Computer Networks最新文献

{"title":"Machine learning approaches for predicting link failures in production networks","authors":"Bruck W. Wubete,&nbsp;Babak Esfandiari,&nbsp;Thomas Kunz","doi":"10.1016/j.comnet.2025.111098","DOIUrl":"10.1016/j.comnet.2025.111098","url":null,"abstract":"<div><div>Resolving network failures after they occur through human investigation is a costly and time-consuming process. Predicting upcoming failures could mitigate this to a large extent. In this work, we collect data from a large intercontinental network and study the problem of flapping links, which are indicative of link failures. Such flapping links have their routing metric increased to divert traffic away; this is followed by corrective actions, and eventually their routing metric is lowered again to carry traffic. Using the collected data, primarily metrics reported from Internet Protocol (IP) and optical layers of the network, we develop ML models to predict upcoming link failures. Exploring a sequence of increasingly complex models, we study the relevance of optical metrics, the underlying temporal relations, and the topological relations in improving the predictive model performance. We discovered that optical features such as optical maximum and minimum power or unavailable and errored seconds increased the model’s performance (measured in average precision) by about 9 percentage points while temporal and spatial features improved it further by 8 and 7 percentage points respectively for a total improvement of 24 percentage points.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111098"},"PeriodicalIF":4.4,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387867","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":"EVFL-DCs: Enhancing verifiability of federated learning by double commitments based on blockchain","authors":"Qianjin Wei ,&nbsp;Xuanjing Wu ,&nbsp;Zhiquan Liu ,&nbsp;Gang Rao","doi":"10.1016/j.comnet.2025.111097","DOIUrl":"10.1016/j.comnet.2025.111097","url":null,"abstract":"<div><div>In decentralized federated learning networks, the presence of malicious users can lead to distrust among participants, significantly undermining the efficiency of model training. Polynomial commitment techniques map gradients into polynomials and have been widely used in decentralized federated learning schemes. However, existing schemes have yet to address the consistency issue between noisy or masked gradients and their corresponding commitments, specifically the verification of whether a commitment is derived from the original gradient of the noisy or masked gradient. To address this issue, this paper proposes an Enhancing Verifiability and Privacy-Preserving of Federated Learning by Double Commitments based on Blockchain (EVFL-DCs). This scheme addresses the consistency issue between noisy gradients and commitments by designing two commitments based on the statistical properties of differential privacy. In the verification committee, the Central Limit Theorem (CLT) is used to constrain the difference between a noisy gradient and the double commitments, ensuring their consistency. Additionally, the scheme achieves lossless aggregation by aggregating masked gradients. Given that attackers may upload masked gradients inconsistent with their signature commitments, a grouped verification mechanism is introduced. This mechanism refines the scope of consistency verification between masked gradients and commitments by performing aggregation within groups and verifying the consistency of the aggregated gradients and commitments for each group. Even if the verification fails for a particular group, the results of the other groups remain unaffected, thereby ensuring the correctness of the overall aggregation result. Experimental results demonstrate that EVFL-DCs effectively verifies the consistency between noisy or masked gradients and their commitments. Moreover, when the proportion of deceptive attackers is less than 30%, the model’s accuracy is nearly identical to that of a decentralized federated learning scheme without attackers. Furthermore, even when noise impacts the gradients, the accuracy of filtering benign noisy gradients is close to that of filtering benign original gradients.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"260 ","pages":"Article 111097"},"PeriodicalIF":4.