Description
Date depot: 13 octobre 2020
Titre: Quality-aware query processing for big datasets
Directeur de thèse:
Themis PALPANAS (LIPADE)
Encadrant :
Soror SAHRI (LIPADE)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
This project aims to propose a framework dealing with quality-aware query processing for large scale datasets. The main challenge is to make trade-offs between the query cost and the answer quality, in the context of Big Data. Big Data require storage and analysis capabilities that can only be addressed by distributed computing systems. The challenge related to big data is then to adapt the quality-driven query processing to a distributed environment, namely: defining distributed query execution plans while dealing with the quality assessment for distributed and scalable data. We will then ensure to adapt the query costs, that involves reducing the communication cost of query processing in distributed environments, to users’ quality requirements.
Doctorant.e: Dong Sijie