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An Integrated Predictive Impact-Enhanced Process Mining Framework for Strategic Oncology Workflow Optimization: Case Study in Iran. [PDF]
Bioengineering (Basel)Salehi M +3 more
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Workload forecasting framework for applications in cloud
Proceedings of 2014 International Conference on Cloud Computing and Internet of Things, 2014With the development of cloud computing technics, an increasing number of applications prefer to be deployed in cloud. Load balancing becomes the key technicfor cloud provider to control the resources and cost. But using load balancing with real time data cannot react in time towards workload peak or valley.
Shuang Jiang, Haopeng Chen, Fei Hu
exaly +2 more sources
Phase-Aware CPU Workload Forecasting
Lecture Notes in Computer Science, 2022Andreas Gerstlauer
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Workload Consumption Metric Forecasting
2023The success of an autonomous database largely depends on its ability to predict the future. With the knowledge of what is going to happen in the future, an autonomous database can choose proper optimization strategies at the right time. This helps an autonomous database to be proactive rather than being reactive.
Naveen Sankaran +3 more
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Adaptive Workload Forecasting in Cloud Data Centers
Journal of Grid Computing, 2019Forecasting on different levels of the management system of a cloud data center has received increased attention due to its significant impact on the cloud services quality. Making accurate forecasts, however, is challenging due to the non-stationary workload and intrinsic complexity of the management system of a cloud data center.
Eduard Zharikov +2 more
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2017
This chapter gives a summary of the state-of-the-art approaches from different research fields that can be applied to continuously forecast future developments of time series data streams. More specifically, the input time series data contains continuously monitored metrics that quantify the amount of incoming workload units to a self-aware system.
Herbst, Nikolas +6 more
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This chapter gives a summary of the state-of-the-art approaches from different research fields that can be applied to continuously forecast future developments of time series data streams. More specifically, the input time series data contains continuously monitored metrics that quantify the amount of incoming workload units to a self-aware system.
Herbst, Nikolas +6 more
openaire +2 more sources
Forecasting Contracting Workload
1989Abstract : This study explored the possibility of forecasting DLA contracting workload from indicators of Service activity. The premise of this analysis is that DLA's contracting workload is somehow related to Service activity -- an increase in Service activity will lead to a corresponding increase in DLA workload.
null Thomas L. +2 more
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Scale-Space Filtering for Workload Analysis and Forecast
2013 IEEE Sixth International Conference on Cloud Computing, 2013Dynamic resource provisioning poses a major challenge for infrastructure providers because it is necessary to both forecast resource consumption and react to recent surges on demand for maintaining a tradeoff between quality of service and cost. However, approaches to workload analysis and forecast are affected due to noise in observed data, specially ...
Gustavo A. C. Santos +4 more
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