IEEE Transactions on Network Science and Engineering最新文献_第7页

Enhancing Quantum Communication: A Fair and Restricted Resource Allocation Approach for Entanglement Networks 增强量子通信：一种公平和有限的纠缠网络资源分配方法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-13 DOI: 10.1109/TNSE.2025.3551425

Li Ren;Zhong-Rui Huang;Hong Lai;Lin-Chun Wan

{"title":"Enhancing Quantum Communication: A Fair and Restricted Resource Allocation Approach for Entanglement Networks","authors":"Li Ren;Zhong-Rui Huang;Hong Lai;Lin-Chun Wan","doi":"10.1109/TNSE.2025.3551425","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3551425","url":null,"abstract":"Quantum entanglement networks has ushered in a new era of communication, with the core task of generating long-distance quantum entanglement being crucial for a multitude of quantum applications. Although current research is primarily focused on establishing long-distance entanglement across various network topologies, there is still a lack of attention to the variability of communication requests within quantum networks. This paper introduces the Fair and Restricted Resource Allocation Algorithm (FARA), designed to meet the business-driven resource allocation requirements within quantum networks. This algorithm prioritizes the demands and urgency of requests to establish a fairer response mechanism, leading to an enhanced user experience. We refine the strategy for allocating network resources to maximize their use during multiple concurrent requests and to improve the success rate of business. Simulation results demonstrate that our proposed scheme improves the business success rate by 6.35% to 24.58% and user satisfaction by 0.922 to 4.533 points compared to the Q-CAST algorithm. Additionally, resource wastage is reduced by 473 to 800 units. These enhancements indicate that our research provides effective strategies for business-driven optimization in quantum networks and makes a positive contribution to the development of entanglement networks towards more practical and efficient applications.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2654-2665"},"PeriodicalIF":6.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492469","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

LNPP: Logical Neural Path Planning of Mobile Beacon for Ocean Sensor Networks in Uncertain Environments Using Hierarchical Reinforcement Learning 基于层次强化学习的不确定环境下海洋传感器网络移动信标逻辑神经路径规划

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-12 DOI: 10.1109/TNSE.2025.3550566

Weijun Wang;Huafeng Wu;Shenhua Yang;Xiaojun Mei;Dezhi Han;Mario D. Marino;Kuan-Ching Li

{"title":"LNPP: Logical Neural Path Planning of Mobile Beacon for Ocean Sensor Networks in Uncertain Environments Using Hierarchical Reinforcement Learning","authors":"Weijun Wang;Huafeng Wu;Shenhua Yang;Xiaojun Mei;Dezhi Han;Mario D. Marino;Kuan-Ching Li","doi":"10.1109/TNSE.2025.3550566","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3550566","url":null,"abstract":"Localization of sensor nodes is a critical issue in Ocean Sensor Networks (OSNs). A key feature of these methods is the use of GPS-enabled mobile beacons that periodically broadcast their locations through path planning to achieve sensor localization. However, mobile beacons in OSNs are vulnerable to wind, waves, and currents, which prevent them from following pre-planned paths. Additionally, existing path planning algorithms are not suitable for handling uncertain obstacles and disturbances in OSN environments. To address these challenges, this article introduces a novel Logic Neural Path Planning (LNPP) scheme for mobile beacons. LNPP incorporates logical rule knowledge into its neural network in order to enhance learning efficiency and reduce unnecessary explorations. Furthermore, to effectively learn strategies across different time scales, a hierarchical reinforcement learning algorithm is proposed. The experimental results demonstrate that, compared to other methods, the proposed path planning scheme reduces the average localization time and the trajectory length by over 21 percent in obstacle-free OSN environments. Moreover, our scheme effectively operates in OSNs with uncertain obstacles.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2606-2621"},"PeriodicalIF":6.7,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492258","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

Self-Tallying E-Voting Using Homomorphic Time-Lock Puzzles and ZK-SNARKs 使用同态时间锁谜题和zk - snark的自计数电子投票

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3550290

Muhammad ElSheikh;Amr M. Youssef;M. Anwar Hasan

引用次数: 0

A Novel Lattice-Based Blockchain Infrastructure and Its Application on Trusted Data Management 一种基于格子的区块链结构及其在可信数据管理中的应用

