面向大数据的绿色IT框架能效分类机制  

Energy-Efficiency Classifying Mechanism for Green IT Framework of Big Data

作　　者：王丽芳[1] 齐勇[2] 蒋泽军[1] 彭成章[1] 

机构地区：[1]西北工业大学计算机学院,西安710072 [2]陕西科技大学电信学院,西安710129

出　　处：《工程研究（跨学科视野中的工程）》2014年第3期224-232,共9页JOURNAL OF ENGINEERING STUDIES

基　　金：国家自然科学基金资助项目(61373120);航空科学基金资助项目(2012ZC53040)

摘　　要：与分散处理相比较,大数据中心集中处理信息通信任务,在能效上已有巨大的提高。但大数据中心包括数以千万记的服务器,其能源消耗量甚至可以超过一座小型城镇。巨大的能源消耗、成吨的温室气体排放,使大数据中心在能效与减排方面面临诸多挑战,建立绿色高效的大数据中心势在必行。本文给出一个面向大数据的绿色IT框架,重点研究了能效分类问题,提出了一个基于度量模型的能效分类机制。根据工作量和能源消耗情况对设备和服务进行分类,无缝地划分为不同的资源池,将电力使用效率、数据中心工作效率和二氧化碳排放等综合计算衡量,制定可以实现并遵循的能效标准,使绘制大数据中心的碳足迹成为可能,并提供服务能效评估方案。Compared with the distributed processing, large data center focuses on information and commu-nication tasks and has already made huge improvement on energy efficiency. But large data center includes tens of millions of servers, and its energy consumption can be ever larger than one small town. Huge energy consumption and tons of greenhouse gas emission bring many challenges to large data center in terms of energy efficiency and emission reduction. Therefore, the establishment of green and efficient large data center is imperative. This paper provides a framework of green IT for large data, focusing on energy efficiency classification and proposes an en-ergy efficiency classification mechanism based on measurement model. According to the workload and energy consumption, this paper classifies the equipment and services seamlessly into different resource pool. Power effi-ciency, data center efficiency and carbon dioxide emissions are calculated and measured. This paper also formu-lates energy efficiency standards which could be realized and followed. The standards make the drawing of the big data center carbon trace possible and provide scheme for energy efficiency evaluation.

关 键 词：大数据 绿色IT 能效分类 能效度量模型 能效评估 

分 类 号：TP308[自动化与计算机技术—计算机系统结构]