Computer Networks最新文献

{"title":"Resource allocation for UAV-RIS-assisted RSMA system with hardware impairments","authors":"Habtamu Demeke Mihertie,&nbsp;Zhengqiang Wang","doi":"10.1016/j.comnet.2025.111336","DOIUrl":"10.1016/j.comnet.2025.111336","url":null,"abstract":"<div><div>The convergence of intelligent reflecting surfaces (IRS), unmanned aerial vehicle (UAV) communication systems, and rate-splitting multiple access (RSMA) heralds a transformative advancement in wireless communication technology. In this paper, we integrate these three pivotal technologies to maximize fairness in downlink hardware-impaired networks. Specifically, we deploy a UAV-mounted IRS to serve single-antenna users from a multiple-antenna base station (BS) with RSMA protocol. This novel approach introduces significant complexity due to the strong coupling of the optimization variables and non-convex nature of the problem. Our study seeks to optimize IRS phase shifts, IRS location, precoding, transmit power, and common rate allocation using a block coordinate decomposition approach. This methodology strives to achieve an equitable distribution of resources among users while accounting for hardware impairments and leveraging the benefits of IRS and RSMA technologies. The coupling of variables makes the optimization problem highly non-convex, significantly increasing its complexity and making the quest for an optimal solution formidable. To address this challenge, we employ successive convex approximation (SCA) and penalty dual decomposition (PDD) methods to handle the non-convex problem and decompose the coupled optimization variables. These approaches facilitate effective exploration of the optimization space while considering the intricate coupling of variables. We propose efficient algorithms for each subproblem. Simulation results demonstrate that RSMA markedly enhances performance in highly impaired networks, leading to improved network performance, better user experience, robust, and efficient resource utilization.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111336"},"PeriodicalIF":4.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931412","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":"Modeling and performance evaluation of OpenFlow switches using a MAP/PH/1/n queueing model","authors":"Virendra Singh Shekhawat ,&nbsp;Rakhee Kulshrestha ,&nbsp;Pooja Yadav ,&nbsp;Ajay Singh ,&nbsp;Farhaan Firdous","doi":"10.1016/j.comnet.2025.111338","DOIUrl":"10.1016/j.comnet.2025.111338","url":null,"abstract":"<div><div>Software-Defined Networking (SDN) is a paradigm shift in network architecture. It decouples the control plane from the data plane to enable centralized network management and programmability. While Software Defined Networks (SDNs) offer significant advantages by efficient traffic management, it also introduces complexities that require comprehensive network modeling to predict and optimize network behavior before actual deployment. Queueing models provide a mathematical framework for analyzing and predicting how data packets behave as they traverse network devices. This paper presents a discrete-time MAP/PH/1/n queueing model to assess the performance of SDNs in handling complex and bursty traffic patterns. The model integrates packet processing at different switch components, including the switch buffer, ingress processing unit, and egress processing unit. It utilizes a finite buffer queue model with Markovian Arrival Process (MAP) and Phase-Type (PH) service times to capture data transmission behavior at an OpenFlow switch. The matrix geometric method is employed to calculate steady-state probabilities, which helps in evaluating Quality of Service (QoS) metrics such as average delay, throughput, and blocking probabilities. In addition, the mathematical model formulates performance measures, including probabilities for packet forwarding, packet drop, and packets redirected to the controller. We validated our model’s outcomes by conducting packet-based simulations using Mininet and the Ryu controller. The graphs obtained from both the mathematical model and the packet simulations demonstrate qualitatively similar behavior of the OpenFlow switch across different traffic rates, buffer sizes, and service rates.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111338"},"PeriodicalIF":4.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934684","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":"MoTor: Resource-efficient cloud-native network acceleration with programmable switches","authors":"Hongyang Chen ,&nbsp;Pengfei Chen ,&nbsp;Zilong He ,&nbsp;Zibin Zheng ,&nbsp;Kaibin Fang","doi":"10.1016/j.comnet.2025.111335","DOIUrl":"10.1016/j.comnet.2025.111335","url":null,"abstract":"<div><div>With the rapid increase in the number of services and the frequency of service invocations in distributed cloud-native applications, the volume of inter-service communication traffic in these applications has grown significantly over the years. As a result, cloud-native network, especially, inter-service communication, is crucial for maintaining the overall performance of cloud-native applications. However, our study indicates that extra intricate network processing induced by packet transmission imposes substantial overhead on inter-service communication. Therefore, we propose <span>MoTor</span>, a programmable switch-assisted network solution to accelerate cloud-native network in a resource-efficient way. The core idea of <span>MoTor</span> is to minimize network processing overhead by