IEEE Transactions on Network Science and Engineering最新文献_第9页

EigenObfu: A Novel Network Topology Obfuscation Defense Method 特征混淆：一种新的网络拓扑混淆防御方法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-18 DOI: 10.1109/TNSE.2024.3501396

Ziliang Zhu;Guopu Zhu;Yu Zhang;Jiantao Shi;Xiaoxia Huang;Yuguang Fang

{"title":"EigenObfu: A Novel Network Topology Obfuscation Defense Method","authors":"Ziliang Zhu;Guopu Zhu;Yu Zhang;Jiantao Shi;Xiaoxia Huang;Yuguang Fang","doi":"10.1109/TNSE.2024.3501396","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3501396","url":null,"abstract":"Link flooding attack is a kind of attack based on the topology information of a network. Sophisticated attackers tend to conduct network reconnaissance before they launch effective attacks to infer key information about the whole network. Existing active defense methods against link flooding attacks either focus on protecting the key links within the network or safeguarding the key nodes with the simple degree centrality. This paper proposes a novel network topology obfuscation method called EigenObfu to protect the key nodes. Instead of using the degree centrality in existing defense methods, our eigenvector centrality-based EigenObfu comprehensively utilizes network topology information and better measures the importance of nodes in a network. EigenObfu is designed to output a secure obfuscated topology suitable for networks, regardless of their sizes, by hiding important nodes while maintaining connectivity and ensuring the protection of key nodes. We evaluate EigenObfu through several comparison experiments on nine different topologies. The results confirm the effectiveness of our method.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"451-462"},"PeriodicalIF":6.7,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880334","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

Distributed On-Demand Routing Algorithm With Graph Representation Learning for Industrial IoT 基于图表示学习的工业物联网分布式按需路由算法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-14 DOI: 10.1109/TNSE.2024.3496438

Bin Dai;Hetao Li;Wenrui Huang

引用次数: 0

Graph-Based Learning in Core and Edge Virtualized O-RAN for Handling Real-Time AI Workloads 处理实时AI工作负载的核心和边缘虚拟化O-RAN中的基于图的学习

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-14 DOI: 10.1109/TNSE.2024.3495583

Prohim Tam;Seokhoon Kim

{"title":"Graph-Based Learning in Core and Edge Virtualized O-RAN for Handling Real-Time AI Workloads","authors":"Prohim Tam;Seokhoon Kim","doi":"10.1109/TNSE.2024.3495583","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3495583","url":null,"abstract":"AI-empowered applications have been deployed in many aspects of networking, and federated learning (FL) has emerged as a complementary approach due to its ability to enable privacy-preserving model training and inference. However, without self-organizing capability, practical FL systems face several issues to co-exist in real-time networking. Therefore, this paper aims to design autonomous FL management with integrated graph neural networks (GNN) and deep reinforcement learning (DRL), namely AutoFedGDRL, to sustain heterogeneous FL execution in optimized open radio access network (O-RAN) and intelligent core network architectures and offer automated policy-driven orchestration by intelligent agent controller. Edge cloud virtualized O-RAN is integrated to assist model computation and support multiple services with elastic containerized resource scaling. The practicability of FL systems is stimulated by modelling the participants and aggregators as a graph representation and subsequently analyzing to predict the accessibility and trustworthiness of the nodes, bandwidth capacities, and virtual link relationship. Our proposed AutoFedGDRL aims to obtain specifications of hidden FL, service, and networking states in order to control the main policies, such as training management, resource sharing, aggregation scheduling, and service prioritization. In the experiment, AutoFedGDRL surpassed reference models (non-federated training) in global accuracy, achieving 98.23% for MNIST and 97.12% for CIFAR-10, compared to 98.22% and 95.89% for PrimaryGNN-FL. The proposed scheme also improved end-to-end convergence speed, with execution times 10.58 ms to 32.79 ms faster. Model delivery ratios reached 99.98%, ensuring the federated system's reliability and sharing workload efficiency.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"302-318"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880385","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

Link-Identified Routing Architecture in Space 空间中的链路识别路由体系结构

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-14 DOI: 10.1109/TNSE.2024.3498042

