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Journal of network and computer applications
Academic Press
Journal of network and computer applications

Academic Press

季刊

1084-8045

Journal of network and computer applications/Journal Journal of network and computer applicationsSCIAHCIISTP
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    A dynamic spectrum access scheme for Internet of Things with improved federated learning

    Li, FengYang, JunyiLam, Kwok-YanShen, Bowen...
    1.1-1.12