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Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids

Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids

Behnaz Pourebrahimi, Koen Bertels
Copyright: © 2012 |Volume: 3 |Issue: 2 |Pages: 20
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781466612006|DOI: 10.4018/jertcs.2012040106
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MLA

Pourebrahimi, Behnaz, and Koen Bertels. "Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids." IJERTCS vol.3, no.2 2012: pp.111-130. http://doi.org/10.4018/jertcs.2012040106

APA

Pourebrahimi, B. & Bertels, K. (2012). Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 3(2), 111-130. http://doi.org/10.4018/jertcs.2012040106

Chicago

Pourebrahimi, Behnaz, and Koen Bertels. "Self-Adaptive Economic-Based Resource Allocation in Ad-Hoc Grids," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 3, no.2: 111-130. http://doi.org/10.4018/jertcs.2012040106

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Abstract

Resource allocation is the process of discovering and allocating resources to requested tasks in a way that satisfy both user jobs and resource administrators. In ad-hoc Grids, resource allocation is a challenging undertaking as tasks and resources are distributed, heterogeneous in nature, owned by different individuals or organizations and they may arise spontaneously at any time with various requirements and availabilities. In this paper, the authors address an economic-based framework for resource allocation in ad-hoc Grids to deal with the dynamic nature of such networks. Within the economic framework, self-interested nodes in ad-hoc Grids are considered as consumers (buyers) and producers (sellers) of resources. Consumers and producers of resources are autonomous agents that cooperate through a simple, single metric namely the price that summarizes the global state of a network in a number. Adaptation is achieved by individual nodes through adopting a bidding strategy that adjusts the price according to the current state of the network in order to optimize the local utility of the node.

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