Computer Networks最新文献

{"title":"Doubling the speed of large-scale packet classification through compressing decision tree nodes","authors":"Jincheng Zhong ,&nbsp;Tao Li ,&nbsp;Gaofeng Lv ,&nbsp;Shuhui Chen","doi":"10.1016/j.comnet.2026.112032","DOIUrl":"10.1016/j.comnet.2026.112032","url":null,"abstract":"<div><div>Packet classification underpins critical network functions such as access control and quality of service. While decision tree-based approaches offer efficiency and scalability, their classification performance is often bottlenecked by excessive memory accesses during tree traversal-primarily due to the use of pointer-based indexing structures necessitated by large node sizes.</div><div>This paper proposes a general pointer-elimination paradigm via Extreme Node Compression (ENC). This enables indexing structures to store nodes directly rather than pointers, thereby eliminating one memory indirection per level and nearly halving the number of memory accesses per lookup. To validate this core idea, this paper designs TupleTree-Compress based on state-of-the-art hash-based decision tree scheme-TupleTree. TupleTree-Compress integrates three key techniques-a unified global hash table, fingerprint-based keys, and hash-based sibling linking-to achieve full node compression while preserving correctness and update support.</div><div>Furthermore, to demonstrate the generality of our approach, we apply the same optimization paradigm to state-of-the-art classical decision tree scheme-CutSplit, resulting in CutSplit-Compress. Experimental results show that TupleTree-Compress achieves speedups of <strong>2.24</strong> × –<strong>3.12</strong> ×  over TupleTree and <strong>1.43</strong> × –<strong>1.91</strong> ×  over DBTable-the current best-performing scheme. Similarly, CutSplit-Compress achieves speedups of <strong>3.19</strong> × –<strong>3.64</strong> ×  over CutSplit, with improvements up to <strong>1.58</strong> ×  over DBTable.</div><div>Our work demonstrates that aggressive node compression is a powerful and generalizable strategy for boosting packet classification performance, offering a promising direction for optimizing decision tree-based schemes.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112032"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039292","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":"SGICPNOM: A computation offloading mechanism for 6G space-ground integrated computing power network","authors":"Yi Xiao ,&nbsp;Xiaolong Xu","doi":"10.1016/j.comnet.2026.112082","DOIUrl":"10.1016/j.comnet.2026.112082","url":null,"abstract":"<div><div>The Space-Air-Ground Integrated Computing Power Network (SGICPN) faces significant challenges in computation offloading, primarily stemming from the dynamic mobility of Low Earth Orbit (LEO) satellites, heterogeneous resource constraints, stringent Quality of Experience (QoE) requirements, and the lack of effective satellite-terrestrial coordination mechanisms. Existing approaches suffer from inflexible resource allocation, inadequate adaptation to satellite coverage dynamics, neglect of user-centric energy-latency tradeoffs, and absence of coordinated satellite-ground collaboration. To address these challenges, we propose SGICPNOM, a novel computation offloading mechanism featuring three key innovations: 1) A battery-level-driven adaptive weighting strategy that dynamically optimizes latency-energy coefficients to enhance user satisfaction across diverse device states. 2) A unified optimization framework that jointly considers LEO satellite mobility, time-varying coverage patterns, and remote cloud data center resources to enable efficient multi-layer task partitioning. 3) An enhanced multi-agent deep reinforcement learning (MADRL) approach incorporating Prioritized Experience Replay (PER) and hybrid centralized-distributed training, with final allocation decisions refined through our load-aware satellite-cloud coordination mechanism. Results from real environment simulations demonstrate that, compared with state-of-the-art methods, such as Multi-Agent Deep Deterministic Policy Gradient (MADDPG), game-theoretic approaches, hierarchical reinforcement learning, and graph reinforcement learning solutions, SGICPNOM achieves an approximate 22.7% reduction in the weighted sum of latency and energy consumption, while exhibiting strong robustness. The system maintains stability under high network loads while improving overall utilization of both satellite and cloud computing resources, sustaining task success rates above 89%. These results validate SGICPNOM’s potential to advance computation offloading technologies in next-generation SGICPN.