A QoS management system and an efficient scheduling heuristic for network computing applications

The dynamic state conditions of the Network of Workstations (NOW) resources should be used to find the best acceptable tasks-to-machines allocation strategy before a network computing (NC) application is launched. We developed an interactive QoS management system that automatically finds the most efficient tasks-to-machines mapping at startup time, and in addition facilitates application adaptation at runtime. The system is self contained and relies on its own middleware layer to do the resource monitoring and servicing behind the scenes, at the application-level. It groups the available machines into clusters to scale down the number of required QoS measurements and to facilitate the mapping process. A scheduler considers user requirements and constraints and uses an efficient mapping heuristic to find an acceptable assignment. The performance estimator predicts the overall running time of a given mapping based on application and network models as well as resource state information. The estimated time is used to decide whether the mapping satisfies the QoS targets set by the user. Furthermore, we conducted many simulations that demonstrate the accuracy of the application and network models as well as the quality of the obtained mappings in different kinds of scenarios and using different types of applications.