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Automation of multi-layer multi-domain transport networks and the role of AI [Invited]

JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING 2025年第2期17卷 A124-A133页

作者： de Dios, Oscar Gonzalez Robles, Pablo Armingol Roelens, Liesbeth Muniz-Da-Costa, Alejandro de Miguel, Ignacio Barroso, Ramon J. Duran Fernandez-Palacios, Juan Pedro Tel Innovac Digital Madrid Spain Univ Valladolid Valladolid Spain

With increasing demand for customized connectivity, transport networks must evolve towards autonomous and customer-driven network management. This paper presents a comprehensive overview of network autonomy and the challenges associated with evolving toward higher levels of autonomy. Moreover, various use cases of artificial intelligence in network automation in ip-over-DWDM transport networks are also analyzed, in particular related to traffic prediction, quality of transmission, anomaly detection, network planning, and proactive failure management. Additionally, the role of generative AI in network operation is explored. Central to our discussion is a proposed control architecture based on open and standard SDN APIs, which incorporates network slicing for multi-layer transport networks and enables real-time access to normalized data, facilitating autonomous network operation.

关键词： Autonomous networks Artificial intelligence Real-time systems Planning Resource management Network slicing Data analysis Computer architecture Telemetry scalability

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Joint energy efficiency and load balancing optimization in hybrid ip/SDN networks

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ANNALS OF TELECOMMUNICATIONS 2023年第1-2期78卷 13-31页

作者： Galan-Jimenez, Jaime Polverini, Marco Lavacca, Francesco G. Luis Herrera, Juan Berrocal, Javier Univ Extremadura Dept Comp Syst & Telemat Engn Avda Univ S-N Caceres 10003 Spain Univ Rome Sapienza DIET Dept Via Eudossiana 18 I-00184 Rome Italy

Software-defined networking (SDN) is a paradigm that provides flexibility and programmability to computer networks. By introducing SDN nodes in a legacy ip network topology, network operators can benefit on higher control over the infrastructure. However, this migration is not a fast or straightforward process. Furthermore, to provide an adequate quality of service in hybrid ip/SDN networks, the coordination of both ip and SDN paradigm is fundamental. In this paper, this coordination is used to solve two optimization problems that are typically solved separately: (i) traffic load balancing and (ii) power consumption minimization. Each of these problems has opposing objectives, and thus, their joint consideration implies striking a balance between them. Therefore, this paper proposes the Hybrid Spreading Load Algorithm (HSLA) heuristic that jointly faces the problems of balancing traffic by minimizing link utilization and network's power consumption in a hybrid ip/SDN network. HSLA is evaluated over differently sized topologies using different methods to select which nodes are migrated from ip to SDN. These evaluations reveal that alternative approaches that only address one of the objectives are outperformed by HSLA.

关键词： Hybrid ip SDN Load balancing Energy efficiency traffic engineering Heuristic

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Adaptive overlay selection at the SD-WAN edges: A reinforcement learning approach with networked agents

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COMPUTER networks 2024年 243卷

作者： Botta, Alessio Canonico, Roberto Navarro, Annalisa Stanco, Giovanni Ventre, Giorgio Univ Napoli Federico II DIETI Via Claudio 21 I-80125 Naples Italy

Software-Defined Wide Area networks (SD-WANs) have emerged as a promising solution to address the connectivity demands of modern distributed enterprises. However, the effective application of the Software Defined Networking (SDN) paradigm in such broad and dynamic environments remains a significant challenge. In this paper, we present two novel contributions. First, we design a decentralized control plane for SD-WANs that leverages edge-based network monitoring and overlays' configuration. Then we present a Reinforcement Learning-based orchestration plane that leverages local information for the enforcement of SD-WAN policies. Since traditional approaches suffer either a lack of scalability due to the problem's complexity or suboptimal performance due to isolated decision-making, the proposed approach leverages a cooperative Multi -Agent Reinforcement Learning framework. Our novel cooperative approach is based on per-site agents that exchange a small amount of information to enhance performance while preserving scalability. To validate the efficacy of our proposed approach, we conducted an extensive experimental evaluation considering diverse SD-WAN scenarios. Results show that our framework is able to satisfy global network policies for a multi-site SD-WAN with different QoS requirements and cost constraints.

