Power-Aware Linear Programming based Scheduling for heterogeneous computer clusters

Abstract

In the past few years, scheduling for computer clusters has become a hot topic. The main focus has been towards achieving better performance. It is true that this goal has been attained to a certain extent, but on the other hand, it has been at the expense of increased energy consumption and consequent economic and environmental costs. As these clusters are becoming more popular and complex, reducing energy consumption in such systems has become a necessity. Several power-aware scheduling policies have been proposed for homogeneous clusters. In this work, we propose a new policy for heterogeneous clusters. Our simulation experiments show that using our proposed policy results in significant reduction in energy consumption while performing very competitively in heterogeneous clusters.

Obtaining dynamic scheduling policies with simulation and machine learning

“…Over the history of scheduling study, many works a empted to tackle the problem of scheduling with a wide range of approaches, covering from integer linear programming [3,11] to genetic algorithms [13,20] and neural networks [1,2]. Xhafa and Abraham [24] present a review of recent computational models and heuristics for scheduling in HPC platforms.…”

Linear programming based parallel job scheduling for power constrained systems

“…It gives a frequency scaling algorithm for a specific type of job scheduling with deadline constraints that is not common in HPC centers. One more work targets bag-of-tasks applications scheduling ( [29]). It aims to minimize power consumption of heterogeneous clusters using linear programming.…”

An Optimizing Technique based on Genetic Algorithm for Power Management in Heterogeneous Multi-Tier Web Clusters

“…Therefore, it is desired to increase performance per unit of energy. Several power management techniques have been proposed for multi-tier clusters [9][10][11][12][13][14]. Most of the researches have focused on homogeneous clusters [22][23][24].…”

“…Al-Daoud et al [9] proposed LPAS policy for heterogeneous clusters. The experimentation results showed the reduction in energy consumption.…”