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Autonomic Communications in Software-Driven Networks


Zhao, Zhongliang; Schiller, Eryk; Kalogeiton, Eirini; Braun, Torsten; Stiller, Burkhard; Garip, Mevlut Turker; Joy, Joshua; Gerla, Mario; Akhtar, Nabeel; Matta, Ibrahim (2017). Autonomic Communications in Software-Driven Networks. IEEE Journal on Selected Areas in Communications, 35(11):2431-2445.

Abstract

Autonomic communications aim to provide the quality-of-service in networks using self-management mechanisms. It inherits many characteristics from autonomic computing, in particular, when communication systems are running as specialized applications in software-defined networking (SDN) and network function virtualization (NFV)-enabled cloud environments. This paper surveys autonomic computing and communications in the context of software-driven networks, i.e., networks based on SDN/NFV concepts. Autonomic communications create new challenges in terms of security, operations, and business support. We discuss several goals, research challenges, and development issues on self-management mechanisms and architectures in software-driven networks. This paper covers multiple perspectives of autonomic communications in software-driven networks, such as automatic testing, integration, and deployment of network functions. We also focus on self-management and optimization, which make use of machine learning techniques.

Abstract

Autonomic communications aim to provide the quality-of-service in networks using self-management mechanisms. It inherits many characteristics from autonomic computing, in particular, when communication systems are running as specialized applications in software-defined networking (SDN) and network function virtualization (NFV)-enabled cloud environments. This paper surveys autonomic computing and communications in the context of software-driven networks, i.e., networks based on SDN/NFV concepts. Autonomic communications create new challenges in terms of security, operations, and business support. We discuss several goals, research challenges, and development issues on self-management mechanisms and architectures in software-driven networks. This paper covers multiple perspectives of autonomic communications in software-driven networks, such as automatic testing, integration, and deployment of network functions. We also focus on self-management and optimization, which make use of machine learning techniques.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:October 2017
Deposited On:08 Feb 2018 08:21
Last Modified:19 Feb 2018 10:52
Publisher:Institute of Electrical and Electronics Engineers
ISSN:0733-8716
OA Status:Closed
Publisher DOI:https://doi.org/10.1109/JSAC.2017.2760354
Other Identification Number:merlin-id:15656

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