Computer Networks最新文献_第3页

Multi-objective optimization model and algorithm for network slicing with demand exceeding resources 需求超过资源的网络切片多目标优化模型与算法

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-18 DOI: 10.1016/j.comnet.2025.111460

Wei Guo, Xiaoli Wang, Yuping Wang

{"title":"Multi-objective optimization model and algorithm for network slicing with demand exceeding resources","authors":"Wei Guo, Xiaoli Wang, Yuping Wang","doi":"10.1016/j.comnet.2025.111460","DOIUrl":"10.1016/j.comnet.2025.111460","url":null,"abstract":"<div><div>Network slicing allocation is a new kind of task and resource scheduling technique for 5G and 6G networks and provides the high quality service by allocating the limited infrastructure network resources to massive heterogeneous user requests (various network slices). Currently, most existing studies only consider the situation that infrastructure network resources can meet the demands of all users. However, with the quick increase of network users, the infrastructure network resources usually cannot satisfy the demands of all users. To tackle this problem, this paper designs a two-objective optimization model to maximize the service provider revenue and the user experience. To solve the model effectively, a new evolutionary algorithm based on NSGA-II framework is proposed, in which the tailor-made encoding scheme, decoding scheme and evolutionary operators are designed, respectively. The simulation results indicate that the proposed algorithm can provide diverse resource allocation solutions and is superior in scenarios where the user resource demands exceed the total available resources in the infrastructure network.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111460"},"PeriodicalIF":4.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471152","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}

引用次数: 0

IPO-ZTA: An Intelligent Policy Orchestration Zero Trust Architecture for B5G and 6G IPO-ZTA: B5G和6G智能策略编排零信任架构

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-18 DOI: 10.1016/j.comnet.2025.111450

Yulong Fu , Yuanqi Xie , Wei Yi , Bikal Poudel , Jin Cao , Hui Li

{"title":"IPO-ZTA: An Intelligent Policy Orchestration Zero Trust Architecture for B5G and 6G","authors":"Yulong Fu , Yuanqi Xie , Wei Yi , Bikal Poudel , Jin Cao , Hui Li","doi":"10.1016/j.comnet.2025.111450","DOIUrl":"10.1016/j.comnet.2025.111450","url":null,"abstract":"<div><div>As 5G and 6G networks become more complex and diverse, traditional security models based on trust boundaries face significant challenges. Zero Trust Architecture (ZTA), with its core principle of “never trust, always verify”, offers a potential solution for securing these dynamic networks. However, due to the vast and complex nature of B5G and 6G, how to achieve the “zero trust” concept in a high dynamic and service oriented systems are still lack of discussion, which limits the developing of ZTA in B5G and 6G, and the network’s ability to respond effectively to emerging threats are also inappropriate. In this article, we proposed an Intelligent Policy Orchestration Zero Trust Architecture (IPO-ZTA), which combines 6G Integrated Sensing and Communication (ISAC) capabilities with AI/ML techniques to predict security requirements and dynamically adjust fine grained security policies to fill this gap. The proposed framework introduces two AI-driven components: one that predicts security demands based on real-time network data and another that adjusts security policies based on these predictions. Additionally, we present a modular 3GPP security capability library that enhances the accuracy and flexibility of policy execution. Our research shows that IPO-ZTA improves the adaptability and efficiency of security policies in real-time while fully aligning with the core Zero Trust principles defined by 3GPP for the next generation networks.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111450"},"PeriodicalIF":4.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314466","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}

引用次数: 0

Coffee: Cost-effective edge caching for live 360 degree video streaming 咖啡：具有成本效益的边缘缓存，用于实时360度视频流

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-18 DOI: 10.1016/j.comnet.2025.111461

