Task Bundle Delegation for Reducing the Flowtime

Autor: Ellie Beauprez, Anne Cécile Caron, Maxime Morge, Jean-Christophe Routier
Přispěvatelé: Systèmes Multi-Agents et Comportements (SMAC), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lille
Rok vydání: 2022
Předmět:
Zdroj: Lecture Notes in Computer Science ISBN: 9783031101601
Agents and Artificial Intelligence, 13th International Conference, ICAART 2021, Online streaming, February 4-6, 2021, Revised Selected Papers
Agents and Artificial Intelligence, 13th International Conference, ICAART 2021, Online streaming, February 4-6, 2021, Revised Selected Papers, 13251, Springer International Publishing, pp.22-45, 2022, Lecture Notes in Computer Science, 978-3-031-10160-1. ⟨10.1007/978-3-031-10161-8_2⟩
Popis: 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 rescheduling of tasks in multiple jobs which must be executed as soon as possible. It allows agents to determine locally the next tasks to process, to delegate, possibly to swap according to their knowledge, their own belief base and their peer modelling. The novelty lies in the ability of agents to identify opportunities and bottleneck agents, and afterwards to reassign some bundles of tasks thanks to concurrent bilateral negotiations. The strategy adopted by the agents allows to warrant a continuous improvement of the flowtime. Our experimentation reveals that our strategy reaches a flowtime which is better than the one reached by a DCOP resolution, close to the one reached by the classical heuristic approach, and significantly reduces the rescheduling time.
Databáze: OpenAIRE
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