On Properties of Game Theoretical Approaches to Balance Load Distribution in Mobile Grids

  • Karin Anna Hummel
  • Harald Meyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5343)


Mobile devices can be integrated into grids to access grid resources but also to provide resources, such as CPU cycles or memory, building mobile grids. To exploit the potential of mobile grids, we propose an opportunistic job scheduling approach to harness cycles among mobile devices. Mobile nodes decide autonomously and locally which job to take by matching the job’s requirements against their capabilities and coordinate with one another by means of shared job queues. A prototype implementation has been presented in previous work. In this work, we introduce selfish nodes which are expected to occur among mobile devices with limited energy sources. To react to selfishness, we introduce three strategies of game theory, that are, Tit For Tat (TFT), generous TFT, and Go-By Majority (GBM), to our approach and investigate the emerging behavior of the system by means of simulation. First results show, that the TFT and GBM implementations converge fast to fully selfish systems, while generous TFT exhibits self-healing characteristics.


Self-organization Mobile Grids Game Theory 


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  1. 1.
    Satyanarayanan, M.: Fundamental Challenges in Mobile Computing. In: 15th Annual ACM Symposium on Principles of Distributed Computing, pp. 1–7 (1996)Google Scholar
  2. 2.
    Hummel, K.A., Jelleschitz, G.: A Robust Decentralized Job Scheduling Approach for Mobile Peers in Ad-hoc Grids. In: 7th CCGRID, pp. 461–470 (2007)Google Scholar
  3. 3.
    Zong, Z., Nijm, M., Manzanares, A., Qin, X.: Energy Efficient Scheduling for Parallel Applications on Mobile Clusters. Cluster Computing 11(1), 91–113 (2008)Google Scholar
  4. 4.
    Chakravarti, A.J., Baumgartner, G., Lauria, M.: The Organic Grid: Self-Organizing Computation on a Peer-to-Peer Network. In: 1st ICAC, pp. 96–103 (2004)Google Scholar
  5. 5.
    Batheja, J., Parashar, M.: A Framework for Opportunistic Cluster Computing Using JavaSpaces. In: 9th HPCN, pp. 647–656 (2001)Google Scholar
  6. 6.
    Cao, J.: Self-Organizing Agents for Grid Load Balancing. In: 5th IEEE/ACM Int. Workshop on Grid Computing, pp. 388–395 (2004)Google Scholar
  7. 7.
    Feldman, M., Chuang, J.: Overcoming Free-riding Behavior in Peer-to-peer Systems. ACM SIGecom Exchanges 5(4), 41–50 (2005)CrossRefGoogle Scholar
  8. 8.
    Axelrod, R.: The Evolution Of Cooperation. Basic Books (1985)Google Scholar
  9. 9.
    Nowak, M.A., Sigmund, K.: Tit for Tat in Heterogeneous Populations. Nature 355, 250–253 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Karin Anna Hummel
    • 1
  • Harald Meyer
    • 1
  1. 1.Department of Distributed and Multimedia SystemsUniversity of ViennaAustria

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