Thermal-benchmarking for cloud hosting green data centers

被引:9
|
作者
Chaudhry, Muhammad Tayyab [1 ]
Jamal, M. Hasan [1 ]
Gillani, Zeeshan [1 ]
Anwar, Waqas [1 ]
Khan, Muhammad Salman [1 ]
机构
[1] COMSATS Univ Islamabad, Dept Comp Sci, Lahore Campus, Lahore, Pakistan
关键词
Cloud computing; Green data centers; Thermal benchmarking; Workload modeling; RESOURCE-MANAGEMENT; ENERGY-EFFICIENT; WORKLOAD; POWER; SIMULATION;
D O I
10.1016/j.suscom.2019.100357
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Thermal efficient usage of cloud hosting data center servers saves cooling energy and helps establish green cloud data centers. To achieve this goal, the data centers must be stress-tested to avail thermal data related to server utilization. The inherent limitations of cloud computing limit the control of cloud data center owner over the workload execution of cloud services except for the infrastructure and therefore thermal-aware workload modeling or thermal benchmarking of cloud infrastructure can fill this gap. Thermal-benchmarking techniques, through manipulation of server utilization, reveal the thermal profiles and thermal statistics of the servers that can be useful for thermal efficient data center management. This paper presents a generic approach to thermal-benchmarking and profiling of cloud hosting data center servers. We propose workload models to generate customizable thermal benchmarks for stress testing of data center servers. Additionally, we use workload traces from Alibaba cloud to generate thermal statistics to show that the proposed thermal benchmarking approach is applicable to any data center workload trace for any data center server. (C) 2019 Elsevier Inc. All rights reserved.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Thermal-Aware Virtual Machine Allocation for Heterogeneous Cloud Data Centers
    Akbari, Abbas
    Khonsari, Ahmad
    Ghoreyshi, Seyed Mohammad
    ENERGIES, 2020, 13 (11)
  • [32] A Spatio-Temporal Prediction Method of Wind Energy in Green Cloud Data Centers
    Bi, Jing
    Li, Han
    Yuan, Haitao
    Duanmu, Shuaifei
    2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2021, : 570 - 575
  • [33] Lowering Down The Cost for Green Cloud Data Centers by Using ESDs and Energy Trading
    Gu, Chonglin
    Hu, Ke
    Li, Zhenlong
    Yuan, Qiang
    Huang, Hejiao
    Jia, Xiaohua
    2016 IEEE TRUSTCOM/BIGDATASE/ISPA, 2016, : 1508 - 1515
  • [34] Multi-objective VM Placement Algorithms for Green Cloud Data Centers: An Overview
    A-Shehri, Hanan Ali
    Hamdi, Khaoufla
    2018 21ST SAUDI COMPUTER SOCIETY NATIONAL COMPUTER CONFERENCE (NCC), 2018,
  • [35] A green-aware optimization strategy for virtual machine migration in cloud data centers
    Hussenet, Laurent
    Boucetta, Cherifa
    2022 INTERNATIONAL WIRELESS COMMUNICATIONS AND MOBILE COMPUTING, IWCMC, 2022, : 1082 - 1087
  • [36] A Data Generator for Cloud-Scale Benchmarking
    Rabl, Tilmann
    Frank, Michael
    Sergieh, Hatem Mousselly
    Kosch, Harald
    PERFORMANCE EVALUATION, MEASUREMENT AND CHARACTERIZATION OF COMPLEX SYSTEMS, 2011, 6417 : 41 - 56
  • [37] Cost minimization method with service delay assurance in hybrid green cloud data centers
    Huang X.
    Duanmu S.
    Bi J.
    Yuan H.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2021, 27 (08): : 2416 - 2425
  • [38] Recent advances in cloud data centers toward fog data centers
    Shojafar, Mohammad
    Pooranian, Zahra
    Sookhak, Mehdi
    Buyya, Rajkumar
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2019, 31 (08):
  • [39] An autonomic cloud environment for hosting ECG data analysis services
    Pandey, Suraj
    Voorsluys, William
    Niu, Sheng
    Khandoker, Ahsan
    Buyya, Rajkumar
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (01): : 147 - 154
  • [40] Robust charm: An efficient data hosting scheme for cloud data storage system
    Thangapandiyan M.
    Rubesh Anand P.M.
    Automatic Control and Computer Sciences, 2017, 51 (4) : 240 - 247