Chen Li , Tingwei Ye , Tongyu Zong , Liyang Sun , Houwei Cao , Yong Liu

{"title":"Coffee: Cost-effective edge caching for live 360 degree video streaming","authors":"Chen Li , Tingwei Ye , Tongyu Zong , Liyang Sun , Houwei Cao , Yong Liu","doi":"10.1016/j.comnet.2025.111461","DOIUrl":"10.1016/j.comnet.2025.111461","url":null,"abstract":"<div><div>While live 360 degree video streaming delivers immersive viewing experience, it poses significant bandwidth and latency challenges for content delivery networks. Edge servers are expected to play an important role in facilitating live streaming of 360 degree videos. In this paper, we propose a novel predictive edge caching framework (Coffee) for live 360 degree video that employs collaborative FoV prediction and predictive tile prefetching to reduce bandwidth consumption and streaming cost, and improve streaming quality and robustness. By utilizing the viewers’ playback latency gaps and exploiting the unique tile consumption patterns of live 360 degree video streaming, our efficient caching algorithms achieve substantial tile caching gains. Through extensive experiments driven by real 360 degree video streaming traces, we demonstrate that edge caching algorithms specifically designed for live 360 degree video streaming can achieve high streaming cost savings with small edge cache space consumption. Coffee, guided by viewer FoV predictions, significantly reduces backhaul traffic by 76% compared to state-of-the-art live 360 edge caching algorithms. In addition, we design a transcoding-aware edge caching variant, called TransCoffee. We assess TransCoffee through extensive experiments, which reveal that it can reduce costs by 63% compared to cutting-edge transcoding-aware methods.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111461"},"PeriodicalIF":4.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502233","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}

引用次数: 0

FLCom: Robust federated learning against strong model poisoning attacks FLCom：针对强模型中毒攻击的鲁棒联邦学习

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-17 DOI: 10.1016/j.comnet.2025.111442

Yang Li , Jun Xu , Dejun Yang

{"title":"FLCom: Robust federated learning against strong model poisoning attacks","authors":"Yang Li , Jun Xu , Dejun Yang","doi":"10.1016/j.comnet.2025.111442","DOIUrl":"10.1016/j.comnet.2025.111442","url":null,"abstract":"<div><div>Federated learning (FL) is an emerging distributed machine learning framework that enables models to be trained on multiple decentralized devices or servers without transferring data to a centralized server. However, due to its distributed nature, FL is vulnerable to attacks from malicious clients. Although most Byzantine-robust FL methods are designed against model poisoning attacks, they lose effectiveness as the intensity of attacks increases or when new attack strategies emerge. To address these challenges, we propose a novel robust FL method, called FLCom, which leverages outlier detection to defend against model poisoning attacks. FLCom enhances the robustness of FL and outperforms the state-of-the-art methods in accuracy. Additionally, we propose an improved model poisoning attack, called vector-scaling attack (VSA), which exhibits stronger stealthiness against robust aggregation methods. We evaluate both our defense and attack methods under IID and Non-IID settings across three different datasets. The results demonstrate that FLCom achieves higher accuracy than other methods under various attacks, particularly in the Non-IID case. Furthermore, FLCom effectively defends against our proposed VSA, while VSA successfully breaches existing defense mechanisms.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111442"},"PeriodicalIF":4.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322618","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}

引用次数: 0

DCDTS: Deterministic cross-domain transmission and scheduling for large-scale deterministic networks DCDTS：大规模确定性网络的确定性跨域传输和调度

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-17 DOI: 10.1016/j.comnet.2025.111434

Xu Huang , Jia Chen , Deyun Gao , Shang Liu , Shangbing Qiao , Hongke Zhang

{"title":"DCDTS: Deterministic cross-domain transmission and scheduling for large-scale deterministic networks","authors":"Xu Huang , Jia Chen , Deyun Gao , Shang Liu , Shangbing Qiao , Hongke Zhang","doi":"10.1016/j.comnet.2025.111434","DOIUrl":"10.1016/j.comnet.2025.111434","url":null,"abstract":"<div><div>Deterministic Networking (DetNet) is emerging to support the deterministic transmission in the Large-scale Deterministic Networks (LDNs). Recent proposals focus on the cooperation of different shaping mechanisms in Time Sensitive Networks (TSN) and DetNet to achieve the deterministic cross-domain in LDNs. However, the queue overflow caused by multi-domain access and the uncontrolled micro bursts during cross-domain remain challenges. To address this dilemma, a deterministic cross-domain scheme for LDNs is essential. In this paper, we design the Deterministic Cross-Domain Transmission and Scheduling (DCDTS), where the deterministic cross-domain cycle mapping scheme is proposed to fulfill the one-to-one cycle mapping between different domains and the cooperation of mechanisms in TSN and DetNet. In addition, we propose the Cyclic Queuing Clusters Forwarding (CQCF) mechanism to solve the effect of micro bursts during transmission in cross-domain and DetNet domains. Furthermore, we design the Hybrid Greedy-DDQN-based Traffic Scheduling (HGDTS) algorithm, which integrates the greedy and double deep Q-network into a two-step scheduling. The prototype and simulation experiments show that CQCF outperforms DIP in the number of successfully scheduled flows by approximately 22.4%. Moreover, HGDTS improves the schedulability, resource utilization, and convergence speed compared to the six baseline algorithms.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111434"},"PeriodicalIF":4.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480669","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}

