The Nimrod/g Grid Resource Broker for Economics-based Scheduling

Computational Grids enable the coordinated and aggregated use of geographically distributed resources, often owned by autonomous organizations, for solving largescale problems in science, engineering, and commerce. However, application composition, resource management, and scheduling in these environments are complex undertakings [18,30]. This is due to the geographic distribution of resources that are often owned by different organizations having different usage policies and cost models, and varying loads and availability patterns. To address these resource management challenges, we have developed a distributed computational economy framework for quality-of-service (Qos)-driven resource allocation and regulation of supply and demand for resources. The new framework offers incentive to resource owners to participate in the Grid and motivates resource users to trade off between time for results delivery and economic cost, namely, deadline and budget [19]. Resource management systems need to provide mechanisms and tools that realize the goals of both service providers and consumers. Resource consumers need a utility model, representing their resource demand and preferences, and brokers that automatically generate strategies for choosing providers on the basis of this model. Further, the brokers need to manage as many issues associated with the execution of the underlying application as possible.