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429406","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":"Enhancing Extended Reality Assisted Surgery through a Field-of-View Video Delivery Optimization","authors":"Daria Alekseeva ,&nbsp;Anzhelika Mezina ,&nbsp;Radim Burget ,&nbsp;Otso Arponen ,&nbsp;Elena Simona Lohan ,&nbsp;Aleksandr Ometov","doi":"10.1016/j.comnet.2025.111093","DOIUrl":"10.1016/j.comnet.2025.111093","url":null,"abstract":"<div><div>Emerging Extended Reality (XR) applications bring new opportunities for digital healthcare systems, i.e., eHealth. XR-assisted surgery is one of the most outstanding examples of future technology that has a high social impact on the healthcare and medical educational system. The current work presents the intelligent design for remote XR-assisted surgery. The study presents the Field-of-View (FoV)-based viewport model empowered with behavioral data. It applies the viewport prediction model based on the behavioral data by applying Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). In the final analysis, LSTM showed lower errors and a higher coefficient of determination, but ANN performed much faster. Finally, the study defines the dynamic system’s states for adaptive and fast video delivery concerning Quality of Experience (QoE). The presented approach aims to mitigate the delay to ensure smooth playback and display high-quality images.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111093"},"PeriodicalIF":4.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KTWIN: A serverless Kubernetes-based Digital Twin platform","authors":"Alexandre Gustavo Wermann,&nbsp;Juliano Araujo Wickboldt","doi":"10.1016/j.comnet.2025.111095","DOIUrl":"10.1016/j.comnet.2025.111095","url":null,"abstract":"<div><div>Digital Twins (DTs) systems are virtual representations of physical assets allowing organizations to gain insights and improve existing processes. In practice, DTs require proper modeling, coherent development and seamless deployment along cloud and edge landscapes relying on established patterns to reduce operational costs. In this work, we propose KTWIN a Kubernetes-based Serverless Platform for Digital Twins. KTWIN was developed using the state-of-the-art open-source Cloud Native tools, allowing DT operators to easily define models through open standards and configure details of the underlying services and infrastructure. The experiments carried out with the developed prototype show that KTWIN can provide a higher level of abstraction to model and deploy a Digital Twin use case without compromising the solution scalability. The tests performed also show cost savings ranging between 60% and 80% compared to overprovisioned scenarios.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111095"},"PeriodicalIF":4.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395925","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":"Mx-TORU: Location-aware multi-hop task offloading and resource optimization protocol for connected vehicle networks","authors":"Oğuzhan Akyıldız ,&nbsp;Feyza Yıldırım Okay ,&nbsp;İbrahim Kök ,&nbsp;Suat Özdemir","doi":"10.1016/j.comnet.2025.111094","DOIUrl":"10.1016/j.comnet.2025.111094","url":null,"abstract":"<div><div>Connected Vehicle Networks (CVNs), as a part of Internet of Vehicles (IoV), represent an innovative solution for enhancing communication between vehicles and Internet of Things (IoT) devices within transportation infrastructures. However, task offloading in CVNs presents significant challenges due to high computational demands and the dynamic nature of network conditions. While traditional static fog networks support CVNs, they often suffer from inefficiencies in resource allocation, leading to underutilization or over-utilization, as well as elevated maintenance costs. To address these limitations, mobile fog computing emerges as a more adaptable solution, enabling efficient task processing by leveraging the resources of nearby vehicles. In this paper, we introduce a novel mobility-driven protocol, Mx-TORU, which combines multi-hop task offloading with resource optimization to enhance task processing efficiency in CVNs. This protocol builds upon our previously proposed MobTORU framework, aiming to maximize resource utilization through dynamic multi-hop strategies. Extensive experiments using real-world vehicular mobility data demonstrate that Mx-TORU improves resource utilization by up to 17.8% compared to one-hop methods. Additionally, our Mx-TORU protocol and the employed RELiOff algorithm show a consistent improvement of at least 5% in task offloading efficiency across various test scenarios including intelligent transformation systems.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111094"},"PeriodicalIF":4.