Grid Scheduling using 2-Phase Prediction (2PP) of CPU Power

Divisible workloads are that kind of workloads that can be partitioned by the scheduler into arbitrary ´chunks´. The problem of scheduling divisible loads has been defined for a long time, however, handful solutions have been proposed. Furthermore, almost all proposed approaches attempt to perform scheduling in a dedicated environment (i.e., for processing local tasks only) such as a LAN, whereas scheduling in non-dedicated environments (i.e., for processing local and external tasks) such as grids remains an open problem. In grids, the incessant variation of workstation´s power is the chief difficulty in planning how to split and distribute workloads to these workstations. This paper presents a new strategy, called 2-phase prediction (2PP) for CPU power. By integrating this strategy and the UMR algorithm, a static scheduling algorithm that is designed for dedicated environments, we develop a new dynamic scheduling algorithm suitable for non-dedicated environment. Our experimental results show that our algorithm is superior to the UMR as the former is able to adapt to the dynamicity of grid workers