Cloud architecture for plant phenotyping research - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Concurrency and Computation: Practice and Experience Année : 2020

Cloud architecture for plant phenotyping research

Résumé

Digital phenotyping is an emergent science mainly based on imagery techniques. The tremendous amount of data generated needs important cloud computing for their processing. The coupling of recent advance of distributed databases and cloud computing offers new possibilities of big data management and data sharing for the scientific research. In this paper, we present a solution combining a lambda architecture built around Apache Druid and a hosting platform leaning on Apache Mesos. Lambda architecture has already proved its performance and robustness. However, the capacity of ingesting and requesting of the database is essential and can constitute a bottleneck for the architecture, in particular, for in terms of availability and response time of data. We focused our experimentation on the response time of different databases to choose the most adapted for our phenotyping architecture. Apache Druid has shown its ability to respond to typical queries of phenotyping applications in times generally inferior to the second.

Dates et versions

hal-02968818 , version 1 (16-10-2020)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Olivier Debauche, Sidi Ahmed Mahmoudi, Nicolas de Cock, Saïd Mahmoudi, Pierre Manneback, et al.. Cloud architecture for plant phenotyping research. Concurrency and Computation: Practice and Experience, 2020, 32 (17), ⟨10.1002/cpe.5661⟩. ⟨hal-02968818⟩
20 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More