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

被引：0

作者：

Combarro, Manuel ^{[1
]}

Tchernykh, Andrei ^{[1
]}

Drozdov, Alexander ^{[2
]}

Kliazovich, Dzmitry ^{[3
]}

Radchenko, Gleb ^{[4
]}

机构：

[1] CICESE Res Ctr, Ensenada, Baja California, Mexico

[2] Moscow Inst Phys & Technol, Moscow, Russia

[3] Univ Luxembourg, Luxembourg, Luxembourg

[4] South Ural State Univ, Chelyabinsk, Russia

来源：

2016 INTERNATIONAL CONFERENCE ON ENGINEERING AND TELECOMMUNICATION (ENT 2016) | 2016年

关键词：

data center; energy efficient; parallel machines; scheduling algorithms;

D O I：

10.1109/EnT.2016.13

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：29 / 33

页数：5

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