Project Details
Description
As the quantity of data that we can collect is increasing exponentially, it is becoming increasingly useful to make powerful computers and efficient algorithms to process and use this data. In particular, most databases are not static: they are constantly updated with new information. Consider an algorithm meant to give a solution to a particular problem: that solution may be the shortest path between some places or an optimal schedule. We want to be able to update our solution fast, and sometimes we want to update it locally: given a delayed train, we want to update the transportation schedule with as few changes as possible.
We focus on networks, that we also refer to as graphs: the database consists of objects and connections between these objects. The aim here is to update the solution to a specific problem when such a connection is created or removed. We want to minimize either the number of objects affected or the time to perform the update.
Once we have an algorithm to solve a graph problem, it may benefit any kind of network. Examples of applications include identifying communities in social networks, finding shortest paths in road networks, optimizing resource allocation in optical networks, and managing bandwidth in various communication networks.
We focus on networks, that we also refer to as graphs: the database consists of objects and connections between these objects. The aim here is to update the solution to a specific problem when such a connection is created or removed. We want to minimize either the number of objects affected or the time to perform the update.
Once we have an algorithm to solve a graph problem, it may benefit any kind of network. Examples of applications include identifying communities in social networks, finding shortest paths in road networks, optimizing resource allocation in optical networks, and managing bandwidth in various communication networks.
Status | Active |
---|---|
Effective start/end date | 01/09/2023 → 31/08/2026 |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.