Computer Networks最新文献

{"title":"Decentralized reinforcement learning-based resource management for dense-interference IoV","authors":"Chengbo Yu ,&nbsp;Yidan Sun ,&nbsp;Xingxing Li ,&nbsp;Fan Yang ,&nbsp;Jie Huang ,&nbsp;Yingying Peng","doi":"10.1016/j.comnet.2025.111402","DOIUrl":"10.1016/j.comnet.2025.111402","url":null,"abstract":"<div><div>In the Internet of Vehicles (IoV) with dense interference, overlapping coverage between vehicle user equipments’ communication radius (VUEs) leads to significant interference, causing resource reuse conflicts between transmission links. To address this, we construct an interference hypergraph model to analyze the interference relationships among multiple users through hyperedges. The degree of interference for the overall network is calculated using this model. The optimization problem for resource allocation is then formulated to minimize the data rate so that multiple quality of service (QoS) requirements are met at the same time while considering interference degree. Furthermore, a novel conflict graph model is constructed to represent the conflicts among transmission links. This model is then transformed into a conflict hypergraph structure, enabling a more comprehensive and accurate depiction of complex interference relationships within the network. We convert the combinatorial optimization problem for radio resource allocation into a Markov decision process (MDP) model. For IoV with dense interference, we employ a federated averaging-deep Q-Network (FedAvg-DQN) algorithm to enhance the transmission rate and overall network throughput. Consequently, the experimental findings demonstrate that this method can significantly enhance the anti-interference capacity of the system in a densely interfered Internet of Vehicles (IoV) environment. Specifically, compared to the benchmark algorithm, network throughput is on average increased by 28.17<span><math><mtext>%</mtext></math></span>, and energy efficiency is on average improved by 24.85<span><math><mtext>%</mtext></math></span>. These improvements effectively accelerate the information transmission rate and guarantee the reliability of the information transmission. These findings validate the efficacy and practicality of the developed approach, demonstrating its potential to enhance the performance of IoV systems under challenging interference conditions.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111402"},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metaversal intelligence: Unifying human-AI interactions in human-in-the-loop AIB-Metaverse","authors":"Minoo Soltanshahi,&nbsp;Martin Maier","doi":"10.1016/j.comnet.2025.111425","DOIUrl":"10.1016/j.comnet.2025.111425","url":null,"abstract":"<div><div>The convergence of 6G and Web 3 technologies with the Metaverse necessitates user-centric, intelligent solutions to address challenges of adaptability, scalability, and efficiency in decentralized systems. This paper introduces the Human-AI Blockchain (HAIB) Metaverse architecture and the Intelligent Smart Contract (InSC) framework, which integrate Reinforcement Learning (RL) and extended stigmergy to optimize multi-agent interactions and enable dynamic, self-executing smart contracts. The HAIB architecture enhances human-AI collaboration through a human-in-the-loop approach, facilitating adaptive decision-making and efficient resource allocation. Serving as the cognitive core, the InSC framework combines dynamic environmental feedback with real-time data analytics to enable intelligent decision-making. Experimental evaluations demonstrate that the proposed framework reduces gas consumption by 32–33% while increasing cumulative rewards. These findings highlight the significant potential of intelligent smart contracts in advancing decentralized intelligence within the Metaverse.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111425"},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DBSRP-ML: Dynamic blockchain sharding reconfiguration protocol based on multi-label","authors":"Hui Dai ,&nbsp;Lingyun Yuan ,&nbsp;Jiaying Wu ,&nbsp;Han Chen ,&nbsp;Haochen Bao","doi":"10.1016/j.comnet.2025.111401","DOIUrl":"10.1016/j.comnet.2025.111401","url":null,"abstract":"<div><div>Sharding provides an effective approach to improving the scalability of blockchain. To address the problems of cross-shard transaction proliferation, transaction latency increase, and load imbalance caused by the improper allocation of shardings, we propose a dynamic blockchain sharding reconfiguration protocol based on multi-label (DBSRP-ML). First, the account state sharding model based on the label graph network is constructed, which achieves the fine-grained correlation analysis and efficient management of the topology of the account transaction network by decoupling and reconstructing the account states. Second, we propose the account label multiplication mechanism to enable efficient mapping between accounts and shards. Third, we propose the multi-label account sharding partition algorithm (MLASPA) to optimize the sharding configuration according to the optimal sharding belonging coefficient of accounts, which enhances the degree of accurate sharding matching, thus minimizing the number of cross-shard transactions. Experimental results show that compared with other sharding protocols, DBSRP-ML improves the system throughput by 50% and up to 268%, reduces the latency by 72.8% to 88%, reduces the cross-shard ratio by up to 70%, and displays excellent workload balancing. The proposed protocol improves the scalability of the blockchain, thereby optimizing its overall performance.