Abstract
In grid computing environment, job requirements are so large scale and complex that we need the allocating mechanism to manage the resources and schedule the job. So that, a well-allocated mechanism is needed to enhance the grid resources be more useful and scalable. In this paper, we propose a resource performance analysis model for grid resources under the grid computing environment. By this model, we can analyze the information about CPU usage, memory usage by fuzzy inferences, and number of running jobs of each grid resource node to achieve load-balancing and make the plans and allocations of the resources of collaborated nodes optimize. There are three modules in the proposed model, namely, resource detecting module, resource estimator module, and resource assignment module. According to the result of experiment, the mechanism can achieve the best resources allocation, and enhance the overall grid computing performance.
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Lee, HM., Chung, CH., Lee, TY., Su, JS. (2009). Fuzzy Performance Analysis Model Based on Grid Environment. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_29
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DOI: https://doi.org/10.1007/978-3-540-92814-0_29
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