Edge GIS platform, which is deployed near the client or the data source side, is to achieve near-by service publishing and real-time analysis and calculation, reduce response latency and bandwidth consumption and reduce the pressure of cloud GIS center. It can effectively improve the terminal access experience of cloud GIS, and provide the ability of intelligent content distribution and efficient edge analysis and calculation, and help to build a more efficient and intelligent cloud-edge-terminal GIS application system.
◇ Proxy standard services: SuperMap REST service and OGC service.
◇ Proxy internet services: Google map service, etc.
◇ Efficient service acceleration mechanism to greatly improves service throughput and reliability.
◇ Map aggregation: aggregates multiple maps from different sources into one map.
◇ Data aggregation: aggregates multiple data from different sources into one data source.
◇ Efficient and reliable distribution technology: distributes GIS data of cloud GIS center to edge nodes quickly and securely.
◇ Flexible and convenient distribution methods: automatically distributes by region and level without any manual operates, and supports append distribution mode.
◇ Rich distribution data types: local files, vector and raster tiles, WebP tiles, 3D terrain and model tiles.
◇ Powerful service distribution capabilities: SuperMap REST map service, SuperMap REST 3D services, vector tiles services, OGC standard services, third-party services.
◇ Edge dynamic mapping: based on local data, PostGIS data and HBase data rendering.
◇ Edge data query: based on local data, PostGIS data and HBase data space query and attribute query.
◇ Edge processing and analysis: measurement, coordinate transformation, geospatial relations, geospatial computing.
◇ Creates iEdge cluster with multi-node based on K3s technology, which improves the efficiency of proxy service.
◇ All nodes share the same service configuration and backup for each other, which improves the stability of proxy service.
◇ Provides automatic scaling mechanism based on CPU threshold, which considers both performance and resource utilization.