1st International Conference on Game Theory for Networks

Research Article

Decentralized decision making process for document server networks

  • @INPROCEEDINGS{10.1109/GAMENETS.2009.5137379,
        author={Aurelie  Beynier and Abdel-Illah   Mouaddib},
        title={Decentralized decision making process for document server networks},
        proceedings={1st International Conference on Game Theory for Networks},
  • Aurelie Beynier
    Abdel-Illah Mouaddib
    Year: 2009
    Decentralized decision making process for document server networks
    DOI: 10.1109/GAMENETS.2009.5137379
Aurelie Beynier1,*, Abdel-Illah Mouaddib2,*
  • 1: LIP6, University Paris, Paris, France
  • 2: GREYC - University of Caen, Caen, France
*Contact email: aurelie.beynier@lip6.fr, mouaddib@info.unicaen.fr


A peer-to-peer server network system consists of a large number of autonomous servers logically connected in a peer-to-peer way where each server maintains a collection of documents. When a query of storing new documents is received by the system, a distributed search process determines the most relevant servers and redirects the documents to them for processing (compressing and storing at the right document base). In this paper, we model this distributed search process as a distributed sequential decision making problem using a set of interactive Markov Decision Processes (MDP), a specific stochastic game approach, which represent each server's decision making problem. The relevance of a server to a document is regarded as a reward considering the capacity of the storage and the goodness score of a server. We show that using a central MDP to derive an optimal policy of how to distribute documents among servers leads to high complexity and is inappropriate to the distributed nature of the application. We present then interactive MDPs approach transforming this problem into a decentralized decision making process.