Using Automated Negotiation for Grid Services

Abstract

The popularity of grid services has widened their application to numerous domains and increased the utilization of computational resources. In order to create more incentives for the resources owners to lease their resources and prevent users from wasting the resources, the introduction of a market-oriented grid is inevitable. However, the issues for the negotiation between service provider and consumer over the supply and demand of resources can be complex, with highly interdependent issues. In this research, a simulated automated negotiation mechanism including a co-evolutionary mechanism and a modified game theory approach is proposed, to assist them in reaching an agreement over the conflicting issues. In the proposed architecture, the co-evolution process is able to reduce the multiple dimensional search space into a two-dimension search space and identify the appropriate negotiation strategies for the negotiating agents to form a payoff matrix which can be used for the game theory related stage of their interaction. The multiple stage negotiation process is introduced to improve the negotiation result. In this paper, an application which requires a large amount of computational resources to process the data generated from mobile devises is used to demonstrate that the proposed system is able to resolve the conflicts and obtain a valid solution.

Modern Advances in Applied Intelligence

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A New Resource Allocation Model for Grid Networks based on Bargaining in a Competitive Market

“…Marketbased models can be categorized as follows: bartering based model, price-based model and bargaining model [1]. In the bartering based model presented in [1] and [8], all companies must possess sources and perform business by exchanging them (for example the exchange of CPU time with storage space). In the priced-based model, the sources have a price which is set according to supply, demand and value in the economic system.…”

Grid Resource Negotiation: Survey and New Directions

“…Third-party mediation: In addition to the works reviewed in Section IV, it is noted that [56] also considered a G-negotiation mechanism by adopting genetic algorithm (GA) for evolving agents' strategies by exploring the possible agreement space and employed a trusted third party protocol (TTP) to find an optimized point in the agreement space. By employing a negotiation protocol that combines GA and TTP, a mutually beneficial agreement point can be reached.…”