Abstract
Cloud computing is entailed for elasticity, scalability, and accuracy for the multi-sharing systems; predicting resource for the multi-sharing system in an existing system is not accurate which leads to under or over-provisioning of resources and increases higher cost for on-demand resources. In this paper, we develop a prediction model called Multiple Output Prediction for Scalability and Accuracy (MOPSA). The key characteristic of this model is to improve accuracy of prediction of resources with multiple outputs in multi-sharing system by using gradient descent method. Experimental results exhibit that the proposed model improves the prediction accuracy of resources and provides scalability in multi-sharing system for minimizing cost by reducing number of on-demand resources.
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Dhanalakshmi, B.K., Srikantaiah, K.C., Venugopal, K.R. (2020). MOPSA: Multiple Output Prediction for Scalability and Accuracy. In: Agarwal, S., Verma, S., Agrawal, D. (eds) Machine Intelligence and Signal Processing. MISP 2019. Advances in Intelligent Systems and Computing, vol 1085. Springer, Singapore. https://doi.org/10.1007/978-981-15-1366-4_29
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DOI: https://doi.org/10.1007/978-981-15-1366-4_29
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