Energy-aware scheduling using slack reclamation for cluster systems

Reducing energy consumption in processors has become a critical issue in cluster systems. The dynamic voltage and frequency scaling (DVFS) is one of the effective techniques to minimize energy consumption in processors when executing parallel applications. These applications may consist of many interrelated tasks that may be computed when their precedence constraints are satisfied. The scheduling of these precedence-constrained tasks on to processors, to optimize makespan or energy consumption or both, has been studied as an NP-complete problem. Thus, many algorithms have been given by the researchers and newer algorithms keep coming in. In the parallel applications, there exist some tasks which may have slacks due to the dependencies between tasks. The EASLA (energy aware service level agreement) is one of the well-known energy-aware task scheduling algorithms which utilize the underused slack of tasks. In this paper, we present an improved version of its sub-algorithm, NCM (Not Changing Makespan), for heterogeneous cluster systems that is used to downscale frequencies when schedule length does not change. The presented algorithm also makes use of a fast and low complexity algorithm called PEFT (Predict Earliest Finish Time) to compute the schedule length of the application. We performed experiments for randomly generated graphs, and the results illustrate that the improved version of the NCM algorithm achieves better energy saving compared to the NCM algorithm.