Series Editorial: Network Softwarization and Management

Industry and Standardization Activities on Converged Management of Fixed & Mobile Networks and the benefits brought by Autonomic Management & Control Principles: NGMN NGCOR and ETSI AFI Reports Keynote-Presentation-1 (20 minutes): Progress made in the Standardization of Autonomic Management & Control in Evolving and Future Network Architectures: ETSI AFI Generic Autonomic Networking Architecture (GANA) Reference Model & its instantiation in diverse network architectures [Presenter: Ranganai Chaparadza (PhD), ETSI AFI, IPv6 Forum] Keynote-Presentation-2(20 minutes): Automation based on harmonized interfaces for converged networks [Presenter: Klaus Martiny: Deutsche Telekom, NGMN] Keynote-Presentation-3 (20 minutes): Towards Converged Operations & Autonomicity in Mobile Backhaul (RAN and Transport)

The Internet of Things (IoT) is an emerging technology that aims to connect heterogeneous and constrained objects to each other and to the Internet. It has grown significantly in a wide variety of applications such as smart homes, smart cities, smart vehicles, etc. The huge number of connected devices increases the challenges, as IoT provides diverse and complex network services with different requirements on a common infrastructure. Network Softwarization is the latest network paradigm that transforms traditional network processes to the separation of hardware and software by using some enabling network technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). Machine Learning (ML) plays an essential role in creating smarter IoT networks, as it has shown remarkable results in various domains. Given that the network softwarization allows it to be easily integrated, ML can play a crucial role in efficient and self-adaptive IoT networks. In this paper, we provide a detailed overview of the concepts of IoT, network softwarization, and ML, and we study and discuss the state of the art of intelligent ML-enabled network softwarization for IoT. We also identify the most prominent future research directions to be considered.

Computer Communications, 1997

With increased number of new services and users being added to the communication network, management of such networks becomes crucial to provide assured quality of service. Finding skilled managers is often a problem. To alleviate this problem and also to provide assistance to the available network managers, network management has to be automated. Many attempts have been made in this direction and it is a promising area of interest to researchers in both academia and industry. In this paper, a review of the management complexities in present day networks and artificial intelligence approaches to network management are presented. Published by Elsevier Science B.V.

This paper examines the state-of-the-art enabling technologies for network management, including policy-based network management, distributed object computing, Web-based network management, Java-based network management, code mobility, intelligent agents, active networks, and economic theories. For each of them, we discuss the underlying concept, analyze the benefits and drawbacks, and discuss the applicability to network management. In doing so, we illustrate the common trend in network management design: moving towards distributed intelligence.

Computer-Mediated Communication [Working Title], 2021

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides ...

Journal of Network and Systems Management, 2009

Today, we see several emerging environments, with a large diversity of devices, networks, providers and service domains, characterized as the networks and services of the future. This special issue contains four papers on how to manage important topics of these environments: policy model to support ontology-driven reasoning for autonomic computing, SOA-based NGM management, metrics to distinguish application traffic, and SLA design and service provisioning for outsourced services. Keywords Autonomic networking Á Next Generation Networked Applications and Services Á IP Multimedia Subsystem Á Business-Driven IT Management The evolution of the Internet in the last few years has been remarkably high. Networks with an increasing access link and core bandwidth, plus the new applications consuming this bandwidth, are everywhere. Moreover, the growing number of heterogeneous wireless access networks, such as Wi-Fi, WiMax, 3G and beyond cellular networks, is allowing ubiquitous access to the Internet through sophisticated devices by which people are ''interconnected'' all the time. In this scenario, we include: • emerging networks, such as Next Generation Networks (NGNs), peer-to-peer (P2P) and community networks, ad hoc and self-configurable networks,

2009

This paper presents a viewpoint of the management for the Future Internet. For this description we consider the architectural model developed by the EU IST Autonomic Internet -AUTOI -consortium for the management design of the Future Internet as a service-and self-aware network that guarantees built-in orchestrated reliability, robustness, mobility, context, access, security, service support and self-management of the communication resources and services. The paper positions the autonomic network management approach taken by the AUTOI solution in a Future Internet scenario and describes the main interactions involved of the different distributed management systems running within the network in the context of the aforementioned scenario. The paper also provides a selection of the technical difficulties encountered so far while developing such a management approach. viewpoint of the network management paradigm for future internet networks. In Proc. of the 1st IFIP/IEEE Int'l Workshop on Management of the Future Internet (ManFI 2009), pages 93-100. IEEE, June 2009. See http://www.net.fim.uni-passau.de/papers/Rubio-Loyola2009a for full reference details (BibTeX, XML).

2009

Recent years, requirements in network management and control have been amended by emerging network and computing models, including wireless networks, ad-hoc networks, overlay networks, Grid networks, optical networks, multimedia networks, storage networks, the convergence of next generation networks (NGN), etc. The network management has to meet resource constraints, multi-federated operations, scalability, dependability, context awareness, security, mobility, probability, etc. This paper presents a survey of the evolution of networks and their trends, the challenges of management for emerging networks and services, and the evolution of network management strategies and solutions in network management.