IET Networks最新文献_第4页

An Efficient Cluster-Based Routing Protocol for Enhanced Data Delivery and Stability in VANETs: Cluster-Based Ant-Colony Routing With Adaptive Cluster Head 一种增强VANETs数据传输和稳定性的高效集群路由协议：具有自适应簇头的基于集群的蚁群路由

IF 1.4

IET Networks Pub Date : 2025-08-24 DOI: 10.1049/ntw2.70013

Léonce Thérèse Pidy Pidy, Justin Moskolaï Ngossaha, Thenuka Karunathilake, Samuel Bowong Tsakou, Anna Förster

{"title":"An Efficient Cluster-Based Routing Protocol for Enhanced Data Delivery and Stability in VANETs: Cluster-Based Ant-Colony Routing With Adaptive Cluster Head","authors":"Léonce Thérèse Pidy Pidy, Justin Moskolaï Ngossaha, Thenuka Karunathilake, Samuel Bowong Tsakou, Anna Förster","doi":"10.1049/ntw2.70013","DOIUrl":"10.1049/ntw2.70013","url":null,"abstract":"Vehicular ad hoc networks (VANETs) are an essential enabler of intelligent transport systems (ITS), facilitating real-time communication among vehicles to enhance traffic safety and mobility. However, challenges such as high node mobility, frequent topology changes, and variable network density continue to impede the design of reliable and efficient routing protocols. This paper proposes CARAC (Cluster-based Ant-colony Routing with Adaptive Cluster Head), a hybrid routing protocol that integrates dynamic clustering using the K-medoids algorithm with Ant Colony Optimisation (ACO) to improve route stability, scalability, and data delivery performance. CARAC forms mobility-aware clusters by grouping vehicles based on spatial proximity and relative velocity. Each node periodically computes a local stability index to evaluate its membership within a cluster, allowing adaptive cluster maintenance. The protocol also incorporates ACO for optimal path selection and utilises Road Side Units (RSUs) as relays when direct communication between cluster heads is not feasible. Simulation experiments conducted in NS-3 with a vehicular network scenario demonstrate that CARAC consistently outperforms benchmark protocols such as AQRV, MetaLearn and CPB. It delivers higher route discovery success, better packet delivery performance, lower latency, and greater throughput. These results validate the advantages of combining clustering, bio-inspired optimisation, and adaptive stability evaluation in VANET routing, positioning CARAC as a robust and scalable solution for next-generation ITS applications.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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A Survey of Load Balancing Approaches Based on Switch Migration in Software-Defined Networks 软件定义网络中基于交换机迁移的负载均衡方法综述

IF 1.4

IET Networks Pub Date : 2025-08-13 DOI: 10.1049/ntw2.70015

Hamid Reza Naji, Harir Riyahi

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IF 1.4

IET Networks Pub Date : 2025-08-13

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Distributed Denial of Service Detection: Enhancing Machine Learning Models for Multiclass Classification 分布式拒绝服务检测：增强多类分类的机器学习模型

IF 1.4

IET Networks Pub Date : 2025-08-09 DOI: 10.1049/ntw2.70014

Paulo Victor, Iris Viana dos Santos Santana, Álvaro Sobrinho, Lenardo Chaves e Silva, Leandro Dias da Silva, Danilo F. S. Santos, Angelo Perkusich

{"title":"Distributed Denial of Service Detection: Enhancing Machine Learning Models for Multiclass Classification","authors":"Paulo Victor, Iris Viana dos Santos Santana, Álvaro Sobrinho, Lenardo Chaves e Silva, Leandro Dias da Silva, Danilo F. S. Santos, Angelo Perkusich","doi":"10.1049/ntw2.70014","DOIUrl":"10.1049/ntw2.70014","url":null,"abstract":"This study experiments with machine learning algorithms for detecting distributed denial of service attacks as a multiclass classification problem. The algorithms included the K-nearest neighbours, decision trees, support vector machines, random forests, extreme gradient boosting, gradient boosting machines and multilayer perceptron. We validated the models using the hold-out and cross-validation methods, performed class and model ablation analysis to evaluate performance impacts and applied feature selection techniques, feature importance and statistical tests. For instance, using 10-fold cross-validation with 79 features, 11 attack types and regular network traffic, the tree-based models achieved accuracies ranging from 75.69% to 76.24%. When using 15 features, seven attacks and regular network traffic, model accuracy improved significantly, ranging from 97.77% to 98.08%. Furthermore, in specific application scenarios, some models achieved near-perfect classification performance. Decision tree achieved the highest accuracy score for the local network communication scenario, reaching 99.86%, followed by software distribution or updates at 99.70%, web platforms and online applications at 98.25%, video streaming or online gaming at 97.06%, infrastructure monitoring and management at 95.00% and directory services and corporate authentication at 87.15%. Depending on the application scenario, our results indicate that specialised models can support classification tasks targeting specific system components with high performance.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Energy-Aware Optimisation for Off-Grid ORAN With RIS and Edge Computing 基于RIS和边缘计算的离网ORAN能量感知优化

