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Negotiation strategies considering market, time and behavior functions for resource allocation in computational grid

Adabi, S ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1007/s11227-012-0808-4
  3. Publisher: 2013
  4. Abstract:
  5. Providing an efficient resource allocation mechanism is a challenge to computational grid due to large-scale resource sharing and the fact that Grid Resource Owners (GROs) and Grid Resource Consumers (GRCs) may have different goals, policies, and preferences. In a real world market, various economic models exist for setting the price of grid resources, based on supply-and-demand and their value to the consumers. In this paper, we discuss the use of multiagent-based negotiation model for interaction between GROs and GRCs. For realizing this approach, we designed the Market- and Behavior-driven Negotiation Agents (MBDNAs). Negotiation strategies that adopt MBDNAs take into account the following factors: Competition, Opportunity, Deadline and Negotiator's Trading Partner's Previous Concession Behavior. In our experiments, we compare MBDNAs with MDAs (Market-Driven Agent), NDF (Negotiation Decision Function) and Kasbah in terms of the following metrics: total tasks complementation and budget spent. The results show that by taking the proposed negotiation model into account, MBDNAs outperform MDAs, NDF and Kasbah
  6. Keywords:
  7. Computational grid ; Negotiation model ; Software agent ; Computational grids ; Decision functions ; Efficient resource allocation ; Grid resource allocation ; Grid resource management ; Negotiation agents ; Negotiation models ; Negotiation strategy ; Grid computing ; International trade ; Multi agent systems ; Resource allocation ; Software agents ; Economics
  8. Source: Journal of Supercomputing ; Volume 66, Issue 3 , 2013 , Pages 1350-1389 ; 09208542 (ISSN)
  9. URL: http://link.springer.com/article/10.1007%2Fs11227-012-0808-4