Forecasting and anticipating SLO breaches in programmable networks

Software Networks built by combining Software Defined Networks (SDN), Network Function Virtualization (NFV) and Cloud principles call for agile and dynamic automation of management operations to ensure continuous provisioning and deployment of networked resources and services. In this context, effic...

Full description

Saved in:
Bibliographic Details
Main Authors: Bendriss, Jaafar, Ben Yahia, Imen Grida, Zeghlache, Djamal
Format: Conference Proceeding
Language:English
Subjects:
ANN
Artificial neural networks
Cloud computing
Cognitive Management
Computer architecture
Machine Learning
Measurement
Monitoring
Network function virtualization
Network Management
NFV
SDN
SLA
SLO
Time factors
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Software Networks built by combining Software Defined Networks (SDN), Network Function Virtualization (NFV) and Cloud principles call for agile and dynamic automation of management operations to ensure continuous provisioning and deployment of networked resources and services. In this context, efficient Service Level Agreements (SLA) management and anticipation of Service Level Objectives (SLO) breaches become essential to fulfill established service contracts with clients. In this paper, we design and specify a framework for cognitive SLA enforcement (using Artificial Neural Network learning) for networking services involving VNFs (Virtualized Network Functions) and SDN controllers. A proof of concept, a testbed description and an extensive evaluation assess the performance of the proposed framework.
ISSN:2472-8144
DOI:10.1109/ICIN.2017.7899402