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
  • [1] Green Intelligence for Cloud Data Centers
    Karthik, C.
    Sharma, Mayank
    Maurya, Kirti
    Chandrasekaran, K.
    2016 3rd International Conference on Recent Advances in Information Technology (RAIT), 2016, : 591 - 597
  • [2] Energy Efficient Green Consolidator for Cloud Data Centers
    Dhule, Chetan
    Shrawankar, Urmila
    PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2019, : 405 - 409
  • [3] A Green Greedy Process Scheduler for Cloud Data Centers
    Karthik, C.
    Gupta, Aayush
    Chandrasekaran, K.
    2014 INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING AND INFORMATICS (IC3I), 2014, : 1302 - 1309
  • [4] Benchmarking Automated Hardware Management Technologies for Modern Data Centers and Cloud Environments
    Hojati, Elham
    Chen, Yong
    Sill, Alan
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC' 17), 2017, : 195 - 196
  • [5] Thermal Aware Workload Consolidation in Cloud Data Centers
    Marcel, Antal
    Cristian, Pintea
    Eugen, Pintea
    Claudia, Pop
    Cioara, Tudor
    Anghel, Ionut
    Ioan, Salomie
    2016 IEEE 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING (ICCP), 2016, : 377 - 384
  • [6] A green energy optimized scheduling algorithm for cloud data centers
    Sanjeevi, P.
    Viswanathan, P.
    2015 INTERNATIONAL CONFERENCE ON COMPUTING AND NETWORK COMMUNICATIONS (COCONET), 2015, : 941 - 945
  • [7] Green Scheduling for Cloud Data Centers Using Renewable Resources
    Gu, Chonglin
    Liu, Chunyan
    Zhang, Jiangtao
    Huang, Hejiao
    Jia, Xiaohua
    2015 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2015, : 354 - 359
  • [8] Optimized Renewable Energy Use in Green Cloud Data Centers
    Xu, Minxian
    Toosi, Adel N.
    Bahrani, Behrooz
    Razzaghi, Reza
    Singh, Martin
    SERVICE-ORIENTED COMPUTING (ICSOC 2019), 2019, 11895 : 314 - 330
  • [9] A Green energy-efficient scheduler for cloud data centers
    Amoon, Mohammed
    El Tobely, Tarek E.
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (02): : S3247 - S3259
  • [10] A Green energy-efficient scheduler for cloud data centers
    Mohammed Amoon
    Tarek E. El. Tobely
    Cluster Computing, 2019, 22 : 3247 - 3259