Temporal Request Scheduling for Energy-Efficient Cloud Data Centers

被引:0
作者
Bi, Jing [1 ]
Yuan, Haitao [2 ]
Qiao, Junfei [1 ]
Zhou, MengChu [3 ]
Song, Xiao [4 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[2] Beijing Jiaotong Univ, Sch Software Engn, Beijing 100044, Peoples R China
[3] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
[4] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
来源
PROCEEDINGS OF THE 2017 IEEE 14TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC 2017) | 2017年
基金
北京市自然科学基金; 中国博士后科学基金;
关键词
Scheduling; Cloud data center; Energy efficiency; Hybrid optimization; MANAGEMENT; HYBRID; RESOURCE; NETWORK;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The cost of grid energy of cloud providers rises greatly due to the growing number of Internet services. Therefore, researches on energy-efficient cloud data centers (ECDCs) are increasingly focused on the effective use of renewable energy instead of brown energy for environmental protection. Because of the temporal difference in price of grid, solar irradiance and wind speed, it is diffcult to satisfy the performance of each delay bounded request with lower grid energy cost of an ECDC. In this work, a temporal request scheduling (TRS) algorithm is proposed for the temporal diversity with strict delay assurance to schedule the appropriate execution of all arriving requests. In addition, a mathematical model is presented to describe the relation between ECDC's service rate and request refusaI. The formulated nonlinear optimization problem is solved by a hybrid meta-heuristic algorithm. Experimental results demonstrate that TRS can realize less cost of grid energy and high er throughput for an ECDC while satisfying requests' delay requirement than three representative scheduling methods.
引用
收藏
页码:180 / 185
页数:6
相关论文
共 50 条
  • [41] Energy-Efficient Virtual Machines Consolidation in Cloud Data Centers using Reinforcement Learning
    Farahnakian, Fahimeh
    Liljeberg, Pasi
    Plosila, Juha
    2014 22ND EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, AND NETWORK-BASED PROCESSING (PDP 2014), 2014, : 500 - 507
  • [42] Reinforcement learning based methodology for energy-efficient resource allocation in cloud data centers
    Thein, Thandar
    Myo, Myint Myat
    Parvin, Sazia
    Gawanmeh, Amjad
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2020, 32 (10) : 1127 - 1139
  • [43] Software Techniques for Making Cloud Data Centers Energy-efficient: A Systematic Mapping Study
    Khan, Fauzia
    Anwar, Hina
    Pfahl, Dietmar
    Srirama, Satish
    2020 46TH EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA 2020), 2020, : 479 - 486
  • [44] Energy-efficient migration and consolidation algorithm of virtual machines in data centers for cloud computing
    Li, Hongjian
    Zhu, Guofeng
    Cui, Chengyuan
    Tang, Hong
    Dou, Yusheng
    He, Chen
    COMPUTING, 2016, 98 (03) : 303 - 317
  • [45] Designing Energy-Efficient Servers and Data Centers
    Carter, John
    Rajamani, Karthick
    COMPUTER, 2010, 43 (07) : 76 - 78
  • [46] HEROS: Energy-Efficient Load Balancing for Heterogeneous Data Centers
    Guzek, Mateusz
    Kliazovich, Dzmitry
    Bouvry, Pascal
    2015 IEEE 8TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, 2015, : 742 - 749
  • [47] EMO-TS: An Enhanced Multi-Objective Optimization Algorithm for Energy-Efficient Task Scheduling in Cloud Data Centers
    Nambi, S.
    Thanapal, P.
    IEEE ACCESS, 2025, 13 : 8187 - 8200
  • [48] NUTS scheduling approach for cloud data centers to optimize energy consumption
    P. Sanjeevi
    P. Viswanathan
    Computing, 2017, 99 : 1179 - 1205
  • [49] NUTS scheduling approach for cloud data centers to optimize energy consumption
    Sanjeevi, P.
    Viswanathan, P.
    COMPUTING, 2017, 99 (12) : 1179 - 1205
  • [50] An Energy-Efficient Data Placement Algorithm and Node Scheduling Strategies in Cloud Computing Systems
    Xiao, Yanwen
    Wang, Jinbao
    Li, Yaping
    Gao, Hong
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER SCIENCE AND ENGINEERING (CSE 2013), 2013, 42 : 59 - 63