IANOS solves the non-trivial problem of scheduling applications within a Grid of HPC machines through a novel approach of combined cost and execution time evaluation based on job re-quirements, application and resource characteristics, as well as historical data. These algorithms are the backbone of a service-based framework that automatically finds best-suited resources for a certain application request and negotiates the specific QoS demands with the respective resource providers. Two models are used: the Cost Function model and the Execution Time Evaluation model. They are based on a parameterisation of the applications and the resources. The Cost Function model calculates the cost value for each candidate resource. The Execution Time Evaluation model forecasts the execution time of a given application on a given resource, a prediction based on the knowledge about the CPU node performance of the applications.