Distributed Vector Tile Generation Using Directed Acyclic Task Graphs
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Solution Overview
Problem
The generation of vector tiles for large map areas, such as world maps or continents, requires a high computational cost and time, often resulting in outdated data by the time the tiles are generated.
Innovation Solution
A distributed computing system that includes multiple processing units and a memory unit configured to store map data, task database, and generated vector tiles. This system uses a directed acyclic task graph to schedule the generation of vector tiles by dividing the map area into subareas, obtaining map data, rendering preliminary and sub-tiles, and merging them to create the final vector tile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If vector tiles for large map areas are generated using traditional methods, then complete map coverage is achieved, but the generation time becomes excessively long (several weeks for world map)
Solution Approach 1:
The patent divides the large map area into multiple smaller squared map subareas, each processed independently by different processing units in a distributed computing system. This segmentation allows parallel processing of map regions, reducing the overall generation time from weeks to a manageable duration while maintaining complete coverage of the entire map area.
Solution Approach 2:
The patent introduces a new dimension of parallel processing by utilizing multiple processing units working simultaneously on different map subareas. This transitions from sequential single-threaded generation to concurrent multi-threaded generation across multiple computational nodes, dramatically accelerating the generation process.
2Area of stationary object
If vector tiles for large map areas are generated using traditional methods, then complete map coverage is achieved, but the computational cost becomes excessively high
Solution Approach 1:
By segmenting the map generation task across multiple processing units, the computational workload is distributed rather than concentrated on a single system. This allows for more efficient resource utilization, better load balancing, and reduced peak computational costs while achieving complete map coverage.
Solution Approach 2:
The patent combines the computational resources of multiple processing units to work on different portions of the map simultaneously. This merging of computational power across a distributed system achieves the same coverage more efficiently than a single system working alone, reducing overall computational cost.
3Quantity of substance
If vector tiles are generated for large map areas, then comprehensive map data is available, but the data becomes outdated by the time generation is complete
Solution Approach 1:
The parallel processing of segmented map subareas enables the generation of comprehensive map data much faster, reducing the time window during which data might become outdated. Each subarea is processed concurrently, so the complete map is generated in a fraction of the time required for sequential processing, preserving data freshness.
Solution Approach 2:
The distributed computing system maintains continuous processing across multiple units without idle time, ensuring that map data generation proceeds at maximum efficiency throughout. This continuous parallel action completes the comprehensive map data generation before significant time passes, keeping the data current.
Data Source
AI summary
Aspects concern a distributed computing system for generating vector tiles of a selected map area including a memory unit configured to store map data and a task database, the map data including a representation of the selected map area with a first resolution and a first detail level and with a second resolution higher than the first resolution and a second detail level; two or more processing units, each of the two or more processing units configured to select a task included in the task database, to execute the selected task, and to provide data generated by the selected task to the memory unit for storage; wherein one of the two or more processing units is further configured to schedule the generation of vector tiles by determining tasks using a specific predefined directed acyclic task graph and to provide the determined task to the task database.