Ki Yong Lee  Minji Seo  Ryong Lee  Minwoo Park  Sang-Hwan Lee

10.5626/JOK.2019.46.1.86

spatio-temporal join Spatio-temporal index thing data

A spatio-temporal join is an operation that connects multiple sets of data with the same spatial and temporal values. Especially with the increasing spread of IoT (Internet of Things), the need for spatio-temporal joins is also increasing in order to retrieve data generated at the same time and location among the data generated by different things in the past. In this study, we propose an efficient method for processing spatio-temporal joins on IoT data. The proposed method divides the 3D spatio-temporal space into small subspaces and maintains the identifiers of things whose data are present in each subspace. When a spatio-temporal join between things is requested, the proposed method identifies the spaces in which the things’ data are close to each other. Then, it retrieves data contained in the identified spaces and performs the join only between them. Therefore, because only that data with the possibility of being joined are accessed, the execution cost is greatly reduced. The experimental results on a real IoT dataset show that the proposed method significantly reduces the execution time compared to the existing spatio-temporal methods.