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Negotiation Strategy of Divisible Tasks for Large Dataset Processing

  • Quentin Baert
  • Anne-Cécile Caron
  • Maxime Morge
  • Jean-Christophe Routier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10767)

Abstract

MapReduce is a design pattern for processing large datasets on a cluster. Its performances depend on some data skews and on the runtime environment. In order to tackle these problems, we propose an adaptive multiagent system. The agents interact during the data processing and the dynamic task allocation is the outcome of negotiations. These negotiations aim at improving the workload partition among the nodes within a cluster and so decrease the runtime of the whole process. Moreover, since the negotiations are iterative the system is responsive in case of node performance variations. In this paper, we show how, when a task is divisible, an agent may split it in order to negotiate its subtasks.

Keywords

Application of mas Automated negotiation Adaptation 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Quentin Baert
    • 1
  • Anne-Cécile Caron
    • 1
  • Maxime Morge
    • 1
  • Jean-Christophe Routier
    • 1
  1. 1.Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de LilleLilleFrance

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