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3550158

Longbo Han;Gengran Hu;Xiaoting Li;Feifei Xia;Shengbao Wang;Lin You

{"title":"A Novel Lattice-Based Blockchain Infrastructure and Its Application on Trusted Data Management","authors":"Longbo Han;Gengran Hu;Xiaoting Li;Feifei Xia;Shengbao Wang;Lin You","doi":"10.1109/TNSE.2025.3550158","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3550158","url":null,"abstract":"As a part of blockchain's infrastructure, the construction of Merkle trees typically relies on secure hash functions, such as SHA256. However, traditional blockchain systems face dual threats: quantum vulnerabilities in hash functions (e.g., Grover's algorithm reduces collision resistance) and inefficiencies in large-scale data verification. To address these challenges, we propose a parameter-hopping Merkle tree framework integrating a pseudo-random number generator (PRNG) with lattice-based cryptography. Our design ensures adaptive security through dynamic basis vector generation. This lattice-based structure offers flexibility in accommodating messages of varying sizes, supports distributed data storage, and enables efficient verification and querying of large-scale information streams. Key contributions include: a). A provably secure hash chain constructed via a family of extended-message-domain lattice-based hash functions (LBHFs), supporting arbitrary-length inputs. b). A variable-parameter Merkle tree protocol enabling efficient distributed data storage and query verification, with proof sizes optimized for P2P networks. c) A trusted data management prototype validated in a cloud storage scenario. Experimental results indicate that our blockchain infrastructure achieves enhanced security while maintaining high efficiency.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2524-2536"},"PeriodicalIF":6.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10922084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492425","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

Planning Cyclic Queuing and Forwarding for Time-Sensitive Networking via Heuristic and Neurodynamic Optimization 基于启发式和神经动力学优化的时间敏感网络循环排队和转发规划

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3550174

Jiasen Wang;Jun Wang

{"title":"Planning Cyclic Queuing and Forwarding for Time-Sensitive Networking via Heuristic and Neurodynamic Optimization","authors":"Jiasen Wang;Jun Wang","doi":"10.1109/TNSE.2025.3550174","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3550174","url":null,"abstract":"Time-sensitive networking (TSN) is a potential means to provide high-quality communication for cyber-physical systems in industrial automation and manufacturing. IEEE 802.1Qch cyclic queuing and forwarding (CQF) is a mechanism for transmitting time-sensitive packets in TSN systems. This paper addresses the planning of periodic time-sensitive flows for CQF in TSN systems. An integer programming problem is formulated to plan the periodic time-sensitive flows. In view of the NP-hardness of the integer programming problem, a polynomial-time heuristic algorithm is developed for CQF planning based on flow efficiency sorting and packet swapping to compute time offsets of multi-period flows. The heuristic algorithm is proven to converge to a CQF plan with a constant worst-case performance ratio with respect to the global optimal plan under given assumptions and derived sufficient conditions. Based on the heuristic solution, neurodynamic optimization is used to search for global optimal plans. Experimental and simulation results on open-loop network flow planning and closed-loop networked model predictive control are elaborated to substantiate the efficacy of the planning algorithms.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2537-2548"},"PeriodicalIF":6.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492404","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

Connectivity Determination Algorithm for Complex Directed Networks 复杂有向网络连通性判定算法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3549777

Zhiyi Zhong;Lin Lin;Zhihan Jiang;Xin Yuan;Edith C.H. Ngai;James Lam;Ka-Wai Kwok

{"title":"Connectivity Determination Algorithm for Complex Directed Networks","authors":"Zhiyi Zhong;Lin Lin;Zhihan Jiang;Xin Yuan;Edith C.H. Ngai;James Lam;Ka-Wai Kwok","doi":"10.1109/TNSE.2025.3549777","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3549777","url":null,"abstract":"Connectivity characterizes the ability of information transmission in systems modeled by complex networks. It is essential to develop an efficient connectivity determination algorithm with low time complexity and minimal storage requirements. To fulfill this need, a connectivity determination algorithm is designed by incorporating Tarjan's algorithm to identify strongly connected components and leveraging a depth-first search idea to traverse the reachability. This algorithm can ascertain strong connectivity, unilateral connectivity, and weak connectivity of complex directed networks. Besides, the accessibility matrix of complex directed networks is computed and visualized through an interface. As this algorithm relies on only two depth-first searches to accomplish connectivity determination tasks, its computational complexity does not exceed <inline-formula><tex-math>$O(n^{2})$</tex-math></inline-formula>, where <inline-formula><tex-math>$n$</tex-math></inline-formula> denotes the number of network nodes. Experiments carried out on some specific networks reveal that the probability of network connections decreases with the increasing number of nodes in directed injective graphs, while in Erdős–Rényi graphs, the likelihood of connections increases as the number of nodes increases. Finally, a comparative example and an application example are provided to demonstrate the effectiveness of the algorithm program.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2512-2523"},"PeriodicalIF":6.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492340","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

Attributes Based Vehicular Named Data Networking for Driving Assistance 基于属性的车辆命名数据网络驾驶辅助

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3550154

Xiaonan Wang;Gaoyang Wu

引用次数: 0

Intermediary-Supervised Auction Mechanism Design With Deep Neural Networks 基于深度神经网络的中介监督拍卖机制设计

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-11 DOI: 10.1109/TNSE.2025.3549456

