计算机工程与应用2019，Vol.55Issue(24)：62-67,74,7.DOI:10.3778/j.issn.1002-8331.1810-0057
数据中心网络中相关感知流量整合算法
Correlation-Aware Traffic Consolidation Algorithm in Data Center Networks
摘要
Abstract
With big data and cloud computing continue to integrate into people’s daily lives, the energy consumption of data center networks, which are the infrastructure that underpins their development, is also rapidly increasing. To solve this problem, Energy-Aware Routing(EAR)is proposed. The main idea of EAR is that traffic demand are gathered over a subset of the network links, sleeping unused network equipment to save energy. However, during traffic peak time, net-work device patterns are switched frequently, which can cause network oscillation and performance degradation. There-fore, this paper proposes a Correlation-Aware Traffic Consolidation(CATC)algorithm in data center network. This paper proposes CATC model based on Software Defined Network(SDN), which considers the correlation between traffics dur-ing traffic consolidation and the adaptive link rate to save more energy. The CATC problem is formulated as an optimal traffic allocation problem subject to flow conservation constraint and link capacity constraint. Furthermore, the optimization problem is solved by the CATC algorithm. The simulation result shows, the CATC algorithm not only saves energy upto 45% at most for the data center network, but also increases little network delay compared with general centralized solutions.关键词
网络能耗/流量相关性/流量整合/软件定义网络/数据中心Key words
network energy consumption/traffic correlation/traffic consolidation/software defined network/data center分类
信息技术与安全科学引用本文复制引用
刘亮,张霖,杨柳,庞瑞琴,汪涛..数据中心网络中相关感知流量整合算法[J].计算机工程与应用,2019,55(24):62-67,74,7.基金项目
重庆市科委基础研究与前沿探索项目(No.cstc2018jcyjA0743,No.cstc2018jcyjA0644) （No.cstc2018jcyjA0743,No.cstc2018jcyjA0644）
重庆市教委科学技术研究项目(No.KJ1502003). （No.KJ1502003）
