Deep Reinforcement Learning for Workload Prediction in Federated Cloud Environments [PDF]
Sensors, 2023 The Federated Cloud Computing (FCC) paradigm provides scalability advantages to Cloud Service Providers (CSP) in preserving their Service Level Agreement (SLA) as opposed to single Data Centers (DC).
Zaakki Ahamed +5 more
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Tr-Predictior: An Ensemble Transfer Learning Model for Small-Sample Cloud Workload Prediction [PDF]
Entropy, 2022 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 outliers make accurate ...
Chunhong Liu +4 more
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Dynamic machine learning approach for workload prediction in cloud environments [PDF]
Scientific ReportsContainers, as a lightweight technology for virtualizing applications, have recently revolutionized the management of cloud applications. Containers can be scaled up or down rapidly and easily depending on the workload. Predicting workload is crucial for
Mona Nashaat +3 more
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Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives
Tsinghua Science and TechnologyWorkload prediction is critical in enabling proactive resource management of cloud applications. Accurate workload prediction is valuable for cloud users and providers as it can effectively guide many practices, such as performance assurance, cost ...
Binbin Feng, Zhijun Ding
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Structured Prediction Method for Small Sample Workload Sequences [PDF]
Jisuanji kexue yu tansuo, 2022 Accurate workload prediction is the key to realize elastic resource management of cloud platform. Aiming at the problem that a large number of tasks with short running time achieve prediction in the cloud platform, which leads to the lack of training ...
LIU Chunhong, ZHANG Zhihua, JIAO Jie, CHENG Bo
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Three-Way Ensemble Prediction for Workload in the Data Center
IEEE Access, 2022 Accurate prediction of data center workload, an important technology of cloud computing, is particular in improving resource utilization and reducing energy consumption.
Rui Shi, Chunmao Jiang
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Cloud Workload Prediction and Generation Models [PDF]
2017 29th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2017 Cloud computing allows for elasticity as users can dynamically benefit from new virtual resources when their workload increases. Such a feature requires highly reactive resource provisioning mechanisms. In this paper, we propose two new workload prediction models, based on constraint programming and neural networks, that can be used for dynamic ...
Madi Wamba, Gilles +4 more
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CANFIS: A Chaos Adaptive Neural Fuzzy Inference System for Workload Prediction in the Cloud
IEEE Access, 2022 As cloud-based applications become increasingly solicited by companies and individuals, the competition between cloud providers that offer cloud services keeps increasing.
Zohra Amekraz, Moulay Youssef Hadi
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Real-Time Team Performance and Workload Prediction From Voice Communications
IEEE Access, 2022 Automatic prediction of team performance and workload plays a crucial role in team selection, training, evaluation, and re-training processes. This study investigated the potential of using voice analysis of team-based communication for predicting team ...
Catherine Sandoval +4 more
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Cloud Workload and Data Center Analytical Modeling and Optimization Using Deep Machine Learning
Network, 2022 Predicting workload demands can help to achieve elastic scaling by optimizing data center configuration, such that increasing/decreasing data center resources provides an accurate and efficient configuration.
Tariq Daradkeh, Anjali Agarwal
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