offloading essential network functions from the CPU to programmable switches. <span>MoTor</span> utilizes eBPF to enable non-intrusive network bypassing and forward inter-service traffic to the switch directly. The switch is then leveraged to perform critical network functions required for inter-service communication. To address the memory constraints of programmable switches, <span>MoTor</span> introduces a table entry prediction algorithm and a no memory-cost per connection consistency (PCC) preservation strategy. The evaluation results show that <span>MoTor</span> achieves salient performance and resource gains while maintaining PCC. Specifically, <span>MoTor</span> improves application’s throughput by up to 1.66<span><math><mo>×</mo></math></span> and reduces latency by up to 62.3% without any code modifications. Although other programmable switch-assisted solutions offer performance improvement comparable to <span>MoTor</span>, they require additional host or switch resources. In contrast, the PCC preservation strategy and prediction algorithm in <span>MoTor</span> enable simultaneous reductions in both host and switch resource consumption. Specifically,it reduces CPU and memory usage by up to 55% and up to 70%, respectively, compared to existing network solutions, while lowering the switch’s memory consumption by 60%.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111335"},"PeriodicalIF":4.4,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923430","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":"A blockchain-based resource sharing incentivization mechanism for multi-to-multi in compute first networking","authors":"Peng Liu,&nbsp;Zixu Zhang,&nbsp;Chenhao Ren,&nbsp;Hailong You","doi":"10.1016/j.comnet.2025.111318","DOIUrl":"10.1016/j.comnet.2025.111318","url":null,"abstract":"<div><div>The explosive growth of data and the rapid development of algorithms have placed increasing demands on computing power. Compute first networking (CFN) can connect cloud, edge and terminal resources and meet the ubiquitous resource demands, becoming an important technology for future computing power development. However, the application premise of CFN is the resource sharing between different entities, but selfish users are usually unwilling to share their own resources. Therefore, how to motivate more users to participate in resource sharing and jointly maintain the CFN is an important issue. In this paper, we designed an incentive mechanism that considers both security, user privacy, fair pricing, and resource allocation schemes to maximize the utilities for both parties. Firstly, we design a resource trading system based on layered blockchain to ensure system security and user privacy. Secondly, the incentive process is modeled considering both supply–demand relationships, pricing and resource allocation strategies. The model is then split into two sub-problems of supply–demand matching and resource trading. An optimization method based on reinforcement learning is proposed to solve complex multi-to-multi matching problems. The resource trading process is modeled as a more realistic multi-to-multi Stackelberg game problem, the Nash equilibrium point is obtained to maximize the utilities of both parties through the game process of supply and demand. Simulations and security analysis show that the incentive method proposed in this paper is able to ensure data security and user privacy, while achieving the goal of motivating users to participate in resource sharing with lower costs.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111318"},"PeriodicalIF":4.4,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907712","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":"From Crowds to Coordinates: A user density-distance dynamic transformation method for Telegram users geolocalization","authors":"Yiyang Shi ,&nbsp;Xiangyang Luo ,&nbsp;Wenqi Shi","doi":"10.1016/j.comnet.2025.111316","DOIUrl":"10.1016/j.comnet.2025.111316","url":null,"abstract":"<div><div>Telegram is a widely used instant messaging service with over 900 million monthly active users. Research on the geolocalization of Telegram users helps verify the platform’s privacy protection and aids in cybercrime investigations. Existing location methods struggle with Telegram’s characteristics, such as large granularity changes in reported distances and irregular user turnover, making direct geolocalization challenging. This paper presents a new geolocalization method for Telegram users based on user density-distance dynamic transformation (U3DT). Unlike traditional methods, U3DT integrates distance breaks caused by reported distance changes and varying user densities to assess actual user distance, dynamically deploying probes for precise positioning. By analyzing changes in reported distances and user densities, we establish a relationship between discontinuity points and user densities. The geolocalization process determines the target’s real distance using dynamically set probes and corresponding user densities. Finally, we address the selection of datum points in trilateration based on discontinuity points. Experimental results on the Telegram platform show that U3DT achieves high geolocalization accuracy, with an average deviation of 223 meters and a maximum error of 450 meters. Compared to existing methods like RRABG, ETBG, and HNBG, U3DT reduces the average error by 60.4 % to 71.2 %.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111316"},"PeriodicalIF":4.