A scheduling method for divisible workload problem in grid environments

Scheduling divisible workloads in distributed systems has been one of the interesting research problems over the last few years. Most of the scheduling algorithms previously introduced are based on the master-worker model. However, the majority of these algorithms assume that workers are dedicated machines, which is a wrong assumption in distributed environments such as Grids. In this work, we propose a dynamic scheduling methodology that takes into account the three prominent aspects of Grids: heterogeneity, dynamicity, and uncertainty. Our contribution is threefold. First, we present an analytical model for processing local and Grid tasks at each non-dedicated worker. Second, we present a simple prediction method to forecast the available CPU capacity and bandwidth at each worker. Third, we introduce a dynamic, multi-round scheduling algorithm.