Elasticsearch for big geotemporal data

• Datum: 2025
• Hauptverfasser: Zhyrenkov, O.S., Doroshenko, A.Yu.
• Format: Artikel
• Sprache: English
• Veröffentlicht: PROBLEMS IN PROGRAMMING 2025
• Schlagworte: Elasticsearch; geospatial data; distributed architecture; H3 indexing; BKD tree; R-tree; performance optimization; geotemporal data; trajectories; UDC 004.65; 004.652; 004.657; 004.78
• Online Zugang: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/764
• Назва журналу: Problems in programming

An exponential growth in the volume and complexity of geospatial data, driven by advances in GPS technology, mobile devices, and Internet of Things (IoT) sensors, has created an urgent need for scalable and efficient solutions for storage and query processing [1]. This paper proposes improvements an...