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111401"},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144240464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An effective data dissemination method in WAIC networks using enhanced CTC","authors":"Tao Cheng ,&nbsp;Shining Li ,&nbsp;Weiwei Dang ,&nbsp;Yan Pan","doi":"10.1016/j.comnet.2025.111399","DOIUrl":"10.1016/j.comnet.2025.111399","url":null,"abstract":"<div><div>By introducing wireless technology into aircraft systems, Wireless Avionics Intra-Communication (WAIC) networks aim to enhance the efficiency and flexibility of onboard operations. Rather than replacing traditional wired systems, WAIC enables the seamless coexistence of heterogeneous wireless nodes to address diverse application requirements, with a particular focus on efficient network management and time-critical data transmission. This paper proposes an effective data dissemination method leveraging cross-technology communication (CTC) to achieve direct data delivery from high-speed gateways to multi-hop field nodes in coexisting hybrid WAIC subnets. The proposed model relies on the efficiency of CTC and its effective transmission capability in multi-hop networks. We introduce an optimized signal emulation method inspired by power-domain non-orthogonal multiple access (PD-NOMA) in 5G, which superimposes multiple signals to improve emulation accuracy from 802.11g to 802.15.4. We also develop a multi-hop CTC link quality evaluation model, providing a comprehensive analysis of reception performance across varying hop counts. Based on these advancements, we design a coordinated data dissemination method that exploits the high-gain propagation and direct communication capabilities of CTC, significantly reducing the latency of multi-hop relaying. Extensive experimental results demonstrate the effectiveness of the proposed hybrid model. In a typical setting, it achieves a 3.18<span><math><mo>×</mo></math></span> reduction in the maximum network dissemination delay and a 2.83<span><math><mo>×</mo></math></span> decrease in the average dissemination delay, compared to traditional hop-by-hop transmissions.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111399"},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cache-INT: In-network caching-enabled In-band Network Telemetry","authors":"Penghui Zhang ,&nbsp;Hua Zhang ,&nbsp;Yuqi Dai ,&nbsp;Yibo Pi ,&nbsp;Jingyu Wang ,&nbsp;Jianxin Liao","doi":"10.1016/j.comnet.2025.111404","DOIUrl":"10.1016/j.comnet.2025.111404","url":null,"abstract":"<div><div>Due to its powerful monitoring capabilities, In-band Network Telemetry (INT) technology has become essential to modern network management. However, a key challenge lies in reducing the redundant telemetry data transmission from the data plane to the controller, a vital process for real-time network status monitoring and swift decision-making. This challenge, if not properly addressed, could significantly waste network bandwidth and increase the controller’s response time.</div><div>In this paper, we present Cache-INT, a highly efficient in-network caching-enabled INT system. Specifically, Cache-INT stores and reuses network information collected by probes through a well-designed cache strategy, and uses the incremental transmission technique to reduce the volume of data transmitted. Furthermore, an INT system’s performance depends heavily on probe path planning, which determines both the network coverage and control overhead. We optimize these factors in two scenarios: one with fixed cache-enabled routers, and the other allowing for flexible selection of cache-enabled routers. For the former, we use a Deep Reinforcement Learning (DRL)-based algorithm to minimize control overhead and design a mask function to speed up training. For the latter, we combine the simulated annealing algorithm and the DRL model to find a suitable cache-enabled router upgrade scheme, and then plan the probe paths accordingly.</div><div>The experimental results show that, compared to existing INT systems, Cache-INT reduces the data transmission volume from the data plane to the controller by at least 40% while achieving a 30% reduction in control overhead.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111404"},"PeriodicalIF":4.