Energy-Aware Scheduling with Computing and Data Consolidation Balance in 3-Tier Data Center

Abstract

Energy consumption represents a large percentage of the operational expenses in data centers. Most of the existing solutions for energy-aware scheduling are focusing on job distribution and consolidation between computing servers, while network characteristics are not considered. In this paper, we propose a model of power and network-aware scheduling that can be tuned to achieve energy-savings, through job consolidation and traffic load balancing. We describe a methodology to find the best tuning of the Adjustable Scheduler.