Publication:
A Decentralized Auction Framework to Promote Efficient Resource Allocation in Open Computational Grids

Thumbnail Image

Date

2007

Published Version

Published Version

Journal Title

Journal ISSN

Volume Title

Publisher

Association for Computing Machinery
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Kang, Laura and David C. Parkes. 2007. A decentralized auction framework to promote efficient resource allocation in open computational grids. In Proceedings, Joint Workshop on The Economics of Networked Systems and Incentive-Based Computing: June 11, 2007, San Diego, CA, ed. D. Grosu, R. Mahajan, R. Sami. New York, N.Y.: Association for Computing Machinery.

Research Data

Abstract

Computational grids enable the sharing, aggregation, and selection of (geographically distributed) computational resources and can be used for solving large scale and data intensive computing applications. Computational grids are an appealing target application for market-based resource allocation especially given the attention in recent years to “virtual organizations ” and policy requirements. In this paper, we present a framework for truthful, decentralized, dynamic auctions in computational grids. Rather than a fullyspecified auction, we propose an open, extensible framework that is sufficient to promote simple, truthful bidding by endusers while supporting distributed and autonomous control by resource owners. Our auction framework incorporates resource prediction in enabling an expressive language for end-users, and highlights the role of infrastructure in enforcing rules that balance the goal of simplicity for end users with autonomy for resource owners. The technical analysis leverages simplifying assumptions of “uniform failure” and “threshold-reliability” beliefs.

Description

Keywords

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories