Abstract
In the distributed computing environments, user-submitted job details such as the expected job completion time estimates are prone to inaccuracies. These inaccurate details force the system to under-perform due to ineffective allocation of processing resources. Addressing the concerns that crop-up due to the presence of these ill-defined user-provided parameters is an important task, which is very much required to get the jobs executed using optimal number of resources. At the same time, studying the ways of deriving accurate job runtimes benefits us in attaining improved load balancing results. The work proposed in the present study tries to apply an enhanced user priority model, taking into account the penalty and aging of job requests. It also combines least load variance method to improve the load balancing across grid resources. Simulation results obtained using realistic workloads bring forward the load balance efficiency of the studied scheme. This also confirms that to consider and infer of improved modeling of these user priority provides gains that outperform the methods void of it. The results attained are equated and contrasted with prevailing algorithms in terms of parameters like response time, wait time, tardiness, and average resource utilization in high-performance computing environments.
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Hijab, M., Damodaram, A. (2021). Efficient Load Balancing in Distributed Computing Environments with Enhanced User Priority Modeling. In: Satapathy, S.C., Bhateja, V., Favorskaya, M.N., Adilakshmi, T. (eds) Smart Computing Techniques and Applications. Smart Innovation, Systems and Technologies, vol 225. Springer, Singapore. https://doi.org/10.1007/978-981-16-0878-0_70
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DOI: https://doi.org/10.1007/978-981-16-0878-0_70
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