Spatiotemporal Data Access for Map Services based on R-star tree index and LSM tree

The paper proposed an approach to building a scalable service for spatiotemporal data storage to be used in applications that require searching for localized data and possibility of scaling up the storage resources. The motivation for proposing this approach was enabling the localized data being overlayed over the map, while transferring only required data and minimize the latency time. The paper describes the architecture combining the R-star tree index and Log Structured Merge (LSM) tree methods. The implementation framework based on Erlang OTP is proposed to provide a basis for sustainability and resiliency.