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teaching:projh402 [2020/10/01 11:34] ezimanyi [Implementing TSBS on MobilityDB] |
teaching:projh402 [2020/10/01 11:59] mahmsakr [Distributed Moving Object Database on Amazon AWS] |
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| A distributed database is an architecture in which multiple database instances on different machines are integrate in order to form a single database server. Both the data and the queries are then distributed over these database instances. This architecture is effective in deploying big databases on a cloud platform. | A distributed database is an architecture in which multiple database instances on different machines are integrate in order to form a single database server. Both the data and the queries are then distributed over these database instances. This architecture is effective in deploying big databases on a cloud platform. | ||
| - | MobilityDB is engineered as an extension of PostgreSQL. AWS supports PostgreSQL databases in Amazon RDS for PostgreSQL and in Amazon Aurora. The goal of this project is to integrate MobilityDB with these products. The key outcomes are a comprehensive assessment of which MOD API can/cannot be distributed, and an assessment of the performance gain. These outcomes should serve as a base for a thesis project to achieve effective integration. | + | MobilityDB is engineered as an extension of PostgreSQL. AWS supports PostgreSQL databases in [[https://aws.amazon.com/rds/postgresql/|Amazon RDS]] for PostgreSQL and in [[https://aws.amazon.com/rds/aurora/postgresql-features/|Amazon Aurora]]. The goal of this project is to integrate MobilityDB with these products. The key outcomes are a comprehensive assessment of which MOD API can/cannot be distributed, and an assessment of the performance gain. These outcomes should serve as a base for a thesis project to achieve effective integration. |
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| ===== Map-matching as a Service ===== | ===== Map-matching as a Service ===== | ||
| - | When GPS tracks typically contain errors, because the GPS receiver | + | GPS location tracks typically contain errors, as the GPS points will normally be some meters away from the true position. If we know that the movement happened on a street network, e.g., a bus or a car, then we can correct this back by putting the points on the street. Luckily there are Algorithms for this, called Map-Matching. There are also a handful of open source systems that do map matching. It remains however difficult to end users to use them, because they involve non-trivial installation and configuration effort. Preparing the base map, which will be used in the matching is also an issue to users. |
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| + | The goal of this project is to build an architecture for a Map-Matching service. The challanges are that the GPS data arrives in different formats, and that Map-Matching is a time consuming Algorithm. This architecture should thus allow different input formats, and should be able to automatically scale according to the request rate. Another key outcome of this project is to compare the existing Map-Matching implementations, and to discuss their suitability in real world problems. | ||
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| + | Links: | ||
| + | * [[https://github.com/bmwcarit/barefoot|Barefoot]] | ||
| + | * [[https://valhalla.readthedocs.io/en/latest/api/map-matching/api-reference/|Valhalla Map Matching API]] | ||
| + | * [[https://github.com/graphhopper/map-matching|GraphHopper]] | ||
| + | * [[https://github.com/cyang-kth/fmm|Fast Map Matching]] | ||