Fair Multi-agent Task Allocation for Large Data Sets Analysis

Abstract : Many companies are using MapReduce applications to process very large amounts of data. Static optimization of such applications is complex because they are based on user-defined operations, called map and reduce, which prevents some algebraic optimization. In order to optimize the task allocation, several systems collect data from previous runs and predict the performance doing job profiling. However they are not effective during the learning phase, or when a new type of job or data set appears. In this paper, we present an adaptive multi-agent system for large data sets analysis with MapReduce. We do not preprocess data and we adopt a dynamic approach, where the reducer agents interact during the job. In order to decrease the workload of the most loaded reducer-and so the execution time-we propose a task reallocation based on negotiation.
Type de document :
Communication dans un congrès
Yves Demazeau; Takayuki Ito; Javier Bajo; Maria José Escalona. PAAMS 2016 - 14th International Conference on Practical Applications of Agents and Multi-Agent Systems, Jun 2016, Sevilla, Spain. Springer, Lecture Note in Artificial Intelligence, Advances in Practical Applications of Scalable Multi-agent Systems, The PAAMS collection, pp.12, 2016, Proc. of 14th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), Sevilla, Spain. 〈http://paams.net/〉. 〈10.1007/978-3-319-39324-7_3〉
Liste complète des métadonnées

Littérature citée [9 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01327522
Contributeur : Cristal Equipe Smac <>
Soumis le : lundi 6 juin 2016 - 18:35:21
Dernière modification le : mardi 24 avril 2018 - 13:53:43

Fichier

morge16paams.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Quentin Baert, Anne-Cécile Caron, Maxime Morge, Jean-Christophe Routier. Fair Multi-agent Task Allocation for Large Data Sets Analysis. Yves Demazeau; Takayuki Ito; Javier Bajo; Maria José Escalona. PAAMS 2016 - 14th International Conference on Practical Applications of Agents and Multi-Agent Systems, Jun 2016, Sevilla, Spain. Springer, Lecture Note in Artificial Intelligence, Advances in Practical Applications of Scalable Multi-agent Systems, The PAAMS collection, pp.12, 2016, Proc. of 14th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS), Sevilla, Spain. 〈http://paams.net/〉. 〈10.1007/978-3-319-39324-7_3〉. 〈hal-01327522〉

Partager

Métriques

Consultations de la notice

216

Téléchargements de fichiers

108