Un système multi-agent adaptatif pour la réallocation de tâches au sein d'un job MapReduce

Autor: Jean-Christophe Routier, Quentin Baert, Maxime Morge, Kostas Stathis, Anne-Cécile Caron

Publikováno v: Journal of Parallel and Distributed Computing
Journal of Parallel and Distributed Computing, Elsevier, In press, 153, pp.75-88. ⟨10.1016/j.jpdc.2021.03.008⟩
Revue Ouverte d'Intelligence Artificielle
Revue Ouverte d'Intelligence Artificielle, 2022, pp.557-585
Journal of Parallel and Distributed Computing, 2021, 153, pp.75-88. ⟨10.1016/j.jpdc.2021.03.008⟩

We study the problem of task reallocation for load-balancing of MapReduce jobs in applications that process large datasets. In this context, we propose a novel strategy based on cooperative agents used to optimise the task scheduling in a single MapR

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::737d34be2764b88a93c7efb4aad0b773
https://hal.science/hal-03869505

Une stratégie de négociation multi-agents pour réduire la durée moyenne de réalisation

Autor: Ellie Beauprez, Anne-Cécile CARON, Maxime Morge, Jean-Christophe Routier

Publikováno v: Vingt-neuvièmes journées francophones sur les systèmes multi-agents (JFSMA)
Vingt-neuvièmes journées francophones sur les systèmes multi-agents (JFSMA), Jun 2021, Bordeaux, France. pp.31-40
HAL

International audience; In this paper, we study the problem of task reallocation for load-balancing in distributed data processing models that tackle vast amount of data. We propose a strategy based on cooperative agents used to optimize the reschedu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3e8ebba1d3c2b4ed64a312ebb4c17b15
https://hal.archives-ouvertes.fr/hal-03266018/document

A Location-Aware Strategy for Agents Negotiating Load-balancing

Autor: Maxime Morge, Kostas Stathis, Anne-Cécile Caron, Quentin Baert, Jean-Christophe Routier

Publikováno v: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)
2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Nov 2019, Portland, Oregon, United States. ⟨10.1109/ICTAI.2019.00098⟩
ICTAI

International audience; We study a novel location-aware strategy for distributed systems where cooperating agents perform the load-balancing. The strategy allows agents to identify opportunities within a current unbalanced allocation , which in turn

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::842bfbaa93e835144e560828d5040c3a
https://hal.science/hal-02344457

Fair multi-agent task allocation for large datasets analysis

Autor: Jean-Christophe Routier, Maxime Morge, Quentin Baert, Anne-Cécile Caron

Publikováno v: Knowledge and Information Systems (KAIS)
Knowledge and Information Systems (KAIS), 2018, 54 (3), pp.591-615. ⟨10.1007/s10115-017-1087-4⟩
Knowledge and Information Systems (KAIS), Springer, 2018, 54 (3), pp.591-615. ⟨10.1007/s10115-017-1087-4⟩

International audience; MapReduce is a design pattern for processing large datasets distributed on a cluster. Its performances are linked to the data structure and the runtime environment. Indeed, data skew can yield an unfair task allocation, but ev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fe2ceb0311a9015e031b707db295ba3
https://inria.hal.science/hal-01567428

Fair Multi-agent Task Allocation for Large Data Sets Analysis

Autor: Anne-Cécile Caron, Maxime Morge, Jean-Christophe Routier, Quentin Baert

Publikováno v: Lecture Note in Artificial Intelligence, Advances in Practical Applications of Scalable Multi-agent Systems, The PAAMS collection
PAAMS 2016-14th International Conference on Practical Applications of Agents and Multi-Agent Systems
PAAMS 2016-14th International Conference on Practical Applications of Agents and Multi-Agent Systems, Jun 2016, Sevilla, Spain. pp.12, ⟨10.1007/978-3-319-39324-7_3⟩
Advances in Practical Applications of Scalable Multi-agent Systems. The PAAMS Collection ISBN: 9783319393230
PAAMS

International audience; 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 prevent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87ca6dd586db2ffcbb78414416f973ae
https://inria.hal.science/hal-01327522/file/morge16paams.pdf