Segment Routing Green Spine Switch Management Systems for Data Center Networks

被引:0
作者
Osamudiamen, Ose [1 ]
Lung, Chung-Horng [1 ]
机构
[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON, Canada
来源
2018 IEEE CONFERENCE ON DEPENDABLE AND SECURE COMPUTING (DSC) | 2018年
基金
加拿大自然科学与工程研究理事会;
关键词
Segment routing; traffic engineering; energy savings; datacenter networks; network reliability; leaf-spine;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The datacenter is the core of most IT industries today. As a result, due to the exponential increase of information and services demanded from datacenters, it is projected that 14.1 zeta bytes of bandwidth would be needed to meet the current demands of data by the end of 2020 in USA datacenters alone. This would require a tremendous amount of energy to run those datacenters. Hence, in recent years there is more focus on reducing the energy consumption in a datacenter. This paper approaches this problem by utilizing Segment Routing based Green Spine Switch Management System (SR-GSSMS) to have an efficient bandwidth usage. The proposed approach makes it possible to deactivate some low utilized spine switches and links on the datacenter networks, which results in energy savings. The system also maintains the network performance when congestion or a link failure occurs. Our experimental results yielded up to a 78% energy savings on the spine-links, while maintaining the same traffic requirements.
引用
收藏
页码:213 / 220
页数:8
相关论文
共 30 条
  • [1] Abts D, 2010, CONF PROC INT SYMP C, P338, DOI 10.1145/1816038.1816004
  • [2] A scalable, commodity data center network architecture
    Al-Fares, Mohammad
    Loukissas, Alexander
    Vahdat, Amin
    [J]. ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2008, 38 (04) : 63 - 74
  • [3] Optimizing Server Resource by Using Virtualization Technology
    Ali, Edwar
    Susandri
    Rahmaddeni
    [J]. INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND COMPUTATIONAL INTELLIGENCE (ICCSCI 2015), 2015, 59 : 320 - 325
  • [4] [Anonymous], 2010, Performance analysis of high performance computing applications on the amazon web services cloud
  • [5] Arista Networks, 2017, SOFTW DRIV CLOUD NET
  • [6] Benson A., 2010, P 10 ACM SIGCOMM C I, P267, DOI [DOI 10.1145/1879141.1879175, 10.1145/1879141.1879175, 10.1145/1879141.1879175.5]
  • [7] Energy Efficiency in the Future Internet: A Survey of Existing Approaches and Trends in Energy-Aware Fixed Network Infrastructures
    Bolla, Raffaele
    Bruschi, Roberto
    Davoli, Franco
    Cucchietti, Flavio
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2011, 13 (02): : 223 - 244
  • [8] C. Services, 2017, CISCO DATA CTR SPINE
  • [9] Carrega A., 2012, International Symposium on Performance Evaluation of Computer and Telecommunication Systems, P1
  • [10] A Critical Analysis of Energy Efficient Virtual Machine Placement Techniques and its Optimization in a Cloud Computing Environment
    Choudhary, Ankita
    Rana, Shilpa
    Matahai, K. J.
    [J]. 1ST INTERNATIONAL CONFERENCE ON INFORMATION SECURITY & PRIVACY 2015, 2016, 78 : 132 - 138