AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks

doi:10.1109/TNET.2020.3026015

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	AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks
	Guo, Zehua 1; Xu, Yang 2,3; Liu, Ya-Feng 4; Liu, Sen 2; Chao, H. Jonathan 5; Zhang, Zhi-Li 6; Xia, Yuanqing 1
	2021-02-01
发表期刊	IEEE-ACM TRANSACTIONS ON NETWORKING
ISSN	1063-6692
卷号	29 期号:1 页码:17-33
摘要	Power-efficient Data Center Networks (DCNs) have been proposed to save power of DCNs using OpenFlow. In these DCNs, the OpenFlow controller adaptively turns on/off links and OpenFlow switches to form a minimum-power subnet that satisfies the traffic demand. As the subnet changes, flows are dynamically routed and rerouted to the routes composed of active switches and links. However, existing flow scheduling schemes could cause undesired results: (1) power inefficiency: due to unbalanced traffic allocation on active routes, extra switches and links may be activated to cater to bursty traffic surges on congested routes, and (2) Quality of Service (QoS) fluctuation: because of the limited flow entry processing ability, switches may not be able to timely install/delete/update flow entries to properly route/reroute flows. In this paper, we propose AggreFlow, a dynamic flow scheduling scheme that achieves power efficiency and QoS improvement using three techniques: Flow-set Routing, Lazy Rerouting, and Adaptive Rerouting. Flow-set Routing achieves load balancing with a small number of flow entry operations by routing flows in a coarse-grained flow-set fashion. Lazy Rerouting spreads rerouting operations over a relatively long period of time, reducing the burstiness of entry operation on switches. Adaptive Rerouting selectively reroutes flow-sets to maintain load balancing. We built an NS3 based fat-tree network simulation platform to evaluate AggreFlow's performance. The simulation results show that AggreFlow reduces power consumption by about 18%, yet achieving load balancing and improved QoS (low packet loss rate and reducing the number of processing entries for flow scheduling by 98%), compared with baseline schemes.
关键词	Load management Control systems Quality of service Data centers Power demand Dynamic scheduling Flow scheduling power-efficient data center networks power saving OpenFlow
DOI	10.1109/TNET.2020.3026015
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFB1003700] ; Natural Science Foundation of China[62002019] ; Natural Science Foundation of China[11688101] ; Natural Science Foundation of China[11671419] ; Natural Science Foundation of China[11991021] ; Natural Science Foundation of China[62002066] ; Beijing Institute of Technology Research Fund Program for Young Scholars ; Project PCL Future GreaterBay Area Network Facilities for Large-scale Experiments and Applications[LZC0019] ; U.S. NSF[CNS-1618339] ; U.S. NSF[CNS-1617729] ; U.S. NSF[CNS-1814322]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000619370600002
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/58204
专题	中国科学院数学与系统科学研究院
通讯作者	Xu, Yang
作者单位	1.Beijing Inst Technol, Beijing 100081, Peoples R China 2.Fudan Univ, Sch Comp Sci, Shanghai 200433, Peoples R China 3.Peng Cheng Lab, Shenzhen 518066, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China 5.NYU, Tandon Sch Engn, Brooklyn, NY 11201 USA 6.Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA
推荐引用方式 GB/T 7714	Guo, Zehua,Xu, Yang,Liu, Ya-Feng,et al. AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks[J]. IEEE-ACM TRANSACTIONS ON NETWORKING,2021,29(1):17-33.
APA	Guo, Zehua.,Xu, Yang.,Liu, Ya-Feng.,Liu, Sen.,Chao, H. Jonathan.,...&Xia, Yuanqing.(2021).AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks.IEEE-ACM TRANSACTIONS ON NETWORKING,29(1),17-33.
MLA	Guo, Zehua,et al."AggreFlow: Achieving Power Efficiency, Load Balancing, and Quality of Service in Data Center Networks".IEEE-ACM TRANSACTIONS ON NETWORKING 29.1(2021):17-33.