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372267","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 cost-efficient traffic engineering framework with various pricing schemes in clouds","authors":"Jingzhou Wang ,&nbsp;Gongming Zhao ,&nbsp;Hongli Xu ,&nbsp;Chunming Qiao ,&nbsp;He Huang","doi":"10.1016/j.comnet.2025.111090","DOIUrl":"10.1016/j.comnet.2025.111090","url":null,"abstract":"<div><div>The rapid growth of cloud services has brought a significant increase in inter-datacenter traffic. To transfer data among geographically distributed datacenters, cloud providers need to purchase bandwidth from ISPs. The data transferring cost has become one of the major expenses for cloud providers. Therefore, it is essential for a cloud provider to carefully allocate inter-datacenter traffic among the ISPs’ links to minimize the costs. Exiting solutions mainly focus on the situations where all links adopt the same pricing scheme. However, in practice, ISPs usually provide multiple pricing schemes for their links due to market competition, which makes the existing solutions non-optimal. Thus, a new traffic engineering approach that considers various pricing schemes is needed. This paper presents COIN, a new framework for cost-efficient traffic engineering with various pricing schemes. We propose a partition rounding traffic engineering algorithm based on linear independence analysis. The approximation factors and time complexity are formally analyzed. We further conduct large-scale simulations with real-world topologies and datasets. Extensive simulation results show that COIN can save the data transferring cost by up to 63.4% compared with the state-of-the-art solutions.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111090"},"PeriodicalIF":4.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387868","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":"Federated dual correction intrusion detection system: Efficient aggregation for heterogeneous data","authors":"Zhigang Jin ,&nbsp;Yu Ding ,&nbsp;Xiaodong Wu ,&nbsp;Xuyang Chen ,&nbsp;Zepei Liu ,&nbsp;Gen Li","doi":"10.1016/j.comnet.2025.111116","DOIUrl":"10.1016/j.comnet.2025.111116","url":null,"abstract":"<div><div>Federated learning-based intrusion detection system (FL-IDS) can effectively ensure global security without the concerns of data privacy, becoming the primary defense method for distributed networks. However, the inherent challenge of heterogeneous data in FL brings client drift to IDS. Besides, the dynamic learning of FL further aggravates model bias caused by the sparsity of malicious traffic. Therefore, we propose a federated dual correction intrusion detection system called FIST-G2 to optimize global aggregation. In the first correction, a momentum-like update mechanism with gradient memory is proposed to solve the client drift. Specifically, with the gradient memory buffer, we leverage the current updated gradient change, historical information, and global information to fix the momentum factor used in global model update. We propose gradient memory buffering strategy in this mechanism to dynamically maintain the information of each client, particularly the records of stragglers. In the second correction, a fine-tuning mechanism with GAN boundary samples is proposed to alleviate the model bias. A generator, deployed on the server, which extracts local models’ knowledge by data-free knowledge distillation, is used to supplement rare traffic. By forming an adversarial training pattern instead of direct data balancing, a GAN boundary samples mining scheme is introduced to keep the ambiguity of samples to improve global model constantly. Extensive experiments on UNSW-NB15 dataset and CICIDS2018 dataset show that the proposed method is robust for heterogeneous data and completely compatible with many client-side optimization algorithms, having excellent scalability and portability.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111116"},"PeriodicalIF":4.4,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387959","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":"PoVF: Empowering decentralized blockchain systems with verifiable function consensus","authors":"Chenxi Xiong,&nbsp;Ting Yang,&nbsp;Yu Wang,&nbsp;Bing Dong","doi":"10.1016/j.comnet.2025.111092","DOIUrl":"10.1016/j.comnet.2025.111092","url":null,"abstract":"<div><div>Consensus mechanism is the core technology for blockchain to ensure that transactions are executed in sequence. It also determines the decentralization, security, and efficiency of blockchain. Existing mechanisms all have certain centralization issues and fail to ensure the decentralization of blockchain networks. A decentralized and efficient mechanism is required to improve blockchain systems. This paper proposes a fair consensus mechanism called Proof of Verifiable Functions (PoVF), based on the verifiability and unpredictability of verifiable functions. PoVF provides a sufficiently fair mechanism, ensuring that all nodes in blockchain network have equal opportunity to participate in consensus. In addition, a structure called ”Delay buffer” is proposed to ensure transactions are executed sequentially. It delay the selection of blocks to avoid blockchain forks caused by broadcasting and transaction execution confusion. According to our security analysis, PoVF is provably secure and has the ability to resist potential adversaries. According to the experiments, PoVF-based blockchain can process up to <span><math><mrow><mn>4</mn><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>3</mn></mrow></msup></mrow></math></span> transactions per second with nodes configured with only 4-core CPUs. This paper uses the Gini coefficient to measure the decentralization of blockchains, and the PoVF-based blockchain achieves the lowest Gini coefficient of 0.39 among all sampled blockchains. PoVF has been shown to provide sufficient efficiency while ensuring decentralization and security through experiments.