Ferdosian et al., 2023 - Google Patents
Autonomous intelligent VNF profiling for future intelligent network orchestrationFerdosian et al., 2023
View PDF- Document ID
- 2493337933317384984
- Author
- Ferdosian N
- Moazzeni S
- Jaisudthi P
- Ren Y
- Agrawal H
- Simeonidou D
- Nejabati R
- Publication year
- Publication venue
- IEEE Transactions on Machine Learning in Communications and Networking
External Links
Snippet
In this article, we propose a profile-based data-driven analysis framework to extract and analyze the characteristics and behavior of virtualized network functions (VNFs) in virtualized networks from the resource and performance perspective. This framework …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/50—Network service management, i.e. ensuring proper service fulfillment according to an agreement or contract between two parties, e.g. between an IT-provider and a customer
- H04L41/5003—Managing service level agreement [SLA] or interaction between SLA and quality of service [QoS]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/14—Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning
- H04L41/147—Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning for prediction of network behaviour
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/08—Configuration management of network or network elements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/22—Arrangements for maintenance or administration or management of packet switching networks using GUI [Graphical User Interface]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing packet switching networks
- H04L43/08—Monitoring based on specific metrics
- H04L43/0876—Network utilization
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Fernández Maimó et al. | Dynamic management of a deep learning-based anomaly detection system for 5G networks | |
EP3951598B1 (en) | Methods and systems for detecting anomalies in cloud services based on mining time-evolving graphs | |
US11489732B2 (en) | Classification and relationship correlation learning engine for the automated management of complex and distributed networks | |
US11461685B2 (en) | Determining performance in a distributed application or system | |
Ilager et al. | Artificial intelligence (ai)-centric management of resources in modern distributed computing systems | |
Zafeiropoulos et al. | Benchmarking and profiling 5G verticals' applications: an industrial IoT use case | |
Terra et al. | Explainability methods for identifying root-cause of SLA violation prediction in 5G network | |
Bendriss et al. | AI for SLA management in programmable networks | |
Fiandrino et al. | Toward native explainable and robust AI in 6G networks: Current state, challenges and road ahead | |
Magableh et al. | A self healing microservices architecture: A case study in docker swarm cluster | |
Moazzeni et al. | A novel autonomous profiling method for the next-generation nfv orchestrators | |
Yahia et al. | CogNitive 5G networks: Comprehensive operator use cases with machine learning for management operations | |
Bendriss et al. | Forecasting and anticipating SLO breaches in programmable networks | |
Jahromi et al. | An application awareness framework based on SDN and machine learning: Defining the roadmap and challenges | |
Aceto et al. | AI-powered Internet Traffic Classification: Past, Present, and Future | |
Ferdosian et al. | Autonomous intelligent VNF profiling for future intelligent network orchestration | |
da Silva et al. | Online machine learning for auto-scaling in the edge computing | |
Ruiz-Villafranca et al. | A MEC-IIoT intelligent threat detector based on machine learning boosted tree algorithms | |
Paramasivam et al. | Cor-ENTC: correlation with ensembled approach for network traffic classification using SDN technology for future networks | |
Zhang et al. | Service workload patterns for Qos-driven cloud resource management | |
Mozo et al. | Scalable prediction of service-level events in datacenter infrastructure using deep neural networks | |
de la Puerta et al. | Network traffic analysis for android malware detection | |
Leyva-Pupo et al. | An intelligent scheduling for 5G user plane function placement and chaining reconfiguration | |
Boukhtouta et al. | Cloud native applications profiling using a graph neural networks approach | |
Khan et al. | Machine Learning-Based Application for Predicting 5G/B5G Service |