Parallel bi-state deep reinforcement learning approach for SFC placements and deployments
The SFC (service function chain) consists of virtual network function chains (VNFs) that
generate provisioned network services on demand. To properly structure a network service …
generate provisioned network services on demand. To properly structure a network service …
Online machine learning for auto-scaling in the edge computing
The evolution of edge computing devices has enabled machine intelligence techniques to
process data close to its producers (the sensors) and end-users. Although edge devices are …
process data close to its producers (the sensors) and end-users. Although edge devices are …
Horizontal auto-scaling in edge computing environment using online machine learning
TP da Silva, AFR Neto, TV Batista… - 2021 IEEE Intl Conf …, 2021 - ieeexplore.ieee.org
A major challenge in edge computing platforms for container-based applications is dealing
with the dynamic workload. At certain times, the resources previously allocated to a given …
with the dynamic workload. At certain times, the resources previously allocated to a given …
NFVLearn: A multi‐resource, long short‐term memory‐based virtual network function resource usage prediction architecture
Virtual resource load prediction in network function virtualization (NFV) is the subject of
intense research due to its crucial role in enabling proactive resource adaptation in dynamic …
intense research due to its crucial role in enabling proactive resource adaptation in dynamic …
An online ensemble method for auto-scaling NFV-based applications in the edge
The synergy of edge computing and Machine Learning (ML) holds immense potential for
revolutionizing Internet of Things (IoT) applications, particularly in scenarios characterized …
revolutionizing Internet of Things (IoT) applications, particularly in scenarios characterized …
Online machine learning for auto-scaling in the edge computing
The evolution of edge computing devices has enabled machine intelligence techniques to
process data close to its producers (the sensors) and end-users. Although edge devices are …
process data close to its producers (the sensors) and end-users. Although edge devices are …
Online Machine Learning for Auto-Scaling Processing Services in the Edge Computing Environment
TPP da Silva, AR Neto, TV Batista… - Available at SSRN …, 2022 - papers.ssrn.com
The evolution of edge computing devices has enabled machine intelligence techniques to
process data close to its producers (the sensors) and end-users. Although edge devices are …
process data close to its producers (the sensors) and end-users. Although edge devices are …
Multivariate outlier filtering for A-NFVLearn: an advanced deep VNF resource usage forecasting technique
Abstract Virtual Network Function Resource Adaptation (VNF-RA) aims at adequately
adapting Network Function Virtualization Infrastructure (NFVI) resources according to the …
adapting Network Function Virtualization Infrastructure (NFVI) resources according to the …
Input Feature Engineering for LSTM-Based VNF Resource Usage Prediction
Virtual resource load prediction in network function virtualization (NFV) is the subject of
intense research activity due to its key role in enabling proactive resource adaptation in …
intense research activity due to its key role in enabling proactive resource adaptation in …
A scalable architecture for federated service chaining
C Chen - 2022 - repository.lboro.ac.uk
The orchestration of Service Function Chain in multiple clouds calls for low-cost, low-latency
and scalability. In the existing literature, several techniques have been proposed to meet …
and scalability. In the existing literature, several techniques have been proposed to meet …