Eliciting honest value information in a batch-queue environment

  • Authors:

  • Andrew Mutz;Rich Wolski;John Brevik

  • Affiliations:

  • Department of Computer Science, University of California Santa Barbara, CA 93106, U.S.A.;Department of Computer Science, University of California Santa Barbara, CA 93106, U.S.A.;California State University, Long Beach, 1250 Bellflower Blvd., 90840, U.S.A.

  • Venue:
  • GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
  • Year:
  • 2007

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Abstract

Markets and auctions have been proposed as mechanisms for efficiently and fairly allocating resources in a number of different computational settings. Economic approaches to resource allocation in batch-controlled systems, however, have proved difficult due to the fact that, unlike reservation systems, every resource allocation decision made by the scheduler affects the turnaround time of all jobs in the queue. Economists refer to this characteristic as an “externality”, where a transaction affects more than just the immediate resource consumer and producer. The problem is particularly acute for computational grid systems where organizations wish to engage in service-level agreements but are not at liberty to abandon completely the use of space-sharing and batch scheduling as the local control policies. Grid administrators desire the ability to make these agreements based on anticipated user demand, but eliciting truthful reportage of job importance and priority has proved difficult due to the externalities present when resources are batch controlled. In this paper we propose and evaluate the application of the Expected Externality Mechanism as an approach to solving this problem that is based on economic principles. In particular, this mechanism provides incentives for users to reveal information honestly about job importance and priority in an environment where batch-scheduler resource allocation decisions introduce “externalities” that affect all users. Our tests indicate that the mechanism meets its theoretical predictions in practice and can be implemented in a computationally tractable manner.