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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      07 April 2023, Volume 38 Issue 2   
    Article

    A CENTRALIZED CLUSTER BASED DYNAMIC LOAD BALANCING FRAMEWORK USING TASK SCHEDULING IN CLOUD COMPUTING ENVIRONMENT
    Ajay Jangra1, Neeraj Mangla2
    Journal of Data Acquisition and Processing, 2023, 38 (2): 682-702 . 

    Abstract

    Cloud computing is an influencing technology that emphasis on internet-oriented development and computing capabilities of machines. Factors like scalability, adaptability, availability, pay for use scheme, virtualization and data handling within infinite space make it as a good option to be adopted by customers. With all these benefits, cloud computing has intended several trends in the area of computing and there are still some challenges that users face and one of the most important is load balancing. In this paper, centralized load balancing algorithm has been proposed that dynamically balance the load and ensures overall performance of the system. It aims to serve both end users and service providers profitably by managing data efficiently and focus on achieving high resource utilization, reduced job rejections, improved computational capabilities and building a fault tolerant system by creating backups. The results of cluster-oriented load balancing algorithm show reduction in response time, communication overhead and improved processing time. The experimental results thus obtained are presented with a detailed discussion and a comparative analysis may be carried out for checking the merit of newly proposed idea.

    Keyword

    Cloud computing, load balancing, virtual machine, scheduling, optimization, response time, resource utilization, dynamic clustering.


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ISSN 1004-9037

         

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