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112082"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398144","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 prototypical alignment approach to unknown traffic classification using BERT","authors":"Minho Cho ,&nbsp;Yongseok Kwon ,&nbsp;Seyoung Ahn ,&nbsp;Sunwon Kwon ,&nbsp;Sunghyun Cho","doi":"10.1016/j.comnet.2026.112062","DOIUrl":"10.1016/j.comnet.2026.112062","url":null,"abstract":"<div><div>As encrypted internet traffic continues to increase, classifying previously unseen traffic has become a major challenge in real-world network environments. Traditional traffic classification models are designed for closed-world scenarios and struggle to process novel traffic types. To address this in real-world network environments, coarse-grained classification approaches have been proposed, which assign all unknown traffic to a single <em>”unknown”</em> class. However, this coarse-grained labeling limits the model’s ability to perform the fine-grained classification of diverse and encrypted traffic behaviors. To address this, we propose Unknown Traffic Prototypical Alignment Bidirectional encoder representations from transformers (UT-PAB), a semi-supervised learning framework for the fine-grained classification of unknown traffic in open-world scenarios. UT-PAB operates in two phases: (1) a pre-training phase that learns general traffic patterns through supervised and masked token prediction tasks, and (2) a fine-tuning phase that refines representations using contrastive learning and prototype-based supervision. These two phases enable the model to cluster unknown traffic by semantic similarity without relying on protocol-specific features. We evaluated the effectiveness of UT-PAB on two benchmark datasets, ISCX-VPN and USTC-TFC, by comparing it against baseline methods based on clustering and representation learning. We conducted extensive experiments on two benchmark datasets across various unknown traffic ratios and demonstrated that the proposed method outperformed state-of-the-art methods by a minimum of 10.63%p and a maximum of 75.34%p improvement in overall accuracy.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112062"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398148","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":"Real-time SARIMA-based anomaly detection in operator networks","authors":"Pablo Fondo-Ferreiro ,&nbsp;Miguel Rodelgo-Lacruz ,&nbsp;Francisco Javier González-Castaño ,&nbsp;Felipe Gil-Castiñeira ,&nbsp;Carlos Zamorano-Pinal ,&nbsp;David Candal-Ventureira","doi":"10.1016/j.comnet.2026.112070","DOIUrl":"10.1016/j.comnet.2026.112070","url":null,"abstract":"<div><div>The growing complexity of telecommunication networks increases the need for automated monitoring and detection of incidents. The increasing amount of data generated by current information and communication technologies equipment can be used to identify abnormal behavior and detect anomalies. In this paper, we propose a volume-based real-time solution for anomaly detection in operator networks. The proposal is based on a seasonal autoregressive integrated moving average (SARIMA) forecasting of time-series data, and the identification of outliers. We validate the proposed solution using real traffic traces from a nationwide operator’s network which we make publicly available. Our experimental results show that the proposed solution outperforms baseline approaches in terms of precision, being able to substantially reduce the amount of false positives, while maintaining the same level of recall.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112070"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398082","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":"Energy-aware holistic optimization in UAV-assisted fog computing: Attitude, trajectory, and task assignment","authors":"Shuaijun Liu ,&nbsp;Jinqiu Du ,&nbsp;Yaxin Zheng ,&nbsp;Jiaying Yin ,&nbsp;Yuhui Deng ,&nbsp;Jingjin Wu","doi":"10.1016/j.comnet.2026.112064","DOIUrl":"10.1016/j.comnet.2026.112064","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs) have significantly enhanced fog computing by acting as both flexible computation platforms and communication mobile relays. In this paper, we consider four important and interdependent modules: attitude control, trajectory planning, resource allocation, and task assignment, and propose a holistic framework that jointly optimizes the total latency and energy consumption for UAV-assisted fog computing in a three-dimensional spatial domain with varying terrain elevations and dynamic task generations. We first establish a fuzzy-enhanced adaptive reinforcement proportional-integral-derivative control model to control the attitude. Then, we propose an enhanced Ant Colony System (ACS) based algorithm, that includes a safety value and a decoupling mechanism to overcome the convergence issue in classical ACS, to compute the optimal UAV trajectory. Finally, we design an algorithm based on the Particle Swarm Optimization technique, to determine where each offloaded task should be executed. Under our proposed framework, the outcome of one module would affect the decision-making in another, providing a holistic perspective of the system and thus leading to improved solutions. We demonstrate by extensive simulation results that our proposed framework can significantly improve the overall performance, measured by latency and energy consumption, compared to existing mainstream approaches.