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MA Computer Science Projects (PROJ-H-402)

Course objective

The course PROJ-H-402 is managed by Dr. Mauro Birattari. Please refer to the course description page http://iridia.ulb.ac.be/proj-h-402/index.php/Main_Page for the rules concerning the project. What follows is a list of project proposals supervised by academic members of CoDE.

Projects in Mobility Databases

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.

Towards filling this gap, our group is building the 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.

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 https://www.osgeo.org/projects/mobilitydb/, which certifies high technical quality.

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 architecture of extensible databases, in this case PostgreSQL.
  • Writing open source software.

==== Visualization Moving Objects on the Web

Implementing TSBS on MobilityDB

which includes devising a spatio-temporal bucket function equivalent to time_bucket from TimescaleDB.

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.

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.

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.

MobilityDB is engineered as an extension of PostgreSQL. MS Azure supports distributed PostgreSQL databases using 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

Geospatial Trajectory Data Cleaning

Geospatial Trajectory Similarity Measure

Spatiotemporal k-Nearest Neighbour (kNN) Queries

 
teaching/projh402.1601542487.txt.gz · Last modified: 2020/10/01 10:54 by mahmsakr