2015 · 26 citations · 23 references
ComputingComputer ScienceComputer SystemsForecastingMachine LearningPredictive AnalyticsCloud ForecastingCloud Resource ManagementCompute Resource ManagementEnergy-efficient Cloud ComputingLoad ForecastingResource ForecastingCloud Resource ForecastingCloud Usage ForecastingElastic Resource AllocationMachine Learning Forecasting ModelsMachine Learning-based ForecastingPrediction Model DevelopmentResource Consumption ForecastingResource Demand Modeling
Data centre prediction models can be used to forecast future loads for a given centre in terms of CPU, memory, VM requests, and other parameters. An effective and efficient model can not only be used to optimize resource allocation, but can also be used as part of a strategy to conserve energy, improve performance and increase profits for both clients and service providers. In this paper, we have developed a prediction model, which combines k-means clustering techniques and Extreme Learning Machines (ELMs). We have shown the effectiveness of our proposed model by using it to estimate future VM requests in a data centre based on its historical usage. We have tested our model on real Google traces that feature over 25 million tasks collected over a 29-day time period. Experimental results presented show that our proposed system outperforms other models reported in the literature.
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Extreme learning machine: Theory and applications
Guang-Bin Huang, Qinyu Zhu, Chee‐Kheong Siew · Neurocomputing · 2006 · 13.2K citations
Prediction of cloud data center networks loads using stochastic and neural models
John J. Prevost, Kranthimanoj Nagothu, Brian Kelley et al. · 2011 · 171 citations