Abstract
In this paper, we study the problem of allocating concurrent jobs composed of situated tasks, underlying the distributed deployment of the MapReduce design pattern on a cluster. In order to implement our multi-agent strategy which aims at minimising the mean flowtime of jobs, we propose a modular agent architecture that allows the concurrency of negotiation and consumption. Our experiments show that our reallocation strategy, when executed continuously during the consumption process: (1) improves the flowtime; (2) does not penalise the consumption; (3) is robust against execution hazards.
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Notes
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The experiments are reproducible using the following instructions: https://gitlab.univ-lille.fr/maxime.morge/smastaplus/-/tree/master/doc/experiments.
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Beauprez, E., Caron, AC., Morge, M., Routier, JC. (2023). Adaptive Consumption by Continuous Negotiation. In: Mathieu, P., Dignum, F., Novais, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Cognitive Mimetics. The PAAMS Collection. PAAMS 2023. Lecture Notes in Computer Science(), vol 13955. Springer, Cham. https://doi.org/10.1007/978-3-031-37616-0_3
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