An Accurate Ensemble Forecasting Approach for Highly Dynamic Cloud Workload With VMD and R-Transformer
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3004370
Abstract: To efficiently manage the cloud resources, improve the quality of service, and avoid the violations of Service-Level Agreement (SLA) agreements, it is very important to make accurate forecast for cloud workload. Prior works concerning cloud… read more here.
Keywords: highly dynamic; workload; ensemble forecasting; dynamic cloud ... See more keywords
TFEGRU: Time-Frequency Enhanced Gated Recurrent Unit With Attention for Cloud Workload Prediction
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DOI: 10.1109/tsc.2024.3517324
Abstract: Accurate prediction of cloud workload is crucial for effective resource allocation in cloud computing. However, due to the complexity and high dimensionality of workloads in the cloud environment, achieving precise workload prediction is a complex… read more here.
Keywords: workload; time frequency; workload prediction; prediction ... See more keywords
Tr-Predictior: An Ensemble Transfer Learning Model for Small-Sample Cloud Workload Prediction
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DOI: 10.3390/e24121770
Abstract: Accurate workload prediction plays a key role in intelligent scheduling decisions on cloud platforms. There are massive amounts of short-workload sequences in the cloud platform, and the small amount of data and the presence of… read more here.
Keywords: transfer; cloud workload; workload prediction; prediction ... See more keywords