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative delay analysis of GI/G/1 queues with heavy-tailed traffic by means of Alpha Theory","authors":"Francesco Fiorini,&nbsp;Marco Cococcioni,&nbsp;Michele Pagano","doi":"10.1016/j.comnet.2025.111394","DOIUrl":"10.1016/j.comnet.2025.111394","url":null,"abstract":"<div><div>The GI/G/1 queue represents a versatile and crucial model for various telecommunication and computer systems applications, but its mathematical complexity makes it difficult to analyse its steady-state behaviour. As an alternative, bounds and approximations for the stationary mean delay have been proposed. However, when dealing with heavy-tailed traffic, even the use of these latter methods becomes problematic. Due to divergent second-order moments, they provide uninformative intervals or indeterminate/divergent estimates, and are therefore unfeasible or useless. This paper presents a new analytical methodology based on Alpha Theory, a development of NonStandard Analysis, to overcome these limitations. Our approach extends classical delay bounds and approximations tools, enabling direct numerical applicability even in challenging scenarios with infinite second-order moments. Additionally, utilizing recently introduced <em>Bounded Algorithmic Numbers</em> (a fixed-length representation format for numbers containing infinite and infinitesimal values, other than finite ones), a discrete-event simulation of the queue is presented. Various simulative tests, under several heavy-tailed traffic conditions and different scheduling policies, are carried out to investigate the behaviour of the queue in terms of mean delay. The obtained results agree with theoretical predictions, even in the case of infinite values. The implementation turns out to be accurate, ensuring satisfying convergence speed and numerical stability.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111394"},"PeriodicalIF":4.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DRAFTEE: A self-adaptive framework for BFT-based consensus to meet fluctuating throughput demands under security constraint","authors":"Guilain Leduc ,&nbsp;Sylvain Kubler ,&nbsp;Jean-Philippe Georges","doi":"10.1016/j.comnet.2025.111396","DOIUrl":"10.1016/j.comnet.2025.111396","url":null,"abstract":"<div><div>Byzantine Fault Tolerance (BFT) consensus protocols are known not to scale to a number of participants as large as mainstream public blockchain solutions. This is due to the way transactions are validated, which is performed by a leader that acts as a bottleneck and cause performance limitations. In BFT-based blockchain systems, a significant challenge involves effectively managing the trade-off between security and throughput performance. This trade-off suggests that while a higher number of validators enhances system security, it also diminishes throughput performance, and vice versa. Traditionally, blockchain systems fix the number of validators during the design phase, which lacks flexibility in adjusting the validator pool in real-time to optimize the aforementioned trade-off. This article presents DRAFTEE, a self-adaptive framework for BFT-based consensus designed to continuously regulate the validator pool to meet transaction throughput demands while upholding security requirements. DRAFTEE’s control mechanism involves determining the optimum number of validators at any given time and selecting the most suitable nodes to minimize network latency, while meeting the users’ (transaction) demand. DRAFTEE is implemented and experimentally evaluated (through simulation and Grid5000). The results demonstrate significantly improved performance, equivalent to double the previous maximum throughput demand with same number of validators. Moreover, the implementation allows for a remarkable increase, up to 250%, in the number of validators maintaining equivalent service quality. This optimization allows to increase the minimal number of validators, while preserving throughput demand.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111396"},"PeriodicalIF":4.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SMASH: An SDN-MTD framework for efficient honeypot deployment and insider threat mitigation","authors":"Nicola d’Ambrosio,&nbsp;Claudio Lista,&nbsp;Gaetano Perrone,&nbsp;Simon Pietro Romano","doi":"10.1016/j.comnet.2025.111327","DOIUrl":"10.1016/j.comnet.2025.111327","url":null,"abstract":"<div><div>Conventional cybersecurity tools, such as firewalls and Intrusion Prevention Systems, have been widely employed to protect against digital threats. However, these approaches reveal their inherent limitations as the complexity and sophistication of cyberattacks increase. Consequently, there is a growing demand for more proactive and adaptive cyber-defense strategies. Deception-based techniques, such as Moving Target Defense (MTD) and honeypots, have emerged as powerful approaches to enhance security by confusing and misleading attackers. Despite their potential, deploying these solutions in large-scale network infrastructures poses significant challenges. Manual configuration of honeypots is time-consuming, resource-intensive, and difficult to scale. Moreover, it is mandatory to ensure that honeypots do not become a pivot for attackers to penetrate the enterprise network infrastructure further. To address these issues, we propose “Sdn-Mtd Automated System with Honeypot integration” (SMASH), a framework that leverages Software Defined Networking (SDN) principles in conjunction with MTD and decoy techniques. Following a Design Science approach, we designed, implemented, and evaluated SMASH to overcome these deployment and management challenges. SMASH not only makes it more difficult for attackers to target the production network infrastructure, but also provides valuable real-time threat intelligence by observing attacker behavior. When an intrusion attempt is detected, MTD techniques redirect the attacker to an isolated subnet dedicated to threat monitoring, preventing access to sensitive systems and data. Furthermore, SMASH introduces a flexible and scalable management system that allows automatic deployment, setup, and real-time monitoring of honeypots. This dynamic adaptability allows organizations to scale their defenses in response to evolving threats, significantly enhancing the security posture of real-world enterprise environments.