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Workload Predicting-Based Automatic Scaling in Service Clouds

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/spe.995openalex-snapshot
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
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Simple Linear Regression
inferredcites →https://doi.org/10.1109/ccgrid.2012.52openalex-snapshot
Lightweight Resource Scaling for Cloud Applications
inferredcites →https://doi.org/10.1109/cloud.2011.42openalex-snapshot
Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting
inferredcites →https://doi.org/10.1109/cloud.2012.12openalex-snapshot
SmartScale: Automatic Application Scaling in Enterprise Clouds
inferredcites →https://doi.org/10.1109/cloud.2012.32openalex-snapshot
Automatic Resource Scaling Based on Application Service Requirements
inferredcites →https://doi.org/10.1109/cloud.2012.82openalex-snapshot
An Availability-Aware Approach to Resource Placement of Dynamic Scaling in Clouds
inferredcites →https://doi.org/10.1109/cnsm.2010.5691343openalex-snapshot
PRESS: PRedictive Elastic ReSource Scaling for cloud systems
inferredcites →https://doi.org/10.1109/ucc.2011.66openalex-snapshot
Load Prediction and Hot Spot Detection Models for Autonomic Cloud Computing
inferredcites →https://doi.org/10.1145/233008.233034openalex-snapshot
Web server workload characterization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Workload and Resource Aware Proactive Auto-scaler for PaaS Cloud
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CloudInsight: Utilizing a Council of Experts to Predict Future Cloud Application Workloads
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Proactive Container Auto-scaling for Cloud Native Machine Learning Services
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Adaptive workload prediction for proactive auto scaling in PaaS systems
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RPTCN: Resource Prediction for High-dynamic Workloads in Clouds based on Deep Learning
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A Literature Review and Taxonomy on Workload Prediction in Cloud Data Center
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Towards Efficient Automatic Scaling and Adaptive Cost-Optimized eHealth Services in Cloud
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Towards Efficient Automatic Scaling and Adaptive Cost-Optimized eHealth Services in Cloud
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Requests Prediction in Cloud with a Cyclic Window Learning Algorithm
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Cooperative dynamic eHealth service placement in Mobile Cloud Computing
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