By Topic

Balancing risk and reward in a market-based task service

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
D. E. Irwin ; Dept. of Comput. Sci., Duke Univ., Durham, NC, USA ; L. E. Grit ; J. S. Chase

We investigate the question of scheduling tasks according to a user-centric value metric-called yield or utility. User value is an attractive basis for allocating shared computing resources, and is fundamental to economic approaches to resource management in linked clusters or grids. Even so, commonly used batch schedulers do not yet support value-based scheduling, and there has been little study of its use in a market-based grid setting. In part this is because scheduling to maximize time-varying value is a difficult problem where even simple formulations are intractable. We present improved heuristics for value-based task scheduling using a simple but rich formulation of value, in which a task's yield decays linearly with its waiting time. We also show the role of value-based scheduling heuristics in a framework for market-based bidding and admission control, in which clients negotiate for task services from multiple grid sites. Our approach follows an investment metaphor: the heuristics balance the risk of future costs against the potential for gains in accepting and scheduling tasks. In particular, we show the importance of opportunity cost, and the impact of risk due to uncertainty in the future job mix.

Published in:

High performance Distributed Computing, 2004. Proceedings. 13th IEEE International Symposium on

Date of Conference:

4-6 June 2004