost of construction and improve the quality of discovery and research processes and most important for a global view of massive IOT data.
