Energy Efficient Utilization of Cloud Resources Using Hybrid Ant colony Genetic Algorithm for a Sustainable Green Cloud Environment

被引:0
|
作者
Karuppasamy, M. [1 ]
Suprakash, S. [1 ]
Balakannan, S. P. [1 ]
机构
[1] Kalasalingam Univ, Krishnankoil, Tamil Nadu, India
来源
PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL (I2C2) | 2017年
关键词
Cloud Computing; Green; Environment; Virtualization; Energy;
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
Nowadays the Cloud computing services are proliferation. The Cloud computing resources face major pitfall in energy consumes. The prime of energy consumption in cloud computing is by means of client computational devices, server computational devices, network computational devices and power required to cool the IT load. The cloud resources contribute high operational energy cost and emit more carbon emission to the environment. Therefore the cloud services providers need green cloud environment resolution to decrease the operational energy cost along with environmental impact. The major objective of this work is to trim down the energy from utilized and unutilized (idle) cloud resources and save the energy in cloud resources efficiently. To achieve the sustainable green cloud environment from a Hybrid Ant colony Genetic Algorithm used in this paper which chooses the appropriate virtual services so that the power at the client, server and network recourses can be reduced.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Multi-Objective Task Scheduling Using Hybrid Genetic-Ant Colony Optimization Algorithm in Cloud Environment
    A. M. Senthil Kumar
    M. Venkatesan
    Wireless Personal Communications, 2019, 107 : 1835 - 1848
  • [2] Multi-Objective Task Scheduling Using Hybrid Genetic-Ant Colony Optimization Algorithm in Cloud Environment
    Kumar, A. M. Senthil
    Venkatesan, M.
    WIRELESS PERSONAL COMMUNICATIONS, 2019, 107 (04) : 1835 - 1848
  • [3] A Genetic-Ant-Colony Hybrid Algorithm for Task Scheduling in Cloud System
    Wu, Zhilong
    Xing, Sheng
    Cai, Shubin
    Xiao, Zhijiao
    Ming, Zhong
    SMART COMPUTING AND COMMUNICATION, SMARTCOM 2016, 2017, 10135 : 183 - 193
  • [4] Efficient Cloud Workflow Scheduling with Inverted Ant Colony Optimization Algorithm
    Ding, Hongwei
    Zhang, Ying
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (10) : 913 - 921
  • [5] Efficient Task Scheduling in Cloud Computing using Multi-objective Hybrid Ant Colony Optimization Algorithm for Energy Efficiency
    Zambuk, Fatima Umar
    Gital, Abdulsalam Ya'u
    Jiya, Mohammed
    Gari, Nahuru Ado Sabon
    Ja'afaru, Badamasi
    Muhammad, Aliyu
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2021, 12 (03) : 450 - 456
  • [6] An Improved Ant Colony Algorithm for New energy Industry Resource Allocation in Cloud Environment
    DU, Haoyang
    Chen, Junhui
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2023, 30 (01): : 153 - 157
  • [7] Hybrid ant genetic algorithm for efficient task scheduling in cloud data centers
    Ajmal, Muhammad Sohaib
    Iqbal, Zeshan
    Khan, Farrukh Zeeshan
    Ahmad, Muneer
    Ahmad, Iftikhar
    Gupta, Brij B.
    COMPUTERS & ELECTRICAL ENGINEERING, 2021, 95
  • [8] Using Ant Colony System to Consolidate VMs for Green Cloud Computing
    Farahnakian, Fahimeh
    Ashraf, Adnan
    Pahikkala, Tapio
    Liljeberg, Pasi
    Plosila, Juha
    Porres, Ivan
    Tenhunen, Hannu
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2015, 8 (02) : 187 - 198
  • [9] An Efficient Approach for Green Cloud Computing using Genetic Algorithm
    Kaur, Baljinder
    Kaur, Arvinder
    2015 1ST INTERNATIONAL CONFERENCE ON NEXT GENERATION COMPUTING TECHNOLOGIES (NGCT), 2015, : 10 - 15
  • [10] Efficient Energy Utilization in Cloud Fog Environment
    Hayat, Babur
    Ali, Muhammad Nauman
    Yousaf, Sheraz
    Mehmood, Mudassar
    Saleem, Hammad
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (04) : 617 - 623