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111327"},"PeriodicalIF":4.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"dApps: Enabling real-time AI-based Open RAN control","authors":"Andrea Lacava ,&nbsp;Leonardo Bonati ,&nbsp;Niloofar Mohamadi ,&nbsp;Rajeev Gangula ,&nbsp;Florian Kaltenberger ,&nbsp;Pedram Johari ,&nbsp;Salvatore D’Oro ,&nbsp;Francesca Cuomo ,&nbsp;Michele Polese ,&nbsp;Tommaso Melodia","doi":"10.1016/j.comnet.2025.111342","DOIUrl":"10.1016/j.comnet.2025.111342","url":null,"abstract":"<div><div>Open Radio Access Networks (RANs) leverage disaggregated and programmable RAN functions and open interfaces to enable closed-loop, data-driven radio resource management. This is performed through custom intelligent applications on the RAN Intelligent Controllers (RICs), optimizing RAN policy scheduling, network slicing, user session management, and medium access control, among others. In this context, we have proposed dApps as a key extension of the O-RAN architecture into the real-time and user-plane domains. Deployed directly on RAN nodes, dApps access data otherwise unavailable to RICs due to privacy or timing constraints, enabling the execution of control actions within shorter time intervals. In this paper, we propose for the first time a reference architecture for dApps, defining their life cycle from deployment by the Service Management and Orchestration (SMO) to real-time control loop interactions with the RAN nodes where they are hosted. We introduce a new dApp interface, E3, along with an Application Protocol (AP) that supports structured message exchanges and extensible communication for various service models. By bridging E3 with the existing O-RAN E2 interface, we enable dApps, xApps, and rApps to coexist and coordinate. These applications can then collaborate on complex use cases and employ hierarchical control to resolve shared resource conflicts. Finally, we present and open-source a dApp framework based on OpenAirInterface (OAI). We benchmark its performance in two real-time control use cases, i.e., spectrum sharing and positioning in a 5th generation (5G) Next Generation Node Base (gNB) scenario. Our experimental results show that standardized real-time control loops via dApps are feasible, achieving average control latency below 450<!--> <!-->microseconds and allowing optimal use of shared spectral resources.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111342"},"PeriodicalIF":4.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the unseen: Robust IP geolocation through the lens of uncertainty quantification","authors":"Xueting Liu ,&nbsp;Xiaohan Wang ,&nbsp;Chao Li ,&nbsp;Joojo Walker ,&nbsp;Wenxin Tai ,&nbsp;Ting Zhong ,&nbsp;Yong Wang ,&nbsp;Fan Zhou ,&nbsp;Kai Chen","doi":"10.1016/j.comnet.2025.111405","DOIUrl":"10.1016/j.comnet.2025.111405","url":null,"abstract":"<div><div>Accurate IP geolocation is critical for applications such as network security, content delivery, and fraud detection, yet existing methods face significant challenges in dynamic environments with fluctuating network conditions. In this work, we present EBGeo (Energy-Based IP Geolocation), a novel framework that combines graph convolutional networks (GCNs) and energy function optimization with Monte Carlo sampling to address these challenges. The proposed framework introduces three key innovations: (1) GCNs, which model the spatial and topological relationships between IPs and are well suited to the IP geolocation task by capturing complex dependencies in network structures; (2) energy-based optimization, which leverages energy function optimization with Monte Carlo sampling to simulate dynamic network conditions during training, thereby enhancing the model’s accuracy and robustness; and (3) gradient ascent for inference, which improves the model’s adaptability under fluctuating network conditions. Uncertainty quantification (UQ) is used to evaluate how well the model adapts to network changes. Lower UQ values indicate that the model is less sensitive to variations in network conditions. UQ further enables a deeper understanding of the model’s adaptability to changing network conditions, making EBGeo a powerful tool for addressing network challenges in real-world applications.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111405"},"PeriodicalIF":4.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144240465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}