Energy-efficient virtual content distribution network provisioning in cloud-based data centers

被引:14
作者
Liao, Dan [1 ,2 ]
Sun, Gang [1 ,3 ]
Yang, Guanghua [1 ]
Chang, Victor [4 ]
机构
[1] UESTC, Minist Educ, Key Lab Opt Fiber Sensing & Commun, Chengdu 611731, Sichuan, Peoples R China
[2] UESTC, Guangdong Inst Elect & Informat Engn, Chengdu 523808, Sichuan, Peoples R China
[3] UESTC, Ctr Cyber Secur, Chengdu 611731, Sichuan, Peoples R China
[4] Xran Jiaotong Liverpool Univ, Suzhou 215123, Peoples R China
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2018年 / 83卷
基金
中国国家自然科学基金;
关键词
Content distribution network; Energy efficiency; Cloud computing; Service level agreement; TIME-SERIES; CONTENT DELIVERY; SPECTRAL EFFICIENCY; NEURAL-NETWORKS; LIVE MIGRATION; HYBRID ARIMA; FRAMEWORK; ALGORITHM; FORECAST; MODELS;
D O I
10.1016/j.future.2018.01.057
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Cloud-based content distribution networks (CDNs) consist of multiple servers that consume large amounts of energy. However, with the development of a cloud-based software defined network (SDN), a new paradigm of the virtual content distribution network (vCDN) has emerged. In an emerging cloud based vCDN environment, the development and adjustment of vCDN components has become easier with the aid of SDN technology. This transformation provides the opportunity to use vCDNs to reduce energy consumption by adjusting the scale of the vCDN components. Energy costs can be reduced by deactivating the commercial servers carrying the software components of the vCDN, such as replica servers, the firewall or routers. In addition, the CDN requires a high service level agreement (SLA) to respond to clients' requests, potentially consuming large amounts of energy. In this research, we focus on the issue of the energy savings of a CDN in a cloud computing environment while maintaining a high quality of service (QoS). We propose an approximate algorithm termed max flow forecast (MFF) to determine the number of software components in the vCDN. Additionally, we use a real traffic trace from a website to assess our algorithm. The experimental results show that MFF can produce a larger energy reduction than the existing algorithms for an identical SLA. We fully justify our research as a good example for the emerging cloud. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:347 / 357
页数:11
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