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| ===== Projects in Mobility Databases ===== | ===== Projects in Mobility Databases ===== | ||
| - | Moving object databases (MOD) are database systems that can store and manage moving object data. A moving object is a value that changes over time. It can be spatial (e.g., a car driving on the road network), or non-spatial (e.g., the temperature in Brussels). Using a variety of sensors, the changing values of moving objects can be recorded in digital formats. A MOD, then, helps storing and querying such data. A couple of prototypes have also been proposed, some of which are still active in terms of new releases. Yet, a mainstream system is by far still missing. Existing prototypes are merely research. By mainstream we mean that the development builds on widely accepted tools, that are actively being maintained and developed. A mainstream system would exploit the functionality of these tools, and would maximize the reuse of their ecosystems. As a result, it becomes more closer to end users, and easily adopted in the industry. | + | Mobility databases (MOD) are database systems that can store and manage moving object geospatial trajectory data. A moving object is an object that changes its location over time (e.g., a car driving on the road network). Using a variety of sensors, the location tracks of moving objects can be recorded in digital formats. A MOD, then, helps storing and querying such data. A couple of prototype systems have been proposed by research groups. Yet, a mainstream system is by far still missing. By mainstream we mean that the development builds on widely accepted tools, that are actively being maintained and developed. A mainstream system would exploit the functionality of these tools, and would maximize the reuse of their ecosystems. As a result, it becomes more closer to end users, and easily adopted in the industry. |
| - | In our group, we are building MobilityDB, a mainstream MOD. It builds on PostGIS, which is a spatial database extension of PostgreSQL. MobilityDB extends the type system of PostgreSQL and PostGIS with ADTs for representing moving object data. It defines, for instance, the tfloat for representing a time dependant float, and the tgeompoint for representing a time dependant geometry point. MobilityDB types are well integrated into the platform, to achieve maximal reusability, hence a mainstream development. For instance, the tfloat builds on the PostgreSQL double precision type, and the tgeompoint build on the PostGIS geometry(point) type. Similarly MobilityDB builds on existing operations, indexing, and optimization framework. | + | Towards filling this gap, our group is building the [[MobilityDB|https://github.com/MobilityDB/MobilityDB]] system . It builds on PostGIS, which is a spatial database extension of PostgreSQL. MobilityDB extends the type system of PostgreSQL and PostGIS with ADTs for representing moving object data. It defines, for instance, the tgeompoint type for representing a time dependant geometry point. MobilityDB types are well integrated into the platform, to achieve maximal reusability, hence a mainstream development. For instance, the tgeompoint type builds on the PostGIS geometry(point) type. Similarly MobilityDB builds on existing operations, indexing, and optimization framework. |
| - | This is all made accessible via the SQL query interface. Currently MobilityDB is quite rich in terms of types and functions. It can answer sophisticated queries in SQL. The first beta version has been released as open source April 2019 (https://github.com/ULB-CoDE-WIT/MobilityDB). | + | MobilityDB supports SQL as query interface. Currently it is quite rich in terms of types and functions. It is incubated as community project in OSGeo [[OSGeo|https://www.osgeo.org/projects/mobilitydb/]], which certifies high technical quality. |
| - | The following thesis ideas contribute to different parts of MobilityDB. They all constitute innovative development, mixing both research and development. They hence will help developing the student skills in: | + | The following project ideas contribute to different parts of MobilityDB. They all constitute innovative development, mixing both research and development. They hence will help developing the student skills in: |
| - | Understanding the theory and the implementation of moving object databases. | + | * Understanding the theory and the implementation of moving object databases. |
| - | Understanding the architecture of extensible databases, in this case PostgreSQL. | + | * Understanding the architecture of extensible databases, in this case PostgreSQL. |
| - | Writing open source software. | + | * Writing open source software. |
| + | ==== Visualization Moving Objects on the Web ==== | ||
| - | ===== Project proposals ===== | + | ==== Implementing TSBS on MobilityDB ==== |
| + | which includes devising a spatio-temporal bucket function equivalent to time_bucket from TimescaleDB. | ||
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| + | ==== Distributed Moving Object Database on Amazon AWS ==== | ||
| + | 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. | ||
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| + | 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. | ||
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| + | ==== Distributed Moving Object Database on MS Azure ==== | ||
| + | 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. | ||
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| + | MobilityDB is engineered as an extension of PostgreSQL. MS Azure supports distributed PostgreSQL databases using [[Citus|https://www.citusdata.com/]]. We have made successful tests for integrating MobilityDB and Citus on a local cluster. The goal of this project is to repeat this work on MS Azureintegrate 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. | ||
| + | ==== Map-matching as a Service ==== | ||
| + | When GPS tracks typically contain errors, because the GPS receiver | ||
| + | |||
| + | ==== Geospatial Trajectory Data Cleaning ==== | ||
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| + | ==== Geospatial Trajectory Similarity Measure ==== | ||
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| + | ==== Spatiotemporal k-Nearest Neighbour (kNN) Queries ==== | ||