Energy-efficient approaches to Cloud Computing

被引:0
|
作者
Asha, N. [1 ]
Rao, G. Raghavendra [2 ]
机构
[1] Natl Inst Engn, Dept PG Studies Comp Engn & Applicat, Mysore, Karnataka, India
[2] Natl Inst Engn, Dept Comp Sci & Engn, Mysore, Karnataka, India
关键词
Energy efficiencyt; distributed system; computing; power; communication;
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
Enterprises are looking forward to adopt cutting edge innovative technologies that could cut costs and maximize value. Cloud is getting into every Business, Industry and Enterprise applications ensuring economic and agility benefits. While Cloud seems to be disruptive, it's still a long way to go to completely materialize the Cloud. Cloud computing envisions that services, platforms and computing resources can be provided, on-demand, in a self-service fashion by a set of cooperating and/or competing providers to clients over the Internet. The emergence of cloud computing stems from the availability of numerous massive data centers, improvements in virtualization technologies and the availability and abundance of high speed networks. A large-scale computing infrastructure consumes enormous amounts of electrical power leading to operational costs not only exceed the cost of the infrastructure, also reflects on its carbon footprint. Green Cloud computing solution is needed that saves energy for the environment. This paper surveys techniques and solutions that aim to improve the energy efficiency of computing resources. It discusses methods to evaluate and model the energy consumed by these resources, and describes techniques that operate at a distributed system level, trying to improve aspects such as resource allocation.
引用
收藏
页码:337 / 342
页数:6
相关论文
共 50 条
  • [1] Energy-Efficient Cloud Computing
    Berl, Andreas
    Gelenbe, Erol
    Di Girolamo, Marco
    Giuliani, Giovanni
    De Meer, Hermann
    Dang, Minh Quan
    Pentikousis, Kostas
    [J]. COMPUTER JOURNAL, 2010, 53 (07): : 1045 - 1051
  • [2] Energy-Efficient Resource Allocation Approaches for Cloud Computing Systems: A Survey and Taxonomy
    Sharma, Chitra
    Tiwari, Pradeep Kumar
    Agarwal, Garima
    [J]. SMART SYSTEMS: INNOVATIONS IN COMPUTING (SSIC 2021), 2022, 235 : 479 - 484
  • [3] Recent Trends in Energy-Efficient Cloud Computing
    Mastelic, Toni
    Brandic, Ivona
    [J]. IEEE CLOUD COMPUTING, 2015, 2 (01): : 40 - 47
  • [4] Energy-Efficient Cloud Computing for Smart Phones
    Arya, Nancy
    Chaudhary, Sunita
    Taruna, S.
    [J]. EMERGING TRENDS IN EXPERT APPLICATIONS AND SECURITY, 2019, 841 : 111 - 115
  • [5] Energy-efficient data replication in cloud computing datacenters
    Boru, Dejene
    Kliazovich, Dzmitry
    Granelli, Fabrizio
    Bouvry, Pascal
    Zomaya, Albert Y.
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2015, 18 (01): : 385 - 402
  • [6] Energy-Efficient Hybrid Framework for Green Cloud Computing
    Alarifi, Abdulaziz
    Dubey, Kalka
    Amoon, Mohammed
    Altameem, Torki
    Abd El-Samie, Fathi E.
    Altameem, Ayman
    Sharma, S. C.
    Nasr, Aida A.
    [J]. IEEE ACCESS, 2020, 8 : 115356 - 115369
  • [7] Holistic Management for a more Energy-Efficient Cloud Computing
    Ayguade, Eduard
    Torres, Jordi
    [J]. ERCIM NEWS, 2010, (83): : 29 - 30
  • [8] Energy-Efficient Resource Management in Mobile Cloud Computing
    Jin, Xiaomin
    Liu, Yuanan
    Fan, Wenhao
    Wu, Fan
    Tang, Bihua
    [J]. IEICE TRANSACTIONS ON COMMUNICATIONS, 2018, E101B (04) : 1010 - 1020
  • [9] An energy-efficient failure detector for vehicular cloud computing
    Liu, Jiaxi
    Wu, Zhibo
    Dong, Jian
    Wu, Jin
    Wen, Dongxin
    [J]. PLOS ONE, 2018, 13 (01):
  • [10] Energy-efficient data replication in cloud computing datacenters
    Dejene Boru
    Dzmitry Kliazovich
    Fabrizio Granelli
    Pascal Bouvry
    Albert Y. Zomaya
    [J]. Cluster Computing, 2015, 18 : 385 - 402