Task cluster scheduling in a grid system

Effective load distribution and resource management is of great importance in designing complex distributed systems as grid. This pre-assumes the capability of partitioning the arriving jobs into independent tasks that can be executed simultaneously, assigning the tasks to processors and scheduling the task execution on each processor. A simulation model, consisting of two homogeneous clusters, is considered to evaluate the performance for various workloads. The Deferred policy is applied to collect global system information about processor queues. This paper proposes a special scheduling method referred to as task clustering method. We examine the efficiency of two task routing policies – one static and one adaptive – and six task scheduling policies, which rearrange processor queues regarding to a criterion. Our simulation results indicate that the adaptive task routing policy in conjunction with SGFS-ST scheduling algorithm, which uses more efficiently the task clustering method, leads to a significant performance improvement.