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111092"},"PeriodicalIF":4.4,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377753","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":"Reunion: Receiver-driven network load balancing mechanism in AI training clusters","authors":"Mingyao Wang ,&nbsp;Keqiang He ,&nbsp;Peirui Cao ,&nbsp;Jiong Duan ,&nbsp;Dongliang Lv ,&nbsp;Zehao Yu ,&nbsp;Yanqing Chen ,&nbsp;Chengyuan Huang ,&nbsp;Wanchun Dou ,&nbsp;Guihai Chen ,&nbsp;Chen Tian","doi":"10.1016/j.comnet.2025.111088","DOIUrl":"10.1016/j.comnet.2025.111088","url":null,"abstract":"<div><div>RDMA over Converged Ethernet (RoCEv2) enables high-performance networking for large-scale model training but faces challenges due to traffic characteristics such as elephant flows, low entropy, and traffic bursts. Conventional load-balancing techniques like ECMP struggle with hash collisions, causing increased tail latency. Advanced solutions, such as source routing and enhanced ECMP, mitigate these issues but still have hash collisions when there are multiple sources. While packet spraying and flow slicing help alleviate load imbalances due to hash collisions, they can intensify packet reordering issues. Reunion, a novel mechanism for RoCEv2 environments, tackles three critical challenges of flowlet-based rerouting: (1) Rerouting decisions introduce new hash conflicts; (2) The out-of-order packets caused by rerouting has a significant impact on small flows; (3) Setting appropriate flowlet timeout values in high-bandwidth environments is difficult. By utilizing Count-Min-Sketch to filter out small flows and aggregating real-time congestion data, Reunion enables source switches to make dynamic rerouting decisions for elephant flows, minimizing congestion hotspots. Simulations conducted using NS-3 highlight Reunion’s robustness and effectiveness in reducing tail latency. Under varying network loads, Reunion outperforms existing load-balancing schemes such as Conga, LetFlow, ECMP, and ConWeave, achieving tail latency reductions ranging from 10.9% to 62.1%.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111088"},"PeriodicalIF":4.4,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349368","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":"Towards Open RAN in beyond 5G networks: Evolution, architectures, deployments, spectrum, prototypes, and performance assessment","authors":"Alexandru Martian ,&nbsp;Razvan-Florentin Trifan ,&nbsp;Teodora-Cristina Stoian ,&nbsp;Marius-Constantin Vochin ,&nbsp;Frank Y. Li","doi":"10.1016/j.comnet.2025.111087","DOIUrl":"10.1016/j.comnet.2025.111087","url":null,"abstract":"<div><div>Along the evolution of mobile communication systems during the past decades from 1st generation (1G) to 5th generation (5G), radio access networks (RANs) have been traditionally implemented and deployed based on vendor-specific hardware and proprietary software. In recent years, there is a surge of interests and efforts among mobile network operators (MNOs) in developing RAN solutions based on <em>open interfaces</em> to facilitate flexible operations and versatile functionalities of RANs using reconfigurable hardware and inter-operable software. In the meantime, various industrial and academic stakeholders are keen on developing open-source driven RAN solutions based on commercial-off-the-shelf (COTS) hardware like software defined radio (SDR). In this article, we convey a comprehensive and systematic study on Open RAN technologies spanning from the theories (from RAN evolution to Open RAN architecture) and the concepts (from disaggregation and functional split to Open RAN architectures), to commercial and prototype deployments as well as implementation platforms. In addition to an in-depth comparison between the 3rd generation partnership project (3GPP) and Open RAN Alliance (O-RAN) interfaces and functions, we shed light on the spectrum allocation aspects for Open RAN deployment covering both public and private 5G networks. Furthermore, this article presents two prototype 5G networks that we have developed based on COTS hardware and open-source software suites as well as the configuration and performance of these prototype proof-of-concept on-campus networks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"259 ","pages":"Article 111087"},"PeriodicalIF":4.4,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143295560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}