On the public citation graph
An Approach for Dynamic Scaling of Resources in Enterprise Cloud
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.future.2010.10.016openalex-snapshot
Adaptive resource provisioning for read intensive multi-tier applications in the cloud
inferredcites →https://doi.org/10.1109/cecnet.2012.6201461openalex-snapshot
Resource prediction based on double exponential smoothing in cloud computing
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.2012.103openalex-snapshot
A Performance Study on the VM Startup Time in the Cloud
inferredcites →https://doi.org/10.1109/cloud.2012.12openalex-snapshot
SmartScale: Automatic Application Scaling in Enterprise Clouds
inferredcites →https://doi.org/10.1109/grid.2010.5697966openalex-snapshot
Cloud auto-scaling with deadline and budget constraints
inferredcites →https://doi.org/10.1109/mascots.2011.47openalex-snapshot
A Distributed Self-Learning Approach for Elastic Provisioning of Virtualized Cloud Resources
inferredcites →https://doi.org/10.1109/svm.2011.6096465openalex-snapshot
Elastic VM for rapid and optimum virtualized resources' allocation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-97-4895-2_20openalex-snapshot
Optimizing Cloud Computing Resource Allocation Through Intelligent Strategies
inferred← citeshttps://doi.org/10.1109/ants.2018.8710165openalex-snapshot
Large Data Transfer Predictability and Forecasting using Application-Aware SDN
inferred← citeshttps://doi.org/10.1109/glocom.2015.7417181openalex-snapshot
Efficient Auto-Scaling Approach in the Telco Cloud Using Self-Learning Algorithm
inferred← citeshttps://doi.org/10.1109/glocomw.2015.7414021openalex-snapshot
An Adaptive Score Model for Effective Bandwidth Prediction and Provisioning in the Cloud Network
inferred← citeshttps://doi.org/10.1109/icc.2018.8422788openalex-snapshot
Auto-Scaling VNFs Using Machine Learning to Improve QoS and Reduce Cost
inferred← citeshttps://doi.org/10.1109/icccbda.2019.8725620openalex-snapshot
Joint Optimization of Resource Allocation and Service Performance in vEPC Using Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/icece59822.2023.10462269openalex-snapshot
Auto-Scaling Service Strategy for Distributed Satellite System
inferred← citeshttps://doi.org/10.1109/times-icon.2018.8621761openalex-snapshot
Dynamic SAR for Efficient Container Auto-Scaling Based on Network Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tnsm.2020.2995900openalex-snapshot
Auto-Scaling Network Service Chains Using Machine Learning and Negotiation Game
inferred← citeshttps://doi.org/10.1145/3377458.3377468openalex-snapshot
Optimized Service Function Path Scaling in SDN/NFV Networks
inferred← citeshttps://doi.org/10.1364/jocn.413188openalex-snapshot
QoS-aware data center network reconfiguration method based on deep reinforcement learning
inferred← citeshttps://doi.org/10.14569/ijacsa.2016.071113openalex-snapshot
Using Multiple Seasonal Holt-Winters Exponential Smoothing to Predict Cloud Resource Provisioning
inferred← citeshttps://doi.org/10.14569/ijacsa.2016.071236openalex-snapshot
Automatic Cloud Resource Scaling Algorithm based on Long Short-Term Memory Recurrent Neural Network
inferred← citeshttps://doi.org/10.20535/1560-8956.42.2023.278925openalex-snapshot
Проактивне автоматичне масштабування вверх для Kuberneters
inferred← citeshttps://doi.org/10.22215/etd/2016-11510openalex-snapshot
A Self-Adaptive Auto-Scaling System in Infrastructure-as-a-Service Layer of Cloud Computing
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