IF 1.4

IET Networks Pub Date : 2025-08-04 DOI: 10.1049/ntw2.70012

Yassir AL-Karawi, Raad S. Alhumaima, Hamed Al-Raweshidy

{"title":"Energy-Aware Optimisation for Off-Grid ORAN With RIS and Edge Computing","authors":"Yassir AL-Karawi, Raad S. Alhumaima, Hamed Al-Raweshidy","doi":"10.1049/ntw2.70012","DOIUrl":"10.1049/ntw2.70012","url":null,"abstract":"This paper proposes a strategy for designing Open Radio Access Networks (ORAN) to maximise their energy efficiency using solar power, supplemented by Reconfigurable Intelligent Surfaces (RIS) and Mobile Edge Computing (MEC). Because grid power is not always available where these ORAN systems are built, our approach manages the difficulties created by dynamic energy and timing issues found in isolated environments. The approach concentrates on allocating energy to all transmitters, CPU speed and RIS phases in real time, subject to strict rules on power use, latency issues and heat. The primal-dual algorithm we propose reacts to queue and energy changes to update the dual variables and control policies without access to every channel parameter. Our combined (composite) cost function measures energy use, delays encountered by users, reliability of the SINR and fairness. Results from the simulation indicate that using the proposed method lowers energy usage by 25% and average delay by 18%, outperforming baseline models under varying solar and traffic patterns. Robustness is further validated through sensitivity and ablation analyses. This work demonstrates the feasibility of deploying sustainable, intelligent ORAN infrastructures in remote 6G scenarios where conventional power and connectivity are unavailable.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IF 1.4

IET Networks Pub Date : 2025-07-29

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Adaptive Routing Strategies for Optimisation in MANETs Through Integration of Expanding Ring Search and Random Early Detection Using Machine Learning 基于扩展环搜索和机器学习随机早期检测的自适应路由优化策略

IF 1.4

IET Networks Pub Date : 2025-07-29 DOI: 10.1049/ntw2.70005

Durre Nayab, Mohammad Haseeb Zafar, Madiha Sher

{"title":"Adaptive Routing Strategies for Optimisation in MANETs Through Integration of Expanding Ring Search and Random Early Detection Using Machine Learning","authors":"Durre Nayab, Mohammad Haseeb Zafar, Madiha Sher","doi":"10.1049/ntw2.70005","DOIUrl":"10.1049/ntw2.70005","url":null,"abstract":"This work presents a novel machine learning (ML)-driven framework to optimise reactive routing protocols (RRPs) in mobile ad hoc networks (MANETs), tackling congestion control through intelligent, real-time protocol selection. Building on our prior Adaptive Expanding Ring Search (AERS) method enhanced with random early detection (RED), the study introduces an ML classification system that dynamically identifies the most efficient RRP based on network conditions. High-accuracy classifiers, AdaBoost (95%), K-Nearest Neighbours (93%), and Decision Trees (92%), enable data-driven decision-making, systematically evaluating protocols across diverse topologies to maximise performance. The framework ensures context-aware routing, significantly improving Quality of Service (QoS) through enhanced packet delivery, reduced latency, and robust congestion mitigation. Rigorous NS-3 simulations validate the approach, demonstrating measurable gains over conventional methods. By integrating predictive analytics into routing strategy, this research advances the design and deployment of RRPs, bridging algorithmic innovation with practical implementation. The results offer high-impact insights for both academic research and real-world MANET applications, establishing a new paradigm for adaptive, efficient routing in dynamic wireless environments.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Power-Allocation Algorithm for Fairness Maximisation of Non-Orthogonal Multiple Access-Based Multibeam Satellite Networks 基于非正交多址的多波束卫星网络公平性最大化的功率分配算法

