Abstract
A cloud computing system consists of physical resources for processing large-scale tasks. With a recent trend of rapidly growing data, a cloud computing system needs a processing method to process a large-scale task in a physical resource. Generally, a physical resource divides a requested large-scale task to several tasks. And a processing time of each divided task varies with two factors which are processing efficiency of each resource and distance between resources. Although a resource completes a task, the resource is standing by until all divided tasks are completed. When all resources complete a large-scale task, each resource can start to process a next task. In this paper, we propose a Fuzzy-based Resource Reallocation Scheduling Model (FRRSM). Using fuzzy rule, FRRSM reallocates an uncompleted task to with a resource in considering efficiency and distance factors of the resource. FRRSM is an efficient method for processing a large-scale task or multiple large-scale tasks.
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Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2002751) and this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2013R1A1A3A04007527).
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Kim, J., Kim, T., Park, M., Han, Y., Lee, J. (2014). Fuzzy-Based Resource Reallocation Scheduling Model in Cloud Computing. In: Park, J., Zomaya, A., Jeong, HY., Obaidat, M. (eds) Frontier and Innovation in Future Computing and Communications. Lecture Notes in Electrical Engineering, vol 301. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8798-7_6
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DOI: https://doi.org/10.1007/978-94-017-8798-7_6
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