A graphical deep learning technique-based VNF dependencies for multi resource requirements prediction in virtualized environments
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A graphical deep learning technique-based VNF dependencies for multi resource requirements prediction in virtualized environments
Authors
Keywords
-
Journal
COMPUTING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-10-14
DOI
10.1007/s00607-023-01225-2
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Intelligent resource sharing to enable quality of service for network clients: the trade-off between accuracy and complexity
- (2022) Luis Antonio L. F. da Costa et al. COMPUTING
- Quality of service provisioning in network function virtualization: a survey
- (2021) Seyedakbar Mostafavi et al. COMPUTING
- An efficient forecasting approach for resource utilization in cloud data center using CNN-LSTM model
- (2021) Soukaina Ouhame et al. NEURAL COMPUTING & APPLICATIONS
- Integrated deep learning method for workload and resource prediction in cloud systems
- (2020) Jing Bi et al. NEUROCOMPUTING
- A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment
- (2019) Yonghua Zhu et al. EURASIP Journal on Wireless Communications and Networking
- Dynamic Resource Prediction and Allocation for Cloud Data Center Using the Multiobjective Genetic Algorithm
- (2018) Fan-Hsun Tseng et al. IEEE Systems Journal
- An Efficient Deep Learning Model to Predict Cloud Workload for Industry Informatics
- (2018) Qingchen Zhang et al. IEEE Transactions on Industrial Informatics
- Deep-Learning-Assisted Network Orchestration for On-Demand and Cost-Effective vNF Service Chaining in Inter-DC Elastic Optical Networks
- (2018) Baojia Li et al. Journal of Optical Communications and Networking
- DeepTP: An End-to-End Neural Network for Mobile Cellular Traffic Prediction
- (2018) Jie Feng et al. IEEE NETWORK
- Survey on prediction models of applications for resources provisioning in cloud
- (2017) Maryam Amiri et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Host load prediction with long short-term memory in cloud computing
- (2017) Binbin Song et al. JOURNAL OF SUPERCOMPUTING
- LSTM: A Search Space Odyssey
- (2017) Klaus Greff et al. IEEE Transactions on Neural Networks and Learning Systems
- Topology-Aware Prediction of Virtual Network Function Resource Requirements
- (2017) Rashid Mijumbi et al. IEEE Transactions on Network and Service Management
- Topology-Aware Prediction of Virtual Network Function Resource Requirements
- (2017) Rashid Mijumbi et al. IEEE Transactions on Network and Service Management
- Management and orchestration challenges in network functions virtualization
- (2016) Rashid Mijumbi et al. IEEE COMMUNICATIONS MAGAZINE
- Energy-aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model
- (2016) Fahimeh Farahnakian et al. IEEE Transactions on Cloud Computing
- An adaptive fuzzy threshold-based approach for energy and performance efficient consolidation of virtual machines
- (2015) Leili Salimian et al. COMPUTING
- Cloud resource management: A survey on forecasting and profiling models
- (2015) Rafael Weingärtner et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS
- (2015) Rodrigo N. Calheiros et al. IEEE Transactions on Cloud Computing
- How to adapt applications for the Cloud environment
- (2012) Vasilios Andrikopoulos et al. COMPUTING
- The Graph Neural Network Model
- (2008) F. Scarselli et al. IEEE TRANSACTIONS ON NEURAL NETWORKS
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started