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Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services
Number of Authors: 2
2008 (English)Conference paper (Refereed)
Abstract [en]

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms.

Place, publisher, year, edition, pages
2008, 1. , 18 p.
Keyword [en]
Automated Bidding - Reinforcement learning - Service Allocation - Grid Computing
National Category
Computer and Information Science
URN: urn:nbn:se:ri:diva-22951DOI: 10.1007/978-3-540-88871-0_52OAI: diva2:1042516
Grid computing, high-performAnce and Distributed Applications (GADA'08)
Available from: 2016-10-31 Created: 2016-10-31

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