Adjustable fuzzy inference for adaptive grid resource negotiation

Valeriia Haberland; Simon Miles; Michael Luck

doi:10.1007/978-4-431-55525-4_3

Adjustable fuzzy inference for adaptive grid resource negotiation

Valeriia Haberland^*, Simon Miles, Michael Luck

^*Corresponding author for this work

Department of Informatics

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Grids are dynamic, with the resource availability fluctuating over time, and at different rates at each instant. To obtain the resources for tasks execution, each client may negotiate with a resource allocator. If demand on resources is higher than their availability, resources can be exhausted. Therefore, a client needs to anticipate the resource availability in future, but its accurate estimation may not be possible because of the lack or inaccessibility of this information. However, through observing the information conveyed by the resource allocator in negotiation, a client can make estimates as to the speed and direction of the change in availability. In this paper, we describe an adaptive negotiation strategy that allows a client to adjust its tactics to the tendency in resource availability changes during negotiation through a fuzzy control mechanism. Results show that our negotiation strategy can allow a client to successfully obtain more resources.

Original language	English
Pages (from-to)	37-57
Number of pages	21
Journal	Studies in Computational Intelligence
Volume	596
DOIs	https://doi.org/10.1007/978-4-431-55525-4_3
Publication status	Published - 18 Mar 2015

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Adjustable fuzzy inference for adaptive grid resource negotiation

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