@article{MAKHILLJEAS202015118862,
    title = {Experimental Model of Distributed Service Broker Policy Algorithm in
Cloud based Centralized and Distributed Data Center},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {15},
    number = {1},
    pages = {303-309},
    year = {2020},
    issn = {1816-949x},
    doi = {jeasci.2020.303.309},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2020.303.309},
    author = {Shivani,Mamta and},
    keywords = {Load balancing algorithms,DSBP,cloud analyst,workload,strategies,parameters},
    abstract = {In recent years cloud computing is a very advanced technique to distribute workload among all the
data centers and also balance those data center very smoothly. To improve the performance of data centers, load
balancing is used to distribute workload of arrival requests on data centers equally in the computing
environment. Load balancing has aim to minimize the response time among the users from different data
centers and also improve resource utilization by using cloud resources. Cloud based data centers always require
efficient load balancing strategies to reduce work load on Virtual Machines (VM). Researchers proposed
various load balancing algorithms to optimize different parameters. In this study, we are proposing a distributed
service broker policy algorithm which gives better result in centralized and distributed data center environment,
considers cloud resources for specific demands and also reduces work load on virtual machines. There are so
many VM load balancing algorithms have compared by using different data center broker policies. A cloud
analyst simulator, simulate these algorithms and then accurate result will be showed. Experimental results have
shown that our proposed Distributed Service Broker Policy (DSBP) algorithm in terms of execution time,
response time, throughput, cost as compared to existing round robin, active monitoring and throttled algorithms.
The experiments have been done using cloud analyst simulator and comparative analysis is evaluated based
on our proposed DSBP algorithm and the results are presented in detail.}
    }