Real-time scheduling of divisible loads in cluster computing environments

Cluster computing has become an important paradigm for solving large-scale problems. To enhance the quality of service (QoS) and provide performance guarantees in a cluster computing environment, various real-time scheduling algorithms and workload models have been investigated. Computational loads that can be arbitrarily divided into independent tasks represent many real-world applications. However, the problem of providing performance guarantees to divisible load applications has only recently been studied systematically. In this work, three important and necessary design decisions, (1) workload partitioning, (2) node assignment, and (3) task execution order, are identified for real-time divisible load scheduling. A scheduling framework that can configure different policies for each of the three design decisions is proposed and used to generate various algorithms. This paper systematically studies these algorithms and identifies scenarios where the choices of design parameters have significant effects.