USING SHADOW PRICES FOR RESOURCE ALLOCATION IN A COMBINATORIAL GRID WITH PROXY-BIDDING AGENTS

Michael Schwind, Oleg Gujo

Abstract

Our paper presents an agent-based simulation environment for task scheduling in a distributed computer systems (grid). The scheduler enables the simultaneous allocation of resources like CPU time, communication bandwidth, volatile, and non-volatile memory while employing a combinatorial resource allocation mechanism. The resources are allocated by an iterative combinatorial auction with proxy-bidding agents that try to acquire their desired resource allocation profiles with respect to limited monetary budget endowments. In order to achieve an efficient bidding process, the auctioneer provides information on resource prices to the bidding agents. The calculation of explicit resource prices in a combinatorial auction is computationally demanding, especially if the the bid bundles exhibit complementarities or substitutionalities. We therefore propose a new approximate pricing mechanism using shadow prices from a linear programming formulation for this purpose. The efficiency of the shadow price-based allocation mechanism is tested in the context of a closed loop grid system in which the agents can use monetary units rewarded for the resources they provide to the system for the acquisition of complementary capacity. Two types of proxy-bidding agents are compared in terms of efficiency (received units of resources, time until bid acceptance) within this scenario: An aggressive bidding agent with strongly rising bids and a smooth bidding agent with slowly increasing bids.

References

  1. AuYoung, A., Chun, B. N., Snoeren, A. C., and Vahdat, A. (2004). Resource allocation in federated distributed computing infrastructures. In Proceedings of the 1st Workshop on Operating System and Architectural Support, San Francisco, USA.
  2. Bjørndal, M. and Jørnsten, K. (2001). An analysis of a combinatorial auction. Technical Report 2001-11, Department of Finance and Management Science, NorweBuyya, R., Stockinger, H., Giddy, J., and Abramson, D. (2001). Economic models for management of resources in peer-to-peer and grid computing. In Proceedings of the SPIE International Conference on Commercial Applications for High-Performance Computing, Denver, USA.
  3. Chun, B. N., Buonadonna, P., AuYoung, A., Ng, C., Parkes, D. C., Shneiderman, J., Snoeren, A. C., and Vahdat, A. (2004). Mirage: A microeconomic resource allocation system for sensornet testbeds. In Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors (EmNetS-II); Sidney, Australia.
  4. Fujishima, Y., Leyton-Brown, K., and Shoham, Y. (1999). Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches. In Proceedings of the 16th International Joint Conference on Artificial Intelligence 1999 (IJCAI-99), Stockholm, Sweden, pages 548 - 553.
  5. Kwasnica, A. M., Ledyard, J., Porter, D., and DeMartini, C. (2005). A new and improved design for multiobjective iterative auctions. Management Science, 51(3):419-434.
  6. Nisan, N. (2005). Bidding languages. In Steinberg, R., Shoham, Y., and Cramton, P., editors, Combinatorial Auctions. MIT-Press.
  7. Parkes, D. C. and Ungar, L. H. (2000). Iterative combinatorial auctions: Theory and practice. In Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-00), pages 74-81.
  8. Rassenti, J. S., Smith, V. L., and Bulfin, R. L. (1982). A combinatorial auction mechanism for airport time slot allocation. Bell Journ. of Economics, 13(2):402-417.
  9. Schwind, M., Stockheim, T., and Rothlauf, F. (2003). Optimization heuristics for the combinatorial auction problem. In Proceedings of the Congress on Evolutionary Computation CEC 2003, pages 1588-1595.
  10. Vries, S. D. and Vohra, R. (2001). Combinatorial auctions: A survey. INFORMS Journal on Computing, 15(3):284-309.
  11. Xia, M., Koehler, G. J., and Whinston, A. B. (2004). Pricing combinatorial auctions. European Journal of Operational Research, 154(1):251-270.
Download


Paper Citation


in Harvard Style

Schwind M. and Gujo O. (2006). USING SHADOW PRICES FOR RESOURCE ALLOCATION IN A COMBINATORIAL GRID WITH PROXY-BIDDING AGENTS . In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 4: ICEIS, ISBN 978-972-8865-44-3, pages 11-18. DOI: 10.5220/0002461500110018


in Bibtex Style

@conference{iceis06,
author={Michael Schwind and Oleg Gujo},
title={USING SHADOW PRICES FOR RESOURCE ALLOCATION IN A COMBINATORIAL GRID WITH PROXY-BIDDING AGENTS},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 4: ICEIS,},
year={2006},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002461500110018},
isbn={978-972-8865-44-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 4: ICEIS,
TI - USING SHADOW PRICES FOR RESOURCE ALLOCATION IN A COMBINATORIAL GRID WITH PROXY-BIDDING AGENTS
SN - 978-972-8865-44-3
AU - Schwind M.
AU - Gujo O.
PY - 2006
SP - 11
EP - 18
DO - 10.5220/0002461500110018