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923431","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":"GPT on the wire: Towards realistic network traffic conversations generated with large language models","authors":"Javier Aday Delgado-Soto,&nbsp;Jorge E. López de Vergara,&nbsp;Iván González,&nbsp;Daniel Perdices,&nbsp;Luis de Pedro","doi":"10.1016/j.comnet.2025.111308","DOIUrl":"10.1016/j.comnet.2025.111308","url":null,"abstract":"<div><div>Realistic network traffic generation is essential for evaluating the performance, security, and scalability of modern communication systems. Traditional methods, such as traffic replay systems and statistical models, while useful, often fall short in capturing the complexity and variability of real-world network scenarios. Recent advancements in Artificial Intelligence (AI), especially Large Language Models (LLMs) like ChatGPT, have introduced new approaches to synthetic traffic generation. This paper presents a novel architecture using OpenAI’s GPT-3.5 Turbo to generate synthetic network traffic, with a focus on creating multi-protocol conversations that are indistinguishable from real-world interactions. Through fine-tuning and prompt engineering, the proposed system successfully generates packet- and conversation-level network traffic for ICMP, ARP, DNS, TCP and HTTP protocols. Additionally, by integrating a Mixture of Experts (MoE) architecture, this model simulates real-world network conversations with high accuracy, being able to generate a conversation combining ARP, DNS, TCP and HTTP without packet or protocol errors. The results show how the application of LLMs in network traffic generation improves realism and adaptability, establishing this approach as a valuable tool for future security testing and network performance evaluation. In addition, the proposed methodology is easily adaptable to other LLMs available both through APIs and to be downloaded and executed on your own computer.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"265 ","pages":"Article 111308"},"PeriodicalIF":4.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895538","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":"VECLLF: A vehicle-edge collaborative lifelong learning framework for anomaly detection in VANETs","authors":"Yingqing Wang ,&nbsp;Yanhua Liang ,&nbsp;Yue Huang ,&nbsp;Guihe Qin","doi":"10.1016/j.comnet.2025.111328","DOIUrl":"10.1016/j.comnet.2025.111328","url":null,"abstract":"<div><div>With the rapid development of intelligent connected vehicles, Vehicular Ad Hoc Network (VANET) is widely used in intelligent transportation systems. VANETs are vulnerable to attacks in their operating environments, such as denial of service (DoS) attacks and injection attacks. Thus, the development of an efficient anomaly detection framework is a promising solution. Most existing methods can only detect known attacks, are less efficient in detecting unknown attacks, and fail to deal with them. To solve these problems, the lifelong learning framework (LLF) is introduced, which aims to store and label suspicious data by applying blockchain and then retrain the model. However, existing LLFs are overly idealized as they do not adequately consider the key issues of label budget and storage space. To improve the practicality of existing methods, this paper proposes a novel LLF based on the existing LLF, called Vehicle Edge Collaborative Lifelong Learning Framework (VECLLF), which can deploy the model update task on the edge server. Specifically, the proposed anomaly detection module based on ensemble active learning is used to achieve high-performance detection under a limited label budget, the proposed incremental learning module based on a sample library continuously learns the model by replaying representative samples within limited storage space, the proposed optimization-based feature selection module is used to remove redundant and interfering features, and the explainable artificial intelligence (XAI) module is used to explain the model to ensure its interpretability. In addition, the blockchain-based database (BC-DB) module is used to help store suspicious data and interact with security agencies to label it. We conducted experiments on two public datasets, AWID2 and CICIDS2017, and the results show that VECLLF outperforms state-of-the-art anomaly detection models and existing LLF, with F1-scores exceeding 97% on both datasets. Furthermore, we collect data from the Network Simulator 3 (NS-3) simulation environment and conduct experiments to evaluate the effectiveness of VECLLF in real-world scenarios.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"265 ","pages":"Article 111328"},"PeriodicalIF":4.4,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891573","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":"Transmission design for uplink multi-group MIMO–NOMA with finite blocklength","authors":"Yuan Yin ,&nbsp;Yiyang Zhang ,&nbsp;Jiaheng Wang ,&nbsp;Ningxing Shen ,&nbsp;Jianli Guo ,&nbsp;Kang Zheng","doi":"10.1016/j.comnet.2025.111313","DOIUrl":"10.1016/j.comnet.2025.111313","url":null,"abstract":"<div><div>Non-orthogonal multiple access (NOMA) with multiple-input multiple-output (MIMO) is one of the promising candidates to support massive connectivity and improve spectral efficiency for wireless communications. To apply MIMO–NOMA in practical applications, finite blocklength has to be considered. In this article, we explore the finite blocklength transmission design for uplink MIMO–NOMA with group successive interference cancellation (GSIC). We employ the effective throughput as