Cloud storage and search for mass spatio-temporal data through Proxmox VE and Elasticsearch cluster

Cloud computing is currently becoming a popular topic in recent years. The innovative application of cloud computing emerges endlessly. In this paper, the cloud computing platform is architected by virtualization tool Proxmox VE and the open source search engine Elasticsearch under the concept of virtualization. Based on this platform, we explore the feasibility and advancement for storing and searching spatio-temporal data. The time period index is imported as spatio-temporal data records both time and location. In this paper, the experiment is conducted using AIS data, which contains vessel motion characteristics. The result shows that the combination between virtualization and Elasticsearch can effectively store and index the spatio-temporal data with high reliability and efficiency. This paper is an innovation in the application of cloud virtualization. The method can widely and strongly support further research based on mass spatio-temporal data.