引用次数: 0

5G-GRAKA: An efficient group based authentication and key agreement protocol for machine-type communication in 5G networks 5G- graka：一种高效的基于组的认证和密钥协议，用于5G网络中机器类型的通信

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-17 DOI: 10.1016/j.comnet.2025.111435

Ronghao Ma , Jianhong Zhou , Maode Ma

{"title":"5G-GRAKA: An efficient group based authentication and key agreement protocol for machine-type communication in 5G networks","authors":"Ronghao Ma , Jianhong Zhou , Maode Ma","doi":"10.1016/j.comnet.2025.111435","DOIUrl":"10.1016/j.comnet.2025.111435","url":null,"abstract":"<div><div>Massive machine type communication (mMTC) is one of the important parts of the fifth-generation (5G) cellular wireless network. In order to meet the security requirements of 5G wireless networks, 3GPP has introduced an authentication and key agreement (AKA) protocol named 5G-AKA; however, it is still inefficient for the mMTC scenario where numerous devices attempt to connect to the network simultaneously. In this paper, we propose a new group-based AKA protocol, which authenticates multiple MTC devices (MTCDs) simultaneously while maintaining consistency with the 5G-AKA framework to ensure security. Specifically, we design a group authentication and key negotiation algorithm based on the challenge-response mechanism used in 5G-AKA protocol and dynamically managed group members to facilitate group authentication. This approach effectively reduces the volume of interactive messages, alleviates signaling congestion, and simultaneously completes key negotiation for multiple MTCDs. The ability of the proposed protocol against significant malicious attacks has been rigorously validated by the deviation of BAN logic and formally verified by the Random Oracle Model (ROM) and the Scyther tool, highlighting its robust security attributes. Extensive simulation experimental results have demonstrated the security, efficiency, and effectiveness of proposed protocol.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"270 ","pages":"Article 111435"},"PeriodicalIF":4.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517252","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}

引用次数: 0

Dependent task offloading in multi-access edge computing: A GCN augmented deep reinforcement learning approach 多访问边缘计算中的相关任务卸载：一种GCN增强深度强化学习方法

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-17 DOI: 10.1016/j.comnet.2025.111445

Liqiong Chen, Xinyuan Yang, Huaiying Sun, Xiuchao Yu, Kaiwen Zhi

{"title":"Dependent task offloading in multi-access edge computing: A GCN augmented deep reinforcement learning approach","authors":"Liqiong Chen, Xinyuan Yang, Huaiying Sun, Xiuchao Yu, Kaiwen Zhi","doi":"10.1016/j.comnet.2025.111445","DOIUrl":"10.1016/j.comnet.2025.111445","url":null,"abstract":"<div><div>Multi-access edge computing (MEC) is a promising distributed computing paradigm that reduces the delayed energy cost (DECC) of users by offloading user-generated application tasks to the network edge. Most of the user-generated tasks contain a series of subtasks with dependencies, how to effectively offload these interdependent tasks and reduce DECC is a key issue. In addition, most existing learning-based approaches are inadequate in dynamically modeling MEC environments and cannot effectively characterize heterogeneous MEC environments. To this end, this paper models the multiuser task offloading problem as a Markov Decision Process (MDP). First, to address the challenges of heterogeneous MEC environments, we propose a multi-dependent task offloading algorithm with state embeddings. This algorithm uses commonality and dissimilarity components to capture the interactions between user and the MEC environment, providing robust state representation. Secondly, we introduce the strategy gradient theorem of the Stackelberg game to optimize the offloading decision. Finally, extensive experiments show that our proposed method significantly reduces DECC compared to existing methods.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111445"},"PeriodicalIF":4.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337929","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}

引用次数: 0

An adaptive deep learning-based user authentication with digitally signed optimal key-aided encryption for secured mobile edge computing data storage in blockchain 基于自适应深度学习的用户身份验证与数字签名的最佳密钥辅助加密，用于b区块链中安全的移动边缘计算数据存储

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-16 DOI: 10.1016/j.comnet.2025.111482