IF 1.4

IET Networks Pub Date : 2025-07-21 DOI: 10.1049/ntw2.70011

Joel Biyoghe, Vipin Balyan

{"title":"Power-Allocation Algorithm for Fairness Maximisation of Non-Orthogonal Multiple Access-Based Multibeam Satellite Networks","authors":"Joel Biyoghe, Vipin Balyan","doi":"10.1049/ntw2.70011","DOIUrl":"10.1049/ntw2.70011","url":null,"abstract":"5G networks and beyond set a critical requirement for both massive capacity and seamless connectivity to all users. This implies that, the network must have both very high capacity and users' fairness. Non-Orthogonal Multiple-Access (NOMA)-based Multibeam Satellite Networks (MBSNs) are designed for 5G networks, and are thus, required to provide both high capacity and high users' fairness. Most existing power-allocation (PA) algorithms for NOMA-MBSNs focus on maximising the network's throughput alone, with not much attention on user's fairness. This leaves a critical requirement of 5G networks unaddressed. As an attempt to close this gap, this paper, proposes a PA algorithm that maximises the users' fairness of a 2Users NOMA-MBSN. To do so, the maximisation request is formulated as an optimisation problem. The original problem being NP-hard, it is decomposed into two sub-problems; namely, the intra-beam and the inter-beam fairness maximisation. Each of these problem is independently solved by means of numerical search methods. In this regards, the concept of converging the Offered-Capacity to Traffic-Request (OCTR) ratios of respective users, in order to maximise the system's fairness, is employed. Thus, based on the OCTR-ratios convergence concept, the fairness maximisations power-allocation algorithms, which respectively solve the two sub-problems, are designed. The two algorithms include the intra-beam and the inter-beam power-allocation algorithms. A global power-allocation algorithm (PAA-1) combines the two algorithm, to yield a solution to the original problem. Numerical results confirm that, the algorithm makes all the OCTR-ratios of all user converge; thus maximising the network's users-fairness. Results also demonstrate the superiority of the proposed PAA-1 with respect to achieved system's fairness, compared to some other existing PA algorithms.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Performance Analysis of Hybrid Scheme of Slotted ALOHA and PD-NOMA for Massive Machine-Type Communications 大规模机型通信中开槽ALOHA和PD-NOMA混合方案的性能分析

IF 1.4

IET Networks Pub Date : 2025-07-21 DOI: 10.1049/ntw2.70009

Chen Guanzhou, Kouki Takahashi, Mai Mikogami, Yuki Ichimura, Takeshi Hirai, Taewoon Kim, Shigeo Shioda

{"title":"Performance Analysis of Hybrid Scheme of Slotted ALOHA and PD-NOMA for Massive Machine-Type Communications","authors":"Chen Guanzhou, Kouki Takahashi, Mai Mikogami, Yuki Ichimura, Takeshi Hirai, Taewoon Kim, Shigeo Shioda","doi":"10.1049/ntw2.70009","DOIUrl":"10.1049/ntw2.70009","url":null,"abstract":"This paper investigates the characteristics of slotted ALOHA and power-domain nonorthogonal multiple access (PD-NOMA) hybrid schemes, focusing on two key performance metrics, namely device transmission success probability and base station throughput, while also considering distance-based unfairness among devices. We analyse three distinct hybrid schemes: a scheme where all devices transmit signals with equal power without utilising received signal strength (RSS) targets (Scheme 1), a scheme where devices randomly select one of multiple RSS targets at the nearest base station (Scheme 2), and a scheme where devices select one of multiple RSS targets based on their proximity to the nearest base station (Scheme 3). Our findings reveal that while Scheme 1 has the highest performance, it also has the most pronounced distance-based unfairness. Conversely, Scheme 2 has the lowest performance but effectively mitigates distance-based unfairness. The performance of Scheme 3 improves as the number of RSS targets increases; however, this coincides with an increase in distance-based unfairness. These results suggest that achieving a balance between fairness and performance improvement may be inherently challenging in grant-free access schemes.","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IF 1.4

IET Networks Pub Date : 2025-07-21

引用次数: 0