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112064"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398145","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":"Threshold-based eavesdropper detection for partial intercept-resend attack in noisy BB84 quantum key distribution","authors":"Francesco Fiorini,&nbsp;Rosario G. Garroppo,&nbsp;Michele Pagano","doi":"10.1016/j.comnet.2026.112058","DOIUrl":"10.1016/j.comnet.2026.112058","url":null,"abstract":"<div><div>Quantum Key Distribution (QKD) protocols are critical for ensuring secure communication against the threats posed by post-quantum technologies. Among these, the BB84 protocol remains the most widely studied and implemented QKD scheme, providing a foundation for secure communication based on the principles of quantum mechanics. This paper investigates the BB84 protocol under a partial intercept-resend attack in a realistic scenario that accounts for system noise. In this context, existing attack detection methods rely on estimating the quantum bit error rate (QBER) in the portion of key bits exchanged over the classical channel to identify the attack. The proposed approach introduces a novel scheme in which the two communicating parties agree on the maximum fraction of shared key bits that can be correctly intercepted by the attacker. This parameter can be configured according to the security requirements of the application. The paper first presents the theoretical model for computing this parameter, which is subsequently used to develop a threshold-based detection method. Unlike other detection methods for intercept-resend attacks, the proposed scheme is independent of the interception density and relies solely on the system noise and the application’s security requirements. Finally, an enhanced version of the Python Quantum Solver library is implemented to test the proposed method using the Qiskit framework. Simulation results demonstrate the high accuracy and very low false negative rate of the proposed method, with a slight degradation in performance observed when the actual interception rate approaches the threshold defined by the security requirements.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112058"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090324","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":"Energy-efficient swarm intelligence-based resource allocation scheme for 5G-HCRAN","authors":"Tejas Kishor Patil,&nbsp;Paramveer Kumar,&nbsp;Pavan Kumar Mishra,&nbsp;Sudhakar Pandey","doi":"10.1016/j.comnet.2026.112034","DOIUrl":"10.1016/j.comnet.2026.112034","url":null,"abstract":"<div><div>The rapid evolution of 5G-HCRAN (Heterogeneous Cloud Radio Access Network) necessitates innovative resource allocation schemes to meet diverse user demands while optimizing energy efficiency. This research introduces a novel resource allocation scheme explicitly designed for 5G-HCRAN, emphasizing the maximization of throughput and energy efficiency. The proposed methodology employs a hybrid Particle Swarm Optimization-Ant Colony Optimization (PSO-ACO) scheme that combines the strengths of both Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to achieve a more efficient and effective optimization process. PSO contributes its global search capability via particle-based solution updates, while ACO introduces a pheromone-driven decision mechanism that smoothly adapts to dynamic network conditions. By integrating these complementary behaviors, the hybrid PSO-ACO scheme can evaluate resource-allocation choices more consistently and respond more effectively to network variability. This combined strategy supports more efficient utilization of limited network resources and significantly improves 5G-HCRAN performance. Simulation results validate the superiority of the proposed hybrid resource allocation scheme over standalone methods, demonstrating significant improvements in throughput and better energy efficiency. By addressing the objectives, the proposed hybrid scheme provides a practical and scalable approach for the next generation 5G-HCRAN.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112034"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090322","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 comprehensive approach for the onboarding, orchestration, and validation of network applications","authors":"Rafael Direito ,&nbsp;Kostis Trantzas ,&nbsp;Jorge Gallego-Madrid ,&nbsp;Ana Hermosilla ,&nbsp;Diogo Gomes ,&nbsp;Christos Tranoris ,&nbsp;Rui L.A. Aguiar ,&nbsp;Antonio Skarmeta ,&nbsp;Spyros Denazis","doi":"10.1016/j.comnet.2026.112057","DOIUrl":"10.1016/j.comnet.2026.112057","url":null,"abstract":"<div><div>The advent of 5G and Beyond 5G networks has propelled the development of innovative applications and services that harness network programmability, data from management and control interfaces, and the capabilities of network slicing. However, ensuring these applications function as intended and effectively utilize 5G/B5G capabilities remains a challenge, mainly due to their reliance on complex interactions with control plane Network Functions. This work addresses this issue by proposing a novel architecture to enhance the onboarding, orchestration, and validation of 5G/B5G-capable applications and services, while enabling the creation of application-tailored network slices. By integrating DevOps principles into the NFV ecosystem, the proposed architecture automates