New Trends in SDN/NFV Architectures and Routing Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (30 October 2021) | Viewed by 12342

Special Issue Editors


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Guest Editor
Department of Automatics, University of Alcalá, Plaza de San Diego, s/n, 28801 Alcalá de Henares, Madrid, Spain
Interests: computer networks; communication networks; SDN; NFV; IoT; P4

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Guest Editor
Department of Computer Engineering and Automation, University of Campinas, Albert Einstein - 400, Cidade Universitária Zeferino Vaz CEP: 13083-852, Campinas, SP, Brazil
Interests: network architectures; SDN; NFV; P4; machine learning
Special Issues, Collections and Topics in MDPI journals
Department of Informatics, Systems and Communication, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo, 1 - 20126 Milano, Italy
Interests: SDN; NFV; programmable data planes; network monitoring; edge computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The SDN architecture is permanently evolving and embracing new challenges after sowing seeds of a programmatic separation between control and data planes. At the crossroads, NFV introduces new ways of refactoring control and data plane related network functions. One of the multiple open challenges refers to hybrid SDN/NFV deployments, in which SDN and NFV principles are applied to hybrid networks. The term “hybrid” may refer to different aspects: networks composed of SDN, NFV and legacy devices, networks that include devices equipped with SDN-programmable wired and wireless interfaces or networks including devices that support both SDN and legacy operations. Such heterogeneous and extremely diverse networks are pushing the proliferation of novel solutions for in-band and advanced SDN control channels, overlay deployments, routing optimization techniques, network monitoring strategies and packet filtering/manipulation capabilities, and also taking advantage of open-source developments, hardware acceleration, novel programmable data planes technologies and programming languages such as P4.  

The networking hardware/software landscape is as relevant as ever and offers new offloading opportunities at node and network-wide scales. The location of control and data plane network functions is blurring, from the core to the edge, from one administrative provider to another, from programmable silicon to portable lightweight virtualized user-space containers, among other evolving SDN refactoring and offloading trends around fluid networking concepts.

Submissions to this Special Issue on ‘’New trends in SDN/NFV architectures and routing solutions” are solicited to represent a snapshot of the field’s development by covering a range of topics that include but are not limited to new protocols, algorithms, solutions, and applications in the following areas:

  • Intra- and inter-domain routing solutions based on SDN architectural principles
  • Protocols novel in-band SDN control and telemetry channels
  • Hybrid SDN/NFV network architectures
  • Routing solutions based on the programmability of the control and/or data planes
  • Offloading techniques of control and data plane functions
  • AI/ML-based routing algorithms
  • SDN-based network monitoring
  • Design and implementation of hybrid programmable data planes
  • Advanced packet manipulation and scheduling in programmable data planes
  • SDN-based control and management of multi-layer networks
  • Intent-based SDN protocols and architectures
  • Novel architectures for function placement and orchestration in SDN/NFV networks

Prof. Dr. Isaias Martinez Yelmo
Dr. Christian Esteve Rothenberg
Dr. Marco Savi
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SDN
  • NFV
  • routing
  • protocols
  • in-band
  • P4

Published Papers (3 papers)

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Research

19 pages, 1965 KiB  
Article
Run-Time Adaptive In-Kernel BPF/XDP Solution for 5G UPF
by Thiago A. Navarro do Amaral, Raphael V. Rosa, David F. Cruz Moura and Christian Esteve Rothenberg
Electronics 2022, 11(7), 1022; https://doi.org/10.3390/electronics11071022 - 24 Mar 2022
Cited by 3 | Viewed by 4126
Abstract
Flexibility is considered a key feature of 5G softwarization to deliver a timely response to changes in network requirements that may be caused by traffic variation, user mobility, dynamic network function chains, slice lifecycle management operations, among others. In this article, we evolve [...] Read more.
Flexibility is considered a key feature of 5G softwarization to deliver a timely response to changes in network requirements that may be caused by traffic variation, user mobility, dynamic network function chains, slice lifecycle management operations, among others. In this article, we evolve the upf-bpf1 open-source project by proposing a new design to improve its flexibility by reducing the run-time adaptation time. The project proposes an in-kernel solution based on BPF and eXpress Data Path (XDP) for 5G User Plane Function (UPF) implementations. The Just-In-Time (JIT) compilation may have a huge impact on the adaptation time due to the in-kernel verification of the BPF programs at run-time. Our results show latency improvements of around 95% to inject the BPF program into the Linux kernel. Furthermore, the solution keeps the same functionalities and delivers a packet processing performance of around 10–11 Mpps using 6 cores with almost 70% of the CPU utilization in downlink/uplink directions. Full article
(This article belongs to the Special Issue New Trends in SDN/NFV Architectures and Routing Solutions)
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16 pages, 1540 KiB  
Article
P4-KBR: A Key-Based Routing System for P4-Programmable Networks
by Pilar Manzanares-Lopez, Juan Pedro Muñoz-Gea and Josemaria Malgosa-Sanahuja
Electronics 2021, 10(13), 1543; https://doi.org/10.3390/electronics10131543 - 25 Jun 2021
Cited by 3 | Viewed by 2299
Abstract
Software-defined networking (SDN) architecture has provided well-known advantages in terms of network programmability, initially offering a standard, open, and vendor-agnostic interface (e.g., OpenFlow) to instruct the forwarding behavior of network devices from different vendors. However, in the last few years, data plane programmability [...] Read more.
Software-defined networking (SDN) architecture has provided well-known advantages in terms of network programmability, initially offering a standard, open, and vendor-agnostic interface (e.g., OpenFlow) to instruct the forwarding behavior of network devices from different vendors. However, in the last few years, data plane programmability has emerged as a promising approach to extend the network management allowing the definition and programming of customized and non-standardized protocols, as well as specific packet processing pipelines. In this paper, we propose an in-network key-based routing protocol called P4-KBR, in which end-points (hosts, contents or services) are identified by virtual identifiers (keys) instead of IP addresses, and where P4 network elements are programmed to be able to route the packets adequately. The proposal was implemented and evaluated using bmv2 P4 switches, verifying how data plane programmability offers a powerful tool to overcome continuing challenges that appear in SDN networks. Full article
(This article belongs to the Special Issue New Trends in SDN/NFV Architectures and Routing Solutions)
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18 pages, 3036 KiB  
Article
Network Intelligent Control and Traffic Optimization Based on SDN and Artificial Intelligence
by Aipeng Guo and Chunhui Yuan
Electronics 2021, 10(6), 700; https://doi.org/10.3390/electronics10060700 - 16 Mar 2021
Cited by 19 | Viewed by 4515
Abstract
For telecom operators, it is of great significance to employ artificial intelligence (AI) and big data technology in a software-defined network (SDN) in order to achieve intelligent network control, traffic management and optimization. This paper proposes a solution for intelligent work control and [...] Read more.
For telecom operators, it is of great significance to employ artificial intelligence (AI) and big data technology in a software-defined network (SDN) in order to achieve intelligent network control, traffic management and optimization. This paper proposes a solution for intelligent work control and traffic optimization. This paper is mainly focused on SDN-based network traffic algorithm optimization and experimental verification. In this paper, we design a network control mechanism for network intelligent control as well as solutions for traffic optimization based on SDN and artificial intelligence. We analyze operators’ network requirements (e.g., the carrying of the 5th generation mobile network (5G) service, multi-protocol label switching virtual private networks optimization, cloudification of services and the IP backbone network). Then, we propose an intelligent network control architecture based on SDN and artificial intelligence. The proposed architecture consists of three modules, including a network status collection/perception module, an AI intelligent analysis module and an SDN controller module. Moreover, this paper also analyzes the objects of traffic optimization as well as routing calculation algorithms (e.g., the greedy algorithm, the top-k-shortest paths (KSP) algorithm) and routing optimization algorithms (e.g., particle swarm optimization, simulated annealing and genetic algorithms). In addition, we also put forward three optimization algorithms for the operator’s network, namely, network congestion control and prevention algorithms, resource preemption algorithms and balance of the entire network traffic algorithms. Then, we propose optimization algorithms for the above three objectives of operator network optimization, respectively. Finally, we conduct large-scale experiments to verify the effectiveness of the control mechanism and algorithms. The experimental results demonstrate that the use of SDN and artificial intelligence in operator networks can realize network intelligent control and traffic optimization more intelligently. Full article
(This article belongs to the Special Issue New Trends in SDN/NFV Architectures and Routing Solutions)
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