LAUSR

According to exascale computing roadmap, the dynamic nature of new generation scientific problems needs an undergoing review in the static management of computing resources. Therefore, it is necessary to present a dynamic load balancing model to manage the load of the system, efficiently. Currently, the distributed exascale systems are the promising solution to support the scientific programs with dynamic requests to resources. In this work, we propose a dynamic load balancing mechanism for distributed controlling of the load in the computing nodes. The presented method overcomes the challenges of dynamic behavior in the next generation problems. The proposed model considers many practical parameters including the load transition and communication delay. We also propose a compensating factor to minimize the idle time of computing nodes. We propose an optimized method to calculate this compensating factor. We estimate the status of nodes and also calculate the exact portion of the load that should be transferred to perform the optimized load balancing. The evaluation results show significant improvements regarding the performance by proposed load balancing in compared with some earlier distributed load balancing mechanisms.