@article{MAKHILLJEAS2019142218624,
    title = {Weighted Optimization Load Balancing Algorithm in Virtualization},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {22},
    pages = {8386-8402},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.8386.8402},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.8386.8402},
    author = {Neha,Ajay and},
    keywords = {energy-consumption,cloud
simulator-cloud analyst,distributed cloud computing,virtual machines,load harmonizing,Virtualization},
    abstract = {Today, there is trend for distributed cloud computing to be followed as new worldwide pattern of
processing. It is an advanced style of utilizing the power of internet to offer assets remotely. However,
distributed cloud computing has many difficulties, for example, poor asset usage which has a deep effect on
the execution of distributed computing. Such issues emerged because of the tremendous quantity of data.
Therefore, the requirement intended for productive and capable distributed cloud computing load harmonizing
calculations is a standout amongst the most imperative issues around to enhance the execution of cloud
processing. Many investigators proposed numerous load balancing and process programming algorithms in
the calculation of cloud but there still remains incompetency within the hardware functioning and lack of load
balancing. Thus, this study endorses a set of rules for load balancing to enhance the overall performance and
effectiveness in diverse cloud computing environment. We advocate a fusion set of rules based on priority and
batch rules, taking advantages of weighted optimization algorithm and equally spread current execution
algorithms. The algorithm reflects the current resource records and the capability issue of central processing
unit to acquire the targets. The fused algorithm has been evaluated and are compared with different algorithms
using Cloud Analyst Simulator. The results demonstrated progress in migration time, reaction time and
scalability, availability and reliability of resources with energy-consumption and throughput via. considering
the modern-day aid records and the central processing unit potential factor in comparison with different
algorithms.}
    }