Khaled M. Matrouk , Arunmozhi Selvi , Ahmad Yahiya Ahmad Bani Ahmad , Dhurgadevi M

{"title":"An adaptive deep learning-based user authentication with digitally signed optimal key-aided encryption for secured mobile edge computing data storage in blockchain","authors":"Khaled M. Matrouk , Arunmozhi Selvi , Ahmad Yahiya Ahmad Bani Ahmad , Dhurgadevi M","doi":"10.1016/j.comnet.2025.111482","DOIUrl":"10.1016/j.comnet.2025.111482","url":null,"abstract":"<div><div>The development of Internet of Things (IoT) gadgets boosted the need for a task computing system that is reliable and efficient. Mobile Edge Computing (MEC) is growing and has become a viable tool for proximate and dependent-on latency jobs. Edge technology is well suited to IoT applications that demand minimal latency, position understanding, and large numbers of interconnections. It certainly compensates for some deficiencies in the cloud in the fields of electrical power and immediate analysis. However, ensuring the security of data in an application context remains a significant concern. Furthermore, privacy is an issue for any computing system that contains dispersed and diverse equipment. Blockchain represents a relatively new technology that emerged as an intriguing option for ensuring integrity, safety, uniformity, and authenticity. Yet, blockchain is unable to ensure adequate privacy for information on its own. So, to prevent the privacy of IoT-based data blockchain technology was developed. The data are collected from the IoT devices. The user authentication is verified, and the data are stored in the network. Also, the Adaptive Deep Markov Random Field (ADMRF) model was used for getting the verified data. The parameters in the ADMRF are tuned with the Help of the Improved Equilibrium Optimized (IEO). Once the user authentication is verified, then the data are encrypted with the help of the Attribute-Based Encryption (ABE) technique. The encryption keys are optimally generated with the help of the IEO. The encrypted data are then digitally signed by the authorized user, and then it is stored in the blockchain. The security of the model is measured by comparing it with other existing models.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111482"},"PeriodicalIF":4.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480668","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}

引用次数: 0

EdgeBoost: Confidence boosting for resource constrained inference via selective offloading EdgeBoost：通过选择性卸载增强资源约束推理的信心

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-16 DOI: 10.1016/j.comnet.2025.111437

Naina Said , Olaf Landsiedel

{"title":"EdgeBoost: Confidence boosting for resource constrained inference via selective offloading","authors":"Naina Said , Olaf Landsiedel","doi":"10.1016/j.comnet.2025.111437","DOIUrl":"10.1016/j.comnet.2025.111437","url":null,"abstract":"<div><div>Deploying large Deep Neural Networks with state-of-the-art accuracy on edge devices is often impractical due to their limited resources. This paper introduces <span>EdgeBoost</span>, a selective input offloading system designed to overcome the challenges of limited computational resources on edge devices. <span>EdgeBoost</span> trains and calibrates a lightweight model for deployment on the edge and, in addition, deploys a large, complex model on the cloud. During inference, the edge model makes initial predictions for input samples, and if the confidence of the prediction is low, the sample is sent to the cloud model for further processing, otherwise, we accept the local prediction. Through careful calibration, <span>EdgeBoost</span> reduces the communication cost by 55%, 27% and 20% for the CIFAR-100, ImageNet-1k and Stanford Cars datasets, respectively, when compared to an cloud-only solution while achieving on-par classification accuracy. Furthermore, <span>EdgeBoost</span> reduces the total inference latency from 148 ms to 123.84 ms per inference compared to a cloud-only solution. Our evaluation also shows that calibrating the edge model for such a collaborative edge–cloud setup results in accuracy gains of up to 8 percent point, compared to an uncalibrated edge model. Additionally, EdgeBoost, when used as an abstaining classifier, can improve accuracy by up to 9 percent points over an uncalibrated model. Finally, <span>EdgeBoost</span> outperforms the Early Exit and Entropy thresholding baselines and achieves comparable accuracy to state-of-the-art routing-based methods without the need for hosting the router on the edge.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"269 ","pages":"Article 111437"},"PeriodicalIF":4.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337928","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}

引用次数: 0

BLAW: BLE Assisted Wi-Fi in idle listening

IF 4.4 2区计算机科学

Computer Networks Pub Date : 2025-06-15 DOI: 10.1016/j.comnet.2025.111440

Jintao Zhao , Jialiang Yan , Siyao Cheng , Jie Liu

引用次数: 0