@inproceedings{aab2bc548a4749cbae02ec31d2b4ab6f,
title = "Forecasting and anticipating SLO breaches in programmable networks",
abstract = "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.",
keywords = "ANN, Cognitive Management, Machine Learning, NFV, Network Management, SDN, SLA, SLO",
author = "Jaafar Bendriss and \{Ben Yahia\}, \{Imen Grida\} and Djamal Zeghlache",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017 ; Conference date: 07-03-2017 Through 09-03-2017",
year = "2017",
month = apr,
day = "13",
doi = "10.1109/ICIN.2017.7899402",
language = "English",
series = "Proceedings of the 2017 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "127--134",
editor = "Stefano Secci and Noel Crespi and Antonio Manzalini",
booktitle = "Proceedings of the 2017 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017",
}