Affiliation:
1. Delft University of Technology, The Netherlands
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.
Reference22 articles.
1. Assuncao, M. D., & Buyya, R. (2006). An evaluation of communication demand of auction protocols in grid environments. In Proceedings of the 3rd International Workshop on Grid Economics & Business.
2. AuYoung, A., Buonadonna, P., Chun, B. N., Ng, C., Parkes, D. C., & Shneidman, J. …Vahdat, A. (2009). Two auction-based resource allocation environments: Design and experience. In R. Buyya & K. Bubendorfer (Eds.), Market oriented grid and utility computing (Ch. 23). New York, NY: John Wiley & Sons.
3. Bagnall, A. J., & Toft, I. E. (2004). Zero intelligence plus and Gjerstad-Dickhaut agents for sealed bid auctions. In Proceedings of the Workshop on Trading Agent Design and Analysis (pp. 59-64).
4. Buyya, R., Abramson, D., & Giddy, J. (2000). Nimrod/g: an architecture for a resource management and scheduling system in a global computational grid. In Proceedings of the Fourth International Conference on High Performance Computing in Asia-Pacific Region (pp. 283-289).
5. Economic models for resource management and scheduling in Grid computing