Workload Prediction and Grid Efficiency Case Study

Workload Prediction and Grid Efficiency Case Study - YellowDog

Global Risk and Analytics Company used YellowDog for improved workload prediction and grid efficiency. This helped the business to drive revenue and lower ...

A Case Study on Grid Performance Modeling - Clemson OPEN

The case study demon- strates that the simulation model can be used to predict the grid system performance given a workload forecast. The model is also used ...

A Case Study on Grid Performance Modeling - Clemson OPEN

The case study demonstrates that the simulation model can be used to predict the grid system performance given a workload forecast. The model is also used ...

(PDF) A case study on grid performance modeling - ResearchGate

The case study demon-strates that the simulation model can be used to predict the grid system performance given a workload forecast. The model is also used ...

A Self-Optimized Generic Workload Prediction Framework for Cloud ...

3) A case study to demonstrate that the highly-accurate predictions ... The. Case for Evaluating MapReduce Performance Using Workload Suites. In IEEE ...

A review of examples and opportunities to quantify the grid reliability ...

The paper uses case studies to extract best practices in quantifying reliability and resilience benefits of energy efficiency. Examples in this brief focus on ...

A Guide to Case Studies of Grid Enhancing Technologies

Install non-contact EMF sensors to monitor three transmission lines for 12 months to determine market efficiency gains with DLR and planning with conductor ...

Time series-based workload prediction using the statistical hybrid ...

... analysis to screen performance indicators as multidimensional ... Adaptive workload prediction of grid performance in confidence windows.

Workload forecasting and energy state estimation in cloud data ...

To understand the intricacies of power consumption of a host, we did a case study on workload traces. ... In terms of energy efficiency, both cases such as ...

A new temporal locality-based workload prediction approach for ...

Workload forecasting techniques have been proposed in order to improve capacity planning, ensure efficient management of resources and, hence, maintain SLA ...

Deep learning-driven hybrid model for short-term load forecasting ...

... grid-connected oscillation risk prediction ... Table 4 Model efficiency comparison in the case of AEMO Load dataset and NYISO dataset.

Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study

Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and ...

Transforming grid operations with accurate short-term energy ... - DNV

... grid performance and reliability. Emerging use cases for short-term energy forecasting for grid operations ... Case study: During the ...

Workload Time Series Cumulative Prediction Mechanism for Cloud ...

... Case Study. In: Proceedings of the ... study on CPU load predictions in a computational grid using artificial neural network algorithms.

Electric grid balancing through lowcost workload migration

Exploring mapreduce efficiency with highly-distributed data. In ... Distributed Grid Storage by Ordinary House Heating Variations: A Swiss Case Study.

Microservice-Oriented Workload Prediction Using Deep Learning

Aim: This research aims to study how an efficient workload prediction ... Höst, “Guidelines for conducting and reporting case study research in software ...

Grid Application Performance Prediction: a Case Study in BROADEN

The BROADEN (Business Resource Optimisation for Aftermarket and Design on Engineering Networks) project aims to build a Rolls-Royce Grid as ...

Cloud Workload Prediction by Means of Simulations - ResearchGate

invisible processes, the so-called background workload. is paper aims at studying performance issues related to the –. unknown – background load and proposes a ...

A novel approach to workload prediction using attention-based ...

... Performance Computing, Networking, Storage and Analysis. ... Using Markov chain analysis to study dynamic behaviour in large-scale grid systems.

Dynamic workload prediction and distribution in numerical modeling ...

... grid is the most efficient for all platforms studied in this article. In the case of the 2D map, load balancing is based on the fact that ...