A Study on Load Balancing in Cloud Computing Environment Using Evolutionary and Swarm Based Algorithms

被引:0
|
作者
Rana, Madhurima [1 ]
Bilgaiyan, Saurabh [1 ]
Kar, Utsav [1 ]
机构
[1] KIIT Univ, Sch Comp Engn, Bhubaneswar, Odisha, India
关键词
Cloud computing; load balancing; evolutionary algorithms; swarm based algorithms; quality of services (QoS); distributed computing; genetic algorithm (GA); particle swarm optimization (PSO); ant colony optimization (ACO); artificial bee colony algorithm (ABC);
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
Literature meaning of cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service, means users pay only for those services which are used by him according to their access times. The data processing and storage amount is increasing quickly day by day in cloud environment. This leads to an uneven distribution of overall work on cloud resources. So a proper balance of overall load over the available resources is a major issue in cloud computing paradigm. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. It also minimizes the time and cost involved in such big computing models. Load balancing and better resource utilization is provided by many existing algorithms. To overcome load balancing problem this paper provides a summary of evolutionary and swarm based algorithms which will help to overcome such problem in different environment of cloud.
引用
收藏
页码:245 / 250
页数:6
相关论文
共 50 条
  • [1] An analysis of swarm intelligence based load balancing algorithms in a cloud computing environment
    Singhal, Uma
    Jain, Sanjeev
    International Journal of Hybrid Information Technology, 2015, 8 (01): : 249 - 256
  • [2] Load Balancing in Cloud Computing Environment Based on An Improved Particle Swarm Optimization
    Pan, Kai
    Chen, Jiaqi
    PROCEEDINGS OF 2015 6TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE, 2015, : 595 - 598
  • [3] A Survey of Swarm Intelligence Based Load Balancing Techniques in Cloud Computing Environment
    Elmagzoub, M. A.
    Syed, Darakhshan
    Shaikh, Asadullah
    Islam, Noman
    Alghamdi, Abdullah
    Rizwan, Syed
    ELECTRONICS, 2021, 10 (21)
  • [4] Study of load balancing algorithms for Cloud Computing
    Handur, Vidya S.
    Belkar, Supriya
    Deshpande, Santosh
    Marakumbi, Prakash R.
    PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON GREEN COMPUTING AND INTERNET OF THINGS (ICGCIOT 2018), 2018, : 173 - 176
  • [5] Performance Study of Some Dynamic Load Balancing Algorithms in Cloud Computing Environment
    Pattanaik, Priyadarashini Adyasha
    Roy, Sharmistha
    Pattnaik, Prasant Kumar
    2ND INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN) 2015, 2015, : 619 - 624
  • [6] A binary Bird Swarm Optimization based load balancing algorithm for cloud computing environment
    Mishra, Kaushik
    Majhi, Santosh Kumar
    OPEN COMPUTER SCIENCE, 2021, 11 (01) : 146 - 160
  • [7] Cloud Computing: Performance Analysis of Load Balancing Algorithms in Cloud Heterogeneous Environment
    Behal, Veerawali
    Kumar, Anil
    2014 5TH INTERNATIONAL CONFERENCE CONFLUENCE THE NEXT GENERATION INFORMATION TECHNOLOGY SUMMIT (CONFLUENCE), 2014, : 200 - 205
  • [8] Particle Swarm Optimization Based Load Balancing in Cloud Computing
    Acharya, Jigna
    Mehta, Manisha
    Saini, Baljit
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND ELECTRONICS SYSTEMS (ICCES), 2016, : 218 - 221
  • [9] A Comparative Study of Load Balancing Algorithms in a Cloud Environment
    Duggal, Ashmeet Kaur
    Dave, Meenu
    ADVANCES IN COMPUTING AND INTELLIGENT SYSTEMS, ICACM 2019, 2020, : 115 - 126
  • [10] Improved Cat Swarm Optimization Algorithm for Load Balancing in the Cloud Computing Environment
    Dou, Wang
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (07) : 1039 - 1046