On time-sensitive revenue management in green data centers

被引：2

作者：

Wang, Huangxin ^{[1
]}

Zhang, Jean X. ^{[2
]}

Yang, Bo ^{[3
]}

Li, Fei ^{[4
]}

机构：

[1] George Mason Univ, Dept Comp Sci, Fairfax, VA 22030 USA

[2] Virginia Commonwealth Univ, Sch Business, Dept Accounting, Med Coll Virginia Campus, Richmond, VA 23284 USA

[3] Jilin Univ, Sch Comp Sci & Technol, Changchun 130012, Jilin, Peoples R China

[4] George Mason Univ, Dept Comp Sci, Fairfax, VA 22030 USA

来源：

SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS | 2017年 / 14卷

基金：

中国国家自然科学基金;

关键词：

Green data centers; Revenue management; Energy scheduling; Job scheduling; ENERGY;

D O I：

10.1016/j.suscom.2017.01.002

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we design an analytically and experimentally better online energy and job scheduling algorithm with the objective of maximizing net profit for service providers in green data centers. We first study the previously known algorithms and conclude that these online algorithms have provable poor performance in their worst-case scenarios. To guarantee an online algorithm's performance in hindsight, we design a randomized algorithm to schedule energy and jobs in the data centers and prove the algorithm's expected competitive ratio in a special setting. Our algorithm is theoretical-sound and it outperforms the previously known algorithms in many settings using both real traces and simulated data. An optimal offline algorithm is also provided as an empirical benchmark. (C) 2017 Elsevier Inc. All rights reserved.

引用

页码：1 / 12

页数：12

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