the performance metric to balance the transmission rate and error performance in the finite blocklength regime. To maximize the system effective throughput, we formulate a joint optimization problem of the precoding vectors, equalization vectors, and transmission rates. Since this joint resource allocation is complex and non-convex, we decompose it into two subproblems, i.e., the joint transceiver design and transmission rate adaptation. We first propose an effective algorithm based on the principles of successive convex approximation (SCA) and alternating optimization to provide a joint transceiver design. Then, we derive a semi-closed-form solution of the optimal transmission rates and develop an iterative algorithm to adapt the transmission rates for all the users. Finally, we propose a joint resource allocation algorithm based on block coordinate descent (BCD). Simulation results demonstrate the performance gains by optimizing the transceiver design and transmission rates, which proves the superiority of the proposed algorithm.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"266 ","pages":"Article 111313"},"PeriodicalIF":4.4,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913293","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":"MFTE: Multifactor and fuzzy trust evaluation for federated learning in mobile edge computing","authors":"Minglong Cheng ,&nbsp;Wei Chen ,&nbsp;Weidong Fang ,&nbsp;Zehua Wang ,&nbsp;Tingting Xu ,&nbsp;Jueting Liu ,&nbsp;Victor C.M. Leung","doi":"10.1016/j.comnet.2025.111340","DOIUrl":"10.1016/j.comnet.2025.111340","url":null,"abstract":"<div><div>Federated learning effectively mitigates privacy leakage issues in mobile edge computing by implementing collaborative training without data sharing, but it also poses challenges to the trust and security of the terminal nodes. There is little research on trust evaluation in federated learning, and existing studies have overlooked the influence of data and reputation trust generated by third-party recommendations. To address these issues, a trust evaluation scheme for federated learning terminal nodes based on multifactor and fuzzy is proposed, incorporating factors such as node behavior, node reliability, and reputation trust. By integrating the current trust and historical trust to obtain the direct trust of terminal nodes and combining it with the reputation trust generated by edge nodes, a comprehensive trust is derived. On this basis, a reputation trust filtering model based on T-S fuzzy logic is proposed to address dishonest recommendations and the uncertainty of reputation trust resulting from malicious attacks. The similarity, timeliness, and external trust of recommendations are analyzed, and fuzzy inference is used to filter dishonest recommendations. The experimental results demonstrate that the proposed scheme can rapidly identify malicious nodes, accurately evaluate node trustworthiness, and effectively filter out dishonest recommendations. Compared with the state-of-the-art scheme, the proposed scheme demonstrates improvements in evaluation accuracy and robustness.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"265 ","pages":"Article 111340"},"PeriodicalIF":4.4,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143903468","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":"Region-based coordination for distributed resource allocation in sidelink mesh networks","authors":"Yawen Chang ,&nbsp;Lei Lei ,&nbsp;Xudong Wang","doi":"10.1016/j.comnet.2025.111315","DOIUrl":"10.1016/j.comnet.2025.111315","url":null,"abstract":"<div><div>Sidelink mesh networking enables multi-hop transmission between user equipments (UEs), which can support emerging Internet-of-things (IoT) applications. In 5G standards, two resource allocation schemes (Mode 1 and Mode 2) are supported for sidelink transmission, but they are unsuitable for sidelink mesh networks. The centralized scheme Mode 1 only works for in-coverage sidelink, which also lacks scalability and adaptability. The distributed scheme Mode 2 overcomes the limitations of Mode 1, but it suffers resource conflict and performance degradation due to its random-access nature. To avoid resource conflict and enhance network performance, coordination among UEs is needed to support distributed resource allocation, yet how to achieve high coordination efficiency and compatibility with 5G standards remains an open problem. To this end, a region-based distributed resource allocation method (RODA) is proposed for sidelink mesh networks. The main idea is that an allocation region contains an allocator, its neighbors as allocatees, and the links between these nodes, where the allocator conducts resource allocation for its inner-region links. Particularly, an allocator determination mechanism is devised to form regions that cover all links in the network. A conflict elimination is developed to avoid resource conflict among regions with interfering links. A resource allocation mechanism is designed to allocate orthogonal and fair resources for inner-region links. A resource notification mechanism is developed to achieve compatibility with 5G standards and coexistence with Mode 2. Extensive simulations validate effectiveness and efficiency of RODA, and also demonstrate its significant throughput and fairness gain over the baseline schemes.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"265 ","pages":"Article 111315"},"PeriodicalIF":4.4,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888029","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}