Hefan Zhang;Zhiyuan Wang;Shan Zhang;Qingkai Meng;Hongbin Luo

{"title":"Link-Identified Routing Architecture in Space","authors":"Hefan Zhang;Zhiyuan Wang;Shan Zhang;Qingkai Meng;Hongbin Luo","doi":"10.1109/TNSE.2024.3498042","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3498042","url":null,"abstract":"Low earth orbit (LEO) satellite networks have the potential to provide low-latency communication with global coverage. To unleash this potential, it is crucial to achieve efficient packet delivery. In this paper, we propose a Link-identified Routing (LiR) architecture for LEO satellite networks. The LiR architecture leverages the deterministic neighbor relation of LEO constellations, and identifies each inter-satellite link (ISL). Moreover, LiR architecture adopts source-route-style forwarding based on in-packet bloom filter (BF). Each satellite could efficiently encode multiple ISL identifiers via an in-packet BF to specify the end-to-end path for the packets. Due to false positives caused by BF, the more ISLs are encoded at a time, the more redundant forwarding cases emerge. Based on the topology characteristics, we derive the expected forwarding overhead in a closed-form and propose the optimal encoding policy. To accommodate link-state changes in LEO satellite networks, we propose the on-demand rerouting scheme and the on-demand detouring scheme to address the intermittent ISLs. We also elaborate how to take advantage of LiR architecture to achieve seamless handover for ground-satellite links (GSLs). Finally, we conduct extensive numerical experiments and packet-level simulations to verify our analytical results and evaluate the performance of the LiR architecture.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"392-408"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880386","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

OpenFi: Open-Set WiFi Human Sensing via Virtual Embedding Confidence-Aware OpenFi：通过虚拟嵌入置信度感知的开放式WiFi人体传感

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-14 DOI: 10.1109/TNSE.2024.3496496

Han Liu;Liang Xi;Wei Wang;Fengbin Zhang;Zygmunt J. Haas

{"title":"OpenFi: Open-Set WiFi Human Sensing via Virtual Embedding Confidence-Aware","authors":"Han Liu;Liang Xi;Wei Wang;Fengbin Zhang;Zygmunt J. Haas","doi":"10.1109/TNSE.2024.3496496","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3496496","url":null,"abstract":"WiFi sensing technology utilizes Channel State Information (CSI) to analyze human behavior and plays a crucial role in mobile computing. WiFi sensing systems are typically deployed by collecting data in specific known environments, known as closed-set settings. However, in practical deployment, WiFi sensing systems may encounter unknown environments, generating unknown CSI patterns due to signal reflection, multipath effects, and interference. In such open-set conditions, the WiFi sensing system should possess the capability to recognize unknown CSI patterns, enhancing its security and reliability. In response, this work proposes an open-set WiFi human sensing method based on virtual embedding confidence-aware (OpenFi). The core of OpenFi is virtual embedding generation to simulate a realistic open-set feature space. This strategy minimizes both empirical and open-set risks, enabling OpenFi to recognize unknown CSI patterns effectively. We conducted extensive experiments on diverse datasets, covering various WiFi sensing tasks, including human identification, human activity recognition, and sign language recognition. Experimental results demonstrate that OpenFi accurately identifies previously unseen CSI patterns in open-set conditions, achieving significant improvements of up to 27% and 10.26% in the FPR95 and OSCR metrics, respectively.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"344-355"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880328","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

Learning-Based Deadlock-Free Multi-Objective Task Offloading in Satellite Edge Computing With Data-Dependent Constraints and Limited Buffers 基于数据依赖约束和有限缓冲区的卫星边缘计算无死锁多目标任务卸载

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-13 DOI: 10.1109/TNSE.2024.3496902

Ruipeng Zhang;Yanxiang Feng;Yikang Yang;Xiaoling Li;Hengnian Li

{"title":"Learning-Based Deadlock-Free Multi-Objective Task Offloading in Satellite Edge Computing With Data-Dependent Constraints and Limited Buffers","authors":"Ruipeng Zhang;Yanxiang Feng;Yikang Yang;Xiaoling Li;Hengnian Li","doi":"10.1109/TNSE.2024.3496902","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3496902","url":null,"abstract":"Satellite edge computing (SEC) is important for future network deployments because of its global coverage and low-latency computing services. Nevertheless, due to data dependencies among tasks and limited buffers in satellites, a coupling exists between transmission and computation, and undesired \u0000<italic>deadlocks</i>\u0000 may arise. This paper addresses task offloading in SEC and aims to minimize service latency, energy consumption, and time window violations simultaneously. First, a mixed-integer nonlinear programming model is presented. To resolve potential deadlocks, a deadlock amending algorithm (DAA) based on Petri net with polynomial time complexity is proposed. Deadlocks in solutions are amended by finding a transition sequence that corresponding transmission and computation can be performed sequentially. By embedding DAA, we develop a learning-based deadlock-free multi-objective scheduling algorithm (LDMOSA) that combines the exploration of evolutionary algorithms with the perception of reinforcement learning. To enhance the convergence and diversity of solutions, an initialization strategy employing problem-specific constructive heuristics is designed. Then, a learning-based mechanism is used to leverage real-time information to perform adaptive operator selection during the search process. Finally, extensive experiments demonstrate the effectiveness of DAA in resolving deadlocks, and the LDMOSA outperforms state-of-the-art algorithms for task offloading in SEC.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"356-368"},"PeriodicalIF":6.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880325","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