workflows for deployment, testing, and validation, while adhering to standardized onboarding models and continuous integration practices. Furthermore, we also address the realization of such architecture into a platform that supports extensive testing across multiple dimensions, including 5G readiness, security, performance, scalability, and availability. Besides introducing such a platform, this work also demonstrates its feasibility through the orchestration and validation of an automotive application that manages virtual On-Board Units within a 5G-enabled environment. The obtained results underscore the effectiveness of the proposed architecture, as well as the performance and scalability of the platform that materializes it. By integrating DevOps principles, our work aids in reducing deployment complexity, automating testing and validation, and enhancing the reliability of next-generation Network Applications, therefore accelerating their time-to-market.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112057"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090328","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":"MASRP: A mobility-assisted service routing protocol for task-oriented flying ad-hoc networks","authors":"Yanbo Wang,&nbsp;Wang Yang,&nbsp;Tao Yang,&nbsp;Lihuan Hui,&nbsp;Jianwei Yao","doi":"10.1016/j.comnet.2025.111986","DOIUrl":"10.1016/j.comnet.2025.111986","url":null,"abstract":"<div><div>Task-driven unmanned aerial vehicle (UAV) networks, as a special type of flying ad hoc network (FANET), are designed to accomplish cooperative tasks through dynamic inter-UAV communication. However, the high mobility and sparse topology of such networks often lead to routing holes and intermittent connectivity, posing significant challenges for reliable data delivery. To address this challenge, we propose MASRP, a mobility-assisted service routing protocol. MASRP introduces service-aware announcements that enable nodes to obtain information about the service capabilities of other nodes in the network. It also employs a two-phase forwarding strategy to reduce communication overhead and leverages UAV mobility to recover broken routes. Extensive simulation results demonstrate that MASRP improves service response ratio by up to 88% under sparse density, achieves around 90% higher completion rate under high requester load, offers approximately 22% higher reliability under heterogeneous service-type distributions, and reduces traffic consumption per successful response by about 24%.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 111986"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145963380","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":"LTGAT: A lightweight temporal graph attention accelerator for deterministic routing in resource-constrained delay-tolerant non-terrestrial networks","authors":"Dalia I. Elewaily ,&nbsp;Ahmed I. Saleh ,&nbsp;Hesham A. Ali ,&nbsp;Mohamed M. Abdelsalam","doi":"10.1016/j.comnet.2026.112035","DOIUrl":"10.1016/j.comnet.2026.112035","url":null,"abstract":"<div><div>This paper introduces the Lightweight Temporal Graph Attention (LTGAT) model, with the primary aim of developing an efficient routing solution to enhance Delay-Tolerant Networking (DTN) performance in resource-constrained non-terrestrial environments. The primary motivation is to overcome the limitations of traditional deterministic routing methods, such as Contact Graph Routing (CGR), which suffer from significant computational overhead in large-scale time-varying topologies, due to their reliance on repeated contact graph searches. The proposed LTGAT achieves this by integrating a lightweight architecture that combines a two-head Graph Attention Network (GAT) and a Gated Recurrent Unit (GRU) to learn the complex representation of the known spatial-temporal structure in the scheduled contact plan, enabling fast routing decisions with minimal computational and energy demands. The significance of this work is validated through experiments across six realistic simulated lunar scenarios, where LTGAT demonstrates a substantial reduction in delivery times by up to 32 % compared to CGR, with processing times scaled to 105.445–286.712 ms on a Proton 200k On-Board Computer, reflecting improvements up to 89.9–91.0 % over CGR and 22.6–40.2 % over GAUSS. Additionally, LTGAT achieves energy consumption of 15.82–43.01 mJ per routing decision, and preserves CGR’s perfect delivery reliability by achieving a delivery ratio of 1.0 on bundles that CGR itself successfully processes, far outperforming GAUSS (0.25 - 0.85) on the same bundles, while recovering 29–100 % of the bundles that CGR drops. These results confirm LTGAT’s suitability for resource-limited CubeSat deployments. This research contributes a lightweight, computation-efficient routing framework, offering a critical advancement for resource-constrained non-terrestrial communication systems and providing a foundation for future interplanetary network studies.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"277 ","pages":"Article 112035"},"PeriodicalIF":4.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039705","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}