ENVI: Elastic resource flexing for Network function Virtualization
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Summary
The preliminary results show that using a combination of features to train a neural network model is a promising approach for scaling detection, and an NFV resource flexing system, ENVI, is proposed.
- Type
- article
- Published
- 2017-01-01
- Cited by
- 38
- References
- 24
- OpenAlex
- https://openalex.org/W2740152917
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:28185532
Keywords
Virtualization, Computer science, Network Functions Virtualization, Function (biology), Computer network
References
- MDP and Machine Learning-Based Cost-Optimization of Dynamic Resource Allocation for Network Function Virtualization
- Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems
- Near optimal placement of virtual network functions
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- On orchestrating virtual network functions
- Sandpiper: Black-box and gray-box resource management for virtual machines
- Opprentice: Towards Practical and Automatic Anomaly Detection Through Machine Learning
- The dynamic placement of virtual network functions
- VNF-P: A model for efficient placement of virtualized network functions
- E2: a framework for NFV applications
- Piecing together the NFV provisioning puzzle: Efficient placement and chaining of virtual network functions
- PRESS: PRedictive Elastic ReSource Scaling for cloud systems
- CloudScale: elastic resource scaling for multi-tenant cloud systems
- Efficient coflow scheduling with Varys
- Elastic virtual network function placement
- NFV-VITAL: A framework for characterizing the performance of virtual network functions
- Online VNF Scaling in Datacenters
- Stratos: A Network-Aware Orchestration Layer for Middleboxes in the Cloud
- Taking the Blame Game out of Data Centers Operations with NetPoirot
- An NFV Orchestration Framework for Interference-Free Policy Enforcement
Cited by
- Data-driven resource flexing for network functions visualization
- Improving Energy Efficiency in NFV Clouds with Machine Learning
- Traffic-aware Threshold Adjustment for NFV Scaling using DDPG
- Dynamic CPU frequency scaling using machine learning for NFV applications.
- A Black-Box Approach for Estimating Utilization of Polled IO Network Functions
- MAPLE: A Machine Learning Approach for Efficient Placement and Adjustment of Virtual Network Functions
- Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing
- Online VNF chain deployment on resource-limited edges by exploiting peer edge devices
- NFV Data Centers: A Systematic Review
- GSDM: Graph-Based Scaling Detection Model in Network Function Virtualization
- Fine-Grained Cloud Resource Provisioning for Virtual Network Function
- A Performance Modelling Approach for SLA-Aware Resource Recommendation in Cloud Native Network Functions
- Dynamic K-Means Clustering of Workload and Cloud Resource Configuration for Cloud Elastic Model
- AI-Driven Provisioning in the 5G Core
- Service function chain composition and placement using grammar‐based genetic algorithm
- ML-Driven Provisioning and Management of Vertical Services in Automated Cellular Networks
- Review on identification analysis technology of Internet of things
- SFC security survey: Addressing security challenges and threats in Service Function Chaining
- Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks
- V2N Service Scaling with Deep Reinforcement Learning
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