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Time series-based workload prediction using the statistical hybrid model for the cloud environment
Resource management is addressed using infrastructure as a service. On demand, the
resource management module effectively manages available resources. Resource …
resource management module effectively manages available resources. Resource …
Is machine learning necessary for cloud resource usage forecasting?
Robust forecasts of future resource usage in cloud computing environments enable high
efficiency in resource management solutions, such as autoscaling and overcommitment …
efficiency in resource management solutions, such as autoscaling and overcommitment …
Evogwp: Predicting long-term changes in cloud workloads using deep graph-evolution learning
J Li, J Yao, D **-2/publication/384094401_WorkloadDiff_Conditional_Denoising_Diffusion_Probabilistic_Models_for_Cloud_Workload_Prediction/links/66fa1976f599e0392faacb5f/WorkloadDiff-Conditional-Denoising-Diffusion-Probabilistic-Models-for-Cloud-Workload-Prediction.pdf" data-clk="hl=sr&sa=T&oi=gga&ct=gga&cd=8&d=1976522084160645024&ei=ze7BZ_vRAZ-_6rQPvv_vqQc" data-clk-atid="oCccDV0EbhsJ" target="_blank">[PDF] researchgate.net
WorkloadDiff: Conditional Denoising Diffusion Probabilistic Models for Cloud Workload Prediction
W Zheng, Z Chen, K Zheng, W Zheng… - … on Cloud Computing, 2024 - ieeexplore.ieee.org
Accurate workload forecasting plays a crucial role in optimizing resource allocation,
enhancing performance, and reducing energy consumption in cloud data centers. Deep …
enhancing performance, and reducing energy consumption in cloud data centers. Deep …
En-beats: A novel ensemble learning-based method for multiple resource predictions in cloud
Cloud computing has become an important driving force in the economy and the
fundamental facility for digitization transformation. Due to its rapid development and …
fundamental facility for digitization transformation. Due to its rapid development and …