From Earth-to-Moon Networking: A Software-Defined Temporal Perspective 从地球到月球的网络：软件定义的时间视角

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-13 DOI: 10.1109/TNSE.2024.3497573

Francesco Chiti;Roberto Picchi;Laura Pierucci

{"title":"From Earth-to-Moon Networking: A Software-Defined Temporal Perspective","authors":"Francesco Chiti;Roberto Picchi;Laura Pierucci","doi":"10.1109/TNSE.2024.3497573","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3497573","url":null,"abstract":"Considering the scientific and economic opportunities, several public and private organizations are going to establish colonies on the Moon. In particular, lunar colonization can be a first step for deep space missions, and the initial phase is accomplished with the deployment of many Internet of Things (IoT) devices and systems. Therefore, a dedicated Earth-Moon backbone, which results from the combination of terrestrial and lunar satellite segments, must be designed. Considering that its elements are inherently mobile, to ensure the connection, the constituent devices are supposed to be programmed to properly operate during specific time intervals. The features of the Software-Defined Networking (SDN) paradigm allows achieving this aim. Moreover, the Temporal Networks (TNs) theoretical framework makes it possible to optimize the forwarding rules. In light of these principles, this paper proposes an SDN-based architecture and analyzes the overall communications scenario proposing a specific strategy to optimize the data rate. The performance was evaluated considering the End-to-End (E2E) best path duration, the number of hops, the control packets latency, the power budget and capacity. The results point out that it is feasible to establish a networking strategy on-demand to support the transmission of continuous IoT data flows with limited overhead.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"369-380"},"PeriodicalIF":6.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10752586","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880411","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}

引用次数: 0

A Tube-Based Distributed MPC Based Method for Low-Carbon Energy Networks With Exogenous Disturbances 一种基于管状分布MPC的外源扰动低碳能源网络求解方法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-13 DOI: 10.1109/TNSE.2024.3497577

Yubin Jia;Zhao Yang Dong;Changyin Sun;Ke Meng

引用次数: 0

Pinning Adaptive Passivity and Bipartite Synchronization of Leaderless Fractional Spatiotemporal Networks 无领导分数时空网络的自适应被动与二部同步

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-11 DOI: 10.1109/TNSE.2024.3496199

Yu Sun;Cheng Hu;Shipin Wen;Juan Yu;Haijun Jiang

引用次数: 0

Potential Game-Based Computation Offloading in Edge Computing With Heterogeneous Edge Servers 异构边缘服务器边缘计算中潜在的基于博弈的计算卸载

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2024-11-07 DOI: 10.1109/TNSE.2024.3494542

Zhiwei Zhou;Li Pan;Shijun Liu

{"title":"Potential Game-Based Computation Offloading in Edge Computing With Heterogeneous Edge Servers","authors":"Zhiwei Zhou;Li Pan;Shijun Liu","doi":"10.1109/TNSE.2024.3494542","DOIUrl":"https://doi.org/10.1109/TNSE.2024.3494542","url":null,"abstract":"With the proliferation of mobile phones, IoT devices, and the rising demand for computational resources, computation offloading has emerged as a promising technique for improving performance, and optimizing resource usage. It involves transferring computational tasks from local devices to edge servers. However, reducing latency and device energy consumption remains a challenge in current research. In this paper, we propose a potential game-theoretic approach to optimize computation offloading in edge computing environments. We consider heterogeneous edge servers, where each server may have different computational capabilities. By formulating the problem as a potential game, we have end devices acting as players deciding whether to execute tasks locally or on edge servers. Our framework includes utility functions capturing the latency-energy consumption trade-off. Through a detailed analysis, we introduce an innovative algorithm for potential games aiming at achieving Nash equilibrium. This algorithm demonstrates exceptional convergence properties, ensuring reliable convergence even in complex scenarios. Extensive experiments validate the convergence of our algorithm and demonstrate its better performance compared to other benchmark algorithms in terms of latency and energy consumption.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 1","pages":"290-301"},"PeriodicalIF":6.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880333","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