Mingxuan Liang;Junwu Zhu;Yuanyuan Zhang;Xueqing Li;Mingwei Zhao

{"title":"Intermediary-Supervised Auction Mechanism Design With Deep Neural Networks","authors":"Mingxuan Liang;Junwu Zhu;Yuanyuan Zhang;Xueqing Li;Mingwei Zhao","doi":"10.1109/TNSE.2025.3549456","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3549456","url":null,"abstract":"An optimal auction mechanism is frequently characterized by its ability to allocate items to bidders who offer the highest marginal revenue. This optimality is described from the perspective of the auctioneer. Its design focus is typically on the unilateral constraints imposed by the auctioneer on the bidders, which can pose a challenge in achieving both incentive compatibility and maximizing revenue. This paper innovatively proposes an intermediary module, decomposing the auction process into a multi-objective optimization task. Specifically, we propose a novel auction mechanism design method called the <bold>T</b>ri-<bold>A</b>uction <bold>G</b>ame <bold>E</b>ngine (TAGE). In this framework, bidders strive to maximize their utility through bidding; the auctioneer concentrates on maximizing revenue by determining allocations and payments based on these bids; and the intermediary plays a pivotal role in modeling the tolerance to ensure the effective regulation of the auction process. Furthermore, we employ an adaptive annealing strategy, which models tolerance to dynamically adjust the optimization process of the model. This approach balances revenue maximization and incentive compatibility constraints, and eliminates the reliance on ex-post regret inherent in traditional methods. Finally, we demonstrate through experiments that TAGE outperforms baseline models in all settings, thereby providing valuable insights for the design of future auction mechanisms.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2500-2511"},"PeriodicalIF":6.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492446","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 Guaranteed-Performance Consensus of Networked Systems Without Involving the Feasibility Condition: A Hierarchical Algorithm 不涉及可行性条件的网络系统分布式保证性能一致性：一种层次算法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-07 DOI: 10.1109/TNSE.2025.3548313

Lei Chen;Hongjing Liang;Xilin Zhang;Tieshan Li

{"title":"Distributed Guaranteed-Performance Consensus of Networked Systems Without Involving the Feasibility Condition: A Hierarchical Algorithm","authors":"Lei Chen;Hongjing Liang;Xilin Zhang;Tieshan Li","doi":"10.1109/TNSE.2025.3548313","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3548313","url":null,"abstract":"This paper utilizes a hierarchical algorithm to focus on the distributed guaranteed-performance consensus problem of multiagent systems subjected to communication faults. With this algorithm, the consensus problem can be transformed into the tracking problem of agents in adjacent layers, and the constraint range for tracking errors does not depend on the Laplacian matrix of the communication topology. Compared to the existing hierarchical algorithm, a fault-tolerant compensation approach is designed to solve the communication fault between agents. Furthermore, the hierarchical rules are redefined according to the physical significance of topological weights, which enhances the rationality of the partition results. In addition, a shifting function is designed and incorporated into the conventional prescribed performance control approach to eliminate the existing feasibility condition. Based on Lyapunov theory, the sufficient conditions for the boundedness of all signals in the closed-loop system are derived. Finally, two simulation examples verify the efficacy of the scheme.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2445-2457"},"PeriodicalIF":6.7,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492411","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

A Lightweight Method for Botnet Detection in Internet of Things Environment 物联网环境下一种轻量级僵尸网络检测方法

IF 6.7 2区计算机科学

IEEE Transactions on Network Science and Engineering Pub Date : 2025-03-07 DOI: 10.1109/TNSE.2025.3548411

Wei Ma;Xing Wang;Jie Dong;Mingsheng Hu;Qinglei Zhou

{"title":"A Lightweight Method for Botnet Detection in Internet of Things Environment","authors":"Wei Ma;Xing Wang;Jie Dong;Mingsheng Hu;Qinglei Zhou","doi":"10.1109/TNSE.2025.3548411","DOIUrl":"https://doi.org/10.1109/TNSE.2025.3548411","url":null,"abstract":"Botnets pose a significant threat to Internet of Things (IoT) environments due to the limited computational resources of IoT devices, making traditional detection methods difficult to implement. These constraints not only hinder effective real-time detection but also leave networks vulnerable to large-scale DDoS and botnet attacks, posing a critical threat to modern connected systems. Aiming to design a lightweight botnet detection method for IoT networks, we propose a novel cloud–edge–node framework that decouples the computationally intensive training phase from the real-time detection phase. In our framework, the node layer comprises resource-constrained IoT devices that collect raw network data, the edge layer hosts lightweight detection modules for rapid analysis, and the cloud layer performs heavy-duty model training and incremental updates. Additionally, we propose a two-step feature selection process, in which the first step uses the cumulative density function (CDF) to rank features based on their distribution characteristics, and the second step applies Gini importance to further refine the feature set. This process effectively reduces computational overhead while retaining highly discriminative features for lightweight botnet detection. Experimental results on a public IoT dataset reveal that our method reduces detection time by up to 52% and energy consumption by up to 71% while maintaining high detection accuracy. These significant improvements not only validate the efficiency of our approach but also underline its potential to transform IoT security by enabling scalable, low-cost, and real-time botnet detection in diverse practical scenarios.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2458-2472"},"PeriodicalIF":6.7,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492413","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