A deadline and cost optimization algorithm for scheduling task in grids and Nash equilibrium in auction-based systems

Whereas grids enable the sharing, selection, query and aggregation of geographically distributed resources for solving large-scale problems, providing efficient resource allocation mechanism managing Grid resources is a complex undertaking. In this work, we have investigated several famous schedule methods proposed by Nimrod-G, a famous computational economy framework for regulating the supply and demand for resources. We proposed a new scheduling algorithm, called DBC deadline and cost optimization, which extends the DBC cost optimization and time optimize algorithm, keeping the cost and time optimization at the minimum. A compare of these several schedule algorithms that schedules userpsilas Bag of Task applications on divisible auction-based resource allocation systems is executed. It is shows that the structure of the schedule method allows quasilinear characterization of a wide variety of broker tasks. We prove that the auction has a unique Nash equilibrium and propose a decentralized bidding strategy.