iSwitch: Coordinating and Optimizing Renewable Energy Powered Server Clusters

被引:0
|
作者
Li, Chao [1 ]
Qouneh, Amer [1 ]
Li, Tao [1 ]
机构
[1] Univ Florida, Dept Elect & Comp Engn, IDEAL, Gainesville, FL 32611 USA
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Large-scale computing systems such as data centers are facing increasing pressure to cap their carbon footprint. Integrating emerging clean energy solutions into computer system design therefore gains great significance in the green computing era. While some pioneering work on tracking variable power budget show promising energy efficiency, they are not suitable for data centers due to lack of performance guarantee when renewable generation is low and fluctuant. In addition, our characterization of wind power behavior reveals that data centers designed to track the intermittent renewable power incur up to 4X performance loss due to inefficient and redundant load matching activities. As a result, mitigating operational overhead while still maintaining desired energy utilization becomes the most significant challenge in managing server clusters on intermittent renewable energy generation. In this paper we take a first step in digging into the operational overhead of renewable energy powered data center. We propose iSwitch, a lightweight server power management that follows renewable power variation characteristics, leverages existing system infrastructures, and applies supply/load cooperative scheme to mitigate the performance overhead. Comparing with state-of-the-art renewable energy driven system design, iSwitch could mitigate average network traffic by 75%, peak network traffic by 95%, and reduce 80% job waiting time while still maintaining 96% renewable energy utilization. We expect that our work can help computer architects make informed decisions on sustainable and high-performance system design.
引用
收藏
页码:512 / 523
页数:12
相关论文
共 50 条
  • [41] EPSCS: Simulating and Measuring Energy Proportionality of Server Clusters
    Xie, Jiazhuang
    Jin, Peiquan
    Wan, Shouhong
    Yue, Lihua
    [J]. DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, DASFAA 2015, PT II, 2015, 9050 : 536 - 540
  • [42] Optimizing server placement for parallel I/O in switch-based clusters
    Wu, Jan-Jan
    Lin, Yi-Fang
    Wang, Da-Wei
    Wang, Chien-Min
    [J]. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2009, 69 (03) : 266 - 281
  • [43] Optimizing Grid Connected Renewable Energy Resources with Variability
    Momoh, James A.
    D'Arnaud, Keisha
    [J]. 2012 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2012,
  • [44] Optimizing plant size in the planning of renewable energy portfolios
    Cucchiella F.
    D’Adamo I.
    Gastaldi M.
    [J]. Letters in Spatial and Resource Sciences, 2016, 9 (2) : 169 - 187
  • [45] Optimizing the flexible design of hybrid renewable energy systems
    Giahi, Ramin
    MacKenzie, Cameron A.
    Hu, Chao
    [J]. ENGINEERING ECONOMIST, 2022, 67 (01): : 25 - 51
  • [46] Optimizing renewable energy utilization with high gain converters
    Tamilselvan, D.
    Sudhakar, T. D.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2024, 191
  • [47] A Dual Delay Timer Strategy for Optimizing Server Farm Energy
    Yao, Fan
    Wu, Jingxin
    Venkataramani, Guru
    Subramaniam, Suresh
    [J]. 2015 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2015, : 258 - 265
  • [48] QoS Aware Energy Allocation Policy for Renewable Energy Powered Cellular Networks
    Li, Qiao
    Wei, Yifei
    Song, Mei
    Yu, F. Richard
    [J]. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2016, 10 (10): : 4848 - 4863
  • [49] Development of a Mobile Water Disinfection Unit Powered by Renewable Energy
    Vitello, Matthew
    Elmore, Andrew C.
    Crow, Mariesa
    [J]. JOURNAL OF ENERGY ENGINEERING-ASCE, 2011, 137 (04): : 207 - 213
  • [50] Optimum Energy Cooperation among Renewable Powered Base Stations
    Pawar, Sarika
    Islam, Shama Naz
    Mahmud, Apel
    Oo, Aman Maung Than
    [J]. 2018 AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE (AUPEC), 2018,