Multi-cluster environments are composed of multiple clusters 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 resources heterogeneity and the co-allocation process, which distributes the tasks of parallel jobs across cluster boundaries.
In this paper, the authors propose a new MIP model which determines the best scheduling for all the jobs in the queue, identifying their resource allocation and its execution order to minimize the overall makespan. The results show that the proposed technique produces a highly compact scheduling of the jobs, producing better resources utilization and lower overall makespan. This makes the proposed technique especially useful for environments dealing with limited resources and large applications.