Method for Computational Grids Resources Allocate Based on Auction and Utility Analyses

  • Dong-E Chen
  • Yang Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4494)


Considering dynamic, heterogeneous and autonomous characteristics of computing resources in the computational grid environment and the advantages of economics mechanism applied to solve the problem of resource management, a sealed-bid auction method for resource allocation on computational grids is presented. Firstly, a grid service markets framework for resource allocation in the computational grid environment is described. Secondly, a sealed-bid auction mechanism is presented, where centered on users, and driven by user’s needs. Thirdly, Bayes equilibrium point and utility, strategy and efficiency in the Bayes equilibrium state are discussed. Finally, utility function-based resources allocation algorithm is presented.


grid service markets resources allocation sealed-bid auction Bayes equilibrium utility 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Waldspurger, C., Hogg, T., Huberman, B., Kephart, J., Stornetta, W.: Spawn: A distributed computational economy. IEEE Trans. Softw. Eng. 18(2), 103–117 (1992)CrossRefGoogle Scholar
  2. 2.
    Nisan, N., London, S., Regev, O., Camiel, N.: Globally distributed computation over the internet: The POPCORN project, presented at the Int. Conf. Distributed Computing Systems (ICDCS 1998), Amsterdam, The Netherlands, pp. 26–29 (May 1998)Google Scholar
  3. 3.
    Lalis, S., Karipidis, A.: An open market-based framework for distributed computing over the internet. The 1st IEEE/ACM Int. Workshop Grid Computing (GRID 2000) Bangalore, India (December 17, 2000) (presented)Google Scholar
  4. 4.
    Moore, R., Baru, C., Marciano, R., Rajasekar, A., Wan, M.: Nimrod-G: An architecture for a resource management and scheduling system in a global computational grid. In: The 4th Int. Conf. High Performance Computing in Asia-Pacific Region (HPC Asia 2000), Beijing, China (May 2000) (presented)Google Scholar
  5. 5.
    Buyya, R., Murshed, M., Abramson, D.: A Deadline and Budget Constrained Cost-Time Optimization Algorithm for Scheduling Task Farming Applications on Global Grids. In: The 2002 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, Nevada, USA (June 2002)Google Scholar
  6. 6.
    Wolski, R., Brevik, J., Plank, J., et al.: Grid Resource Allocation and Control Using Computational Economies. In: Berman F, Fox G, Hey T. (eds.) Grid Computing: Making the Global Infrastructure a Reality, pp. 747–772 (2003)Google Scholar
  7. 7.
    Buyya, R.: Economic-Based Distributed Resource Management and Scheduling for Grid Computing. Ph.D.Dissertation (2002)Google Scholar
  8. 8.
    Buyya, R., Abramson, D., Venugopal, S.: The Grid Economy. In: Proceedings of the Ieee, vol. 93(3) (March 2005)Google Scholar
  9. 9.
    Wolski, R., Plank, J.S., Brevik, J., et al.: Analyzing market-based resource allocation strategies for the computational Grid. International Journal of High. Performance Computing Applications 15(3), 258–281 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Dong-E Chen
    • 1
    • 2
  • Yang Yang
    • 1
  1. 1.Information Engineering School, University of Science and Technology Beijing, Beijing, 100083China
  2. 2.Computer Center, HeBei University of Economics and business, Shijiazhuang, 050091China

Personalised recommendations