A QoS and Energy aware Load Balancing and Resource Allocation Framework for IaaS Cloud Providers

被引:6
|
作者
Govindaraju, Yatheendraprakash [1 ]
Duran-Limon, Hector [1 ]
机构
[1] Univ Guadalajara, Ctr Univ Ciencias Econ Adm, Dept Sistemas Informac, Guadalajara, Jalisco, Mexico
关键词
Load Balancing; IaaS Cloud; Resource Allocation; Energy efficiency; Service Level Agreement;
D O I
10.1145/2996890.3007895
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 exponential growth of cloud based applications and the increased number of cloud users have given rise to new challenges for cloud service providers, especially for Infrastructure as a Service (IaaS) providers. This exponential growth of datacenters increases the energy consumption, along with its carbon footprints. Hence, better energy aware techniques not only reduce energy costs, but they are also helpful for reducing pollution in the environment. Some of the main challenges for cloud providers include increasing the resource utilization and minimizing energy consumption while maintaining the quality of service (QoS) offered to the users. There are many load balancing and resource allocation techniques proposed to handle these challenges. Out of these techniques, only a few consider QoS goals for IaaS service providers. However, none of these techniques includes service level agreement (SLA) parameters related to the Virtual Machine (VM) life cycle such as VM startup times. In this paper, we propose a novel approach to address this problem.
引用
收藏
页码:410 / 415
页数:6
相关论文
共 50 条
  • [31] Energy-aware and QoS-aware load balancing for HetNets powered by renewable energy
    Han, Qiaoni
    Yang, Bo
    Chen, Cailian
    Guan, Xinping
    COMPUTER NETWORKS, 2016, 94 : 250 - 262
  • [32] Communication Cost Aware Resource Efficient Load Balancing (CARE-LB) Framework for Cloud Datacenter
    Saxena D.
    Singh A.K.
    Recent Advances in Computer Science and Communications, 2021, 14 (09) : 2920 - 2933
  • [33] A QoS-Aware and Energy-Efficient Genetic Resource Allocation Algorithm for Cloud Data Centers
    Bakalla, Maha
    Al-Jami, Hadeel
    Kurdi, Heba
    Alsalamah, Shada
    2017 9TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT), 2017, : 244 - 249
  • [34] QRSF: QoS-aware resource scheduling framework in cloud computing
    Singh, Sukhpal
    Chana, Inderveer
    JOURNAL OF SUPERCOMPUTING, 2015, 71 (01): : 241 - 292
  • [35] QRSF: QoS-aware resource scheduling framework in cloud computing
    Sukhpal Singh
    Inderveer Chana
    The Journal of Supercomputing, 2015, 71 : 241 - 292
  • [36] A resource elasticity framework for QoS-aware execution of cloud applications
    Kaur, Pankaj Deep
    Chana, Inderveer
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 37 : 14 - 25
  • [37] Satellite QoS Routing Algorithm Based on Energy Aware and Load Balancing
    Hao, Linchun
    Ren, Pinyi
    Du, Qinghe
    2020 12TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2020, : 685 - 690
  • [38] An Enhanced Load Balancing Approach for Dynamic Resource Allocation in Cloud Environments
    Praveenchandar, J.
    Tamilarasi, A.
    WIRELESS PERSONAL COMMUNICATIONS, 2022, 122 (04) : 3757 - 3776
  • [39] Simulated-Annealing Load Balancing for Resource Allocation in Cloud Environments
    Fan, Zongqin
    Shen, Hong
    Wu, Yanbo
    Li, Yidong
    2013 INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED COMPUTING, APPLICATIONS AND TECHNOLOGIES (PDCAT), 2013, : 1 - 6
  • [40] Fusion-based Resource Allocation Algorithms for Load Balancing in Cloud
    Thota, Srinivas
    Kar, Dulal C.
    Katangur, Ajay K.
    PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), 2017, : 1554 - 1559