关键词： SD-WAN SDN Multi-agent reinforcement learning traffic engineering

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High Bandwidth and Highly Available Packet Buffer Design Using Multi-Retention Time MRAM

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IEEE ACCESS 2023年 11卷 98016-98024页

作者： Song, Yongwoon Lee, Munhyung Lee, Hyukjun Sogang Univ Dept Comp Sci & Engn Seoul 04107 South Korea

Significant challenges are posed in the design of routers and switches by the explosive growth of internet traffic and the stringent requirements for high availability in the research area of computer networks. Ensuring both high performance and system availability is crucial. To achieve this, recent advancements have turned to the utilization of non-volatile memories, such as magnetic RAM (MRAM) and phase-change memory (PCM), in routing lookup tables and packet buffers of routers and switches. However, the use of non-volatile memories show limitations in scaling with respect to bandwidth and capacity. With the increasing clock speed of the IO bus, high-capacity memories like PCM exhibit limited scalability in performance since accessing the cells in the array does not show significant improvement. Meanwhile, attempts to enhance the capacity of low-access-latency non-volatile memories like spin-transfer torque MRAM (STT-MRAM) through smaller cell sizes result in an adverse impact on the write time. The goal of this study is to design a packet buffer that can provide high bandwidth and ensure high availability. To achieve this, a multi-retention time MRAM-based packet buffer is presented, along with a packet mapping method, which aims to overcome the scalability challenge while ensuring high availability. The two-tier packet buffer (TT-PB) structure implements a small/fast MRAM combined with a large/slow MRAM, which outperforms the baseline MRAM/PCM hybrid memory-based packet buffer by up to 16% and 58% for 1.6 and 3.2 GHz IO bus clocks. For input, internet-mix packet traffic is utilized to depict realistic internet traffic. Moreover, the proposed latency-aware multi-retention time MRAM-based packet buffer structure (MR-PB) consists of short and long retention time MRAM partitions. It identifies the buffering latency demands of various packets and writes the packets into partitions that have sufficient retention time to accommodate the required buffering latencies, t

关键词： Random access memory Bandwidth Thermal stability Phase change materials Clocks Nonvolatile memory Thermal factors ip networks Torque control Packet switching ip router packet buffer spin-transfer torque magnetic RAM (STT-MRAM) multi-retention time

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A Heuristic Route Planning Scheme in Scalable VANET-Oriented Evolving Grid Graph (S-VoEGG)

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第4期11卷 3851-3865页

作者： Khan, Zahid Koubaa, Anis Benjdira, Bilel Prince Sultan Univ PSU Coll Comp & Informat Sci Robot & Internet Things Lab RI OTU Lab Riyadh 12435 Saudi Arabia

Clustering is an excellent solution to divide the network into manageable groups to reduce the excessive overhead. However, the number of clusters can lead to MAC contention (in dense clusters) and network disconnection (in sparse clusters) problems. This paper proposes a heuristic and scalable route planning scheme for traffic congestion avoidance and optimal data communications. The contributions are two-fold: (i) Heuristic Street Planning Scheme (H-SPS) and (ii) Heuristic Scalable Reliable Ad hoc on Demand Distance Vector (HS-RAODV). H-SPS utilizes A-Star ( A(& lowast;) ) for traffic control, outperforming the conventional Dijkstra algorithm regarding street discovery time and overhead. HS-RAODV, an extension of CEG-RAODV, introduces scalability and A & lowast;as the route planning algorithm. It operates in linear mode (A*-RAODV) for sparse VANETs, discovering reliable routes without forming extra clusters. In congested VANETs, clustering mode (CA*-RAODV) leverages spectral clustering for optimal grouping. Compared to previous schemes, the proposed protocol achieves superior performance in route reliability, discovery messages, packet delivery ratio, end-to-end delay, throughput, and route scalability.

关键词： Routing protocols Routing Reliability Planning Clustering algorithms Vehicular ad hoc networks Roads Clustering evolving graphs path planning routing smart transportation

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LoRa Meets ip: A Container-Based Architecture to Virtualize LoRaWAN End Nodes

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第10期23卷 9191-9207页

作者： Cilfone, Antonio Davoli, Luca Ferrari, Gianluigi Univ Parma Dept Engn & Architecture Internet Things IoT Lab I-43124 Parma Italy Tesmec Automat Srl I-43036 Fidenza Italy

In this work, a container-based architecture for the integration of Long Range Wide Area Network (LoRaWAN) end nodes-e.g., used to monitor industrial machines or mobile entities in specific environments-with Internet Protocol (ip)-based networks is proposed and its performance is investigated. To this end, we exploit the native service and resource discovery support of the Constrained Application Protocol (CoAP), as well as its light traffic requirements, owing to its use of User Datagram Protocol (UDP) rather than Transmission control Protocol (TCP). This approach (i) adapts transparently (with no impact) to both private and public LoRaWAN networks, (ii) enables seamless interaction between LoRaWAN-based and CoAP-based nodes, through a logical "virtualization" of LoRaWAN nodes at server side, and (iii) enables routing among LoRaWAN end nodes, overcoming LoRaWAN's absence of inter-node communication and lack of compliance (at the end nodes' side) with ip. Two virtualization approaches are proposed: (i) virtualization of a single end node (represented as a CoAP server) per container and (ii) virtualization of multiple end nodes (as CoAP servers) per container. Finally, deployments of the proposed virtualization architectures, using both a laptop and an Internet of Things (IoT) device (e.g., a Raspberry Pi), are considered, highlighting how the best solution relies on the use of several containers, with more than one CoAP server per container.

关键词： Internet of Things Low-power wide area networks Servers Computer architecture Mobile computing Downlink LoRaWAN virtualization Constrained Application Protocol (CoAP) Constrained Application Protocol (CoAP)

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A flow-based intrusion detection framework for internet of things networks

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CLUSTER COMPUTING-THE JOURNAL OF networks SOFTWARE TOOLS AND APPLICATIONS 2023年第1期26卷 37-57页

作者： Santos, Leonel Goncalves, Ramiro Rabadao, Carlos Martins, Jose Polytech Leiria Comp Sci & Commun Res Ctr Leiria Portugal Polytech Leiria Sch Technol & Management Leiria Portugal INESC TEC Porto Portugal AquaValor Ctr Valorizacao & Transferencia Tecnol Chaves Portugal Inst Politecn Braganca Campus Santa Apolonia P-5300253 Braganca Portugal

The application of the Internet of Things concept in domains such as industrial control, building automation, human health, and environmental monitoring, introduces new privacy and security challenges. Consequently, traditional implementation of monitoring and security mechanisms cannot always be presently feasible and adequate due to the number of IoT devices, their heterogeneity and the typical limitations of their technical specifications. In this paper, we propose an ip flow-based Intrusion Detection System (IDS) framework to monitor and protect IoT networks from external and internal threats in real-time. The proposed framework collects ip flows from an IoT network and analyses them in order to monitor and detect attacks, intrusions, and other types of anomalies at different IoT architecture layers based on some flow features instead of using packet headers fields and their payload. The proposed framework was designed to consider both the IoT network architecture and other IoT contextual characteristics such as scalability, heterogeneity, interoperability, and the minimization of the use of IoT networks resources. The proposed IDS framework is network-based and relies on a hybrid architecture, as it involves both centralized analysis and distributed data collection components. In terms of detection method, the framework uses a specification-based approach drawn on normal traffic specifications. The experimental results show that this framework can achieve approximate to 100% success and 0% of false positives in detection of intrusions and anomalies. In terms of performance and scalability in the operation of the IDS components, we study and compare it with three different conventional IDS (Snort, Suricata, and Zeek) and the results demonstrate that the proposed solution can consume fewer computational resources (CPU, RAM, and persistent memory) when compared to those conventional IDS.

关键词： Internet of things Network monitoring Intrusion detection Network security Network attacks

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Anomaly Detection for Mitigating xApp and E2 Interface Threats in O-RAN Near-RT RIC

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2025年 6卷 1682-1694页

作者： Hung, Cheng-Feng Tseng, Chi-Heng Cheng, Shin-Ming Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei City 106335 Taiwan

As 5G networks advance, the Open Radio Access Network (O-RAN) is crucial in enabling openness and fostering collaboration across the telecom industry. O-RAN enhances flexibility, scalability, and interoperability through open interfaces, reducing dependence on a single vendor and promoting interoperability among vendors and solutions. The Near-Real-Time Radio Intelligent controller (Near-RT RIC) is crucial for optimizing network resources and improving user experience. However, the openness of O-RAN also introduces security challenges, particularly from third-party developed xApps and E2 nodes that may exploit vulnerabilities to launch attacks. This paper proposes an anomaly traffic detector to protect the Near-RT RIC from threats on the E2 interface. The anomaly traffic detector verifies the legality of signaling through an internal state machine analysis module and checks packet fields through a conformance check module while monitoring network traffic in real time to detect and mitigate Denial of Service attacks. Additionally, we designed a fuzzer to simulate random attacks, testing the capability of the anomaly traffic detector. The anomaly traffic detector not only successfully passes the test cases highlighted in the O-RAN Security Test Specifications, effectively detecting unauthorized traffic and signaling, but also identifies real-world vulnerability exploits, including CVE-2023-40997, CVE-2023-40998, CVE-2023-41627, and CVE-2023-41628, thereby significantly enhancing the security of the Near-RT RIC.

关键词： Open RAN Security Detectors ip networks Real-time systems 5G mobile communication Monitoring Resource management Optimization traffic control Anomaly detection E2 node E2 interface O-RAN security xApp

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Adaptive Beacon Period Configurator for Scalable LoRaWAN Downlink Applications

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IEEE ACCESS 2023年 11卷 83627-83638页

作者： Todoli-Ferrandis, David Silvestre-Blanes, Javier Sempere-Paya, Victor Santonja-Climent, Salvador Inst Tecnol Informat ITI Valencia 46980 Spain Polytech Univ Valencia UPV Dept Informat Sistemas & Comp DISCA ITI Valencia 46022 Spain Polytech Univ Valencia UPV Dept Comunicac DCOM ITI Valencia 46022 Spain

Low-power wide-area networks (LPWAN) are commonly used because they meet the requirements of Internet-of-Things (IoT) networks with a large number of end devices, such as high network scalability, wide area coverage, low data rates, and delay tolerance while consuming very little energy. The LoRa wide-area network (LoRaWAN) is one of the most popular solutions, supporting three types of medium access control (MAC) options to handle distinct application demands. Class B shortens downlink frame transmission latency while maintaining low energy consumption in the end device. This article analyzes the operation of gateways with class B devices to determine the events that influence scalability and performance, presents an analytical model to describe these systems, and proposes an optimization mechanism called Adaptive Beacon Period Configurator (ABPC). ABPC changes the time-related parameters configuration to improve the usability of these networks in dynamic scenarios. The proposed solution is then simulated and tested against the analytical model. The tradeoff between the waiting time between messages, the probability of reception, and the energy consumption of an end device is shown in the results, describing how traffic density increases impacts in these Key Performance Indicators (KPI) and how to try to guarantee these requirements in a network deployment.

关键词： LoRaWAN low power wide area network (LPWAN) scalability network optimization

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BDDTPA: Blockchain-Driven Deep traffic Pattern Analysis for Enhanced Security in Cognitive Radio Ad-Hoc networks

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IEEE ACCESS 2023年 11卷 98202-98216页

作者： Dansana, Debabrata Behera, Prafulla Kumar Darem, Abdulbasit A. Ashraf, Zubair Zamani, Abu Taha Ahmed, Mohammad Nadeem Patro, Gopal Krishna Shameem, Mohammad Utkal Univ Dept Comp Sci & Applicat Vani Vihar Bhubaneswar 751004 Odisha India Northern Border Univ Dept Comp Sci Ar Ar 73213 Saudi Arabia GLA Univ Dept Comp Engn & Applicat Mathura 281406 Uttar Pradesh India King Khalid Univ Dept Comp Sci Abha 61421 Saudi Arabia GIET Univ Dept CSE Gunupur 765022 Odisha India Dr Vishwanath Karad MIT World Peace Univ Dept Comp Sci & Applicat Pune 411005 India

Cognitive Radio Ad-hoc networks (CRAHNs) combines characteristics of ad-hoc networks with cognitive radios to facilitate a variety of communication scenarios. However, these networks are subject to persistent attacks from internal and external adversaries, such as Masquerading, Spoofing, Spying, and Distributed Denial of Service (DDoS). Existing deep learning models proposed to counter these attacks suffer from complexity, real-time processing limitations, and a lack of network scalability. In addition, their limited ip tracing capabilities make them unsuitable for real-time deployments. To address these issues, this paper proposes a novel blockchain-based model for deep traffic pattern analysis and mitigation of malicious attacks in CRAHNs. The proposed model employs a multi-step methodology. The collected traffic patterns are then used to train a deep Convolutional Neural Network (dCNN) model. This trained model permits the temporal classification of incoming real-time traffic packets. The packets are stored on a distributed network based on blockchain technology to ensure data integrity, transparency, and traceability. This blockchain implementation renders the packets immutable and easily accessible, while also facilitating the recommendation of improved mitigation strategies. The blockchain employs a Proof-of-Trust (PoT) consensus mechanism and is managed via a Genetic Algorithm (GA)-based sidechaining model, which significantly reduces access and writing delays for various packets. The proposed model achieves a significant reduction in communication delay in comparison to existing models, with decreases of 35.4%, 19.5%, and 23.5% for BIDS, BIST WM, and GAN, respectively. Additionally, energy consumption is reduced by 18.5%, 18.3%, and 24.5%, respectively. In addition, the model exhibits an increase in throughput of 14.5%, 16.4%, and 15.5%, respectively. Lastly, it improves the accuracy of attack detection during various communications by 8.3%, 23.2%, and 8.3%,

关键词： Blockchains traffic control Real-time systems Analytical models Security Ad hoc networks Cognitive radio Trust management Genetic algorithms Cognitive radio ad-hoc networks attacks blockchain dCNN proof of trust genetic algorithm

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