OAS: A MIP Model for Ordering and Allocating Parallel Jobs on M ulti-Cluster Systems

Multi-cluster environments are composed of multiple clusters of computers that act collaboratively, thus allowing computational problems that require more resources than those available in a single cluster to be treated. However, the degree of complexity of the scheduling process is greatly increased by the heterogeneity of resources and the co-allocation process, which distributes the tasks of parallel jobs across cluster boundaries. In a previous work, the authors presented a scheduling strategy which selects from the system queue only the set of jobs that fits the available resources, and finds their best possible allocation by a Mixed-Integer Programming model (MIP), considering both the processing and communication requirements of the applications. In this study, the authors propose a new MIP model that treats a set of jobs in the waiting queue determining their best execution order and allocation, in order to improve the makespan of the set of jobs.