MetaLoRaS:: A predictable Metascheduler for non-dedicated multiclusters

The main aim of this work is to take advantage of the computer resources of a single organization or Multicluster system to execute distributed applications efficiently without excessively damaging the local users. In doing so we propose a Metascheduler environment named MetaLoRaS with a 2-level hierarchical architecture for a non-dedicated Multicluster with job prediction capabilities. Among other Metaschedulers, the non-dedicated feature and an efficient prediction system are the most distinctive characteristics of MetaLoRaS. Another important contribution is the effective cluster selection mechanism, based on the prediction system. In this article, we show how the hierarchical architecture and simulation mechanism are the best choices if we want to obtain an accurate prediction system and, at the same time, the best turnaround times for distributed jobs without damaging local user performance.