Dynamic Geographic Tiling With Spatial Index and Proxy Tile Retrieval
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Solution Overview
Problem
Existing systems face challenges in efficiently rendering and transmitting large geographic datasets over networks, particularly in scenarios requiring just-in-time retrieval or rendering, which are computationally expensive and lead to increased latency and bandwidth usage.
Innovation Solution
A dynamic data tiling system using an in-memory spatial index and persistent server resources to render map tiles on demand, employing HTTP proxies for connection reuse and parallel processing of source imagery, and utilizing Cloud Optimized GeoTIFF format for efficient I/O.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If geographic data is rendered and transmitted over networks in real-time, then data availability and responsiveness are improved, but network bandwidth consumption and latency increase
Solution Approach 1:
The geographic dataset is divided into discrete tiles that can be independently rendered and transmitted. This segmentation allows the system to transmit only the specific tiles needed for the current view rather than the entire dataset, reducing bandwidth consumption while maintaining real-time responsiveness.
Solution Approach 2:
Tiles are pre-rendered and stored in an optimized format (Cloud Optimized GeoTIFF) before being requested. This preliminary action prepares the data in advance for efficient transmission and rendering, reducing the time and bandwidth needed during actual data delivery.
2Adaptability or versatility
If map tiles are rendered on demand with flexible styling, then adaptability and customization are improved, but computational cost and rendering time increase
Solution Approach 1:
The system dynamically applies styling and rendering parameters based on the specific request rather than using fixed pre-rendered styles. This allows flexible customization while optimizing the rendering process by applying transformations only when needed and using efficient rendering techniques.
Solution Approach 2:
The system modifies rendering parameters such as color maps, scaling, and masking dynamically based on request specifications. By changing these parameters during the rendering process rather than creating multiple pre-rendered versions, the system maintains adaptability while reducing computational overhead.
3Measurement precision
If source imagery is processed and transformed in real-time, then data freshness and accuracy are improved, but processing complexity and computational resources increase
Solution Approach 1:
The system extracts only the specific tiles and data portions needed for the current request from the larger source imagery, rather than processing the entire dataset. This extraction approach maintains data accuracy for the requested area while significantly reducing processing complexity.
Solution Approach 2:
Instead of permanently modifying source imagery during processing, the system creates temporary copies and transformations of the required data portions. This allows accurate processing and transformation while preserving the original source data and reducing the complexity of managing permanent changes.
4Productivity
If multiple source tiles are retrieved and processed in parallel, then rendering speed and responsiveness are improved, but system resource consumption and complexity increase
Solution Approach 1:
The system divides the tile retrieval and processing task into independent parallel segments, each handling specific source tiles. This segmentation enables concurrent processing of multiple tiles without requiring complex inter-dependent operations, thus improving throughput while managing system complexity.
Solution Approach 2:
Multiple parallel processing streams are merged into a single coherent output by coordinating the results from different source tiles. This merging process consolidates the parallel operations into a unified rendered tile, maintaining high productivity while providing a manageable system interface.
Data Source
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AI summary
Dynamic data tiling is provided. In various embodiments, a request is received for a tile of geographic data from a requestor. The request specifies a region relative to a projection. The region is looked up in a spatial index to determine one or more source tiles. The spatial index corresponds to the projection and the one or more source tiles intersecting the region, The one or more source tiles are requested from a proxy, The proxy is configured to maintain one or more persistent connections to one or more datastores and to retrieve the one or more source tiles via the one or more persistent connections. The one or more source tiles is received from the proxy. The requested tile of geographic data is constructed from the one or more source tiles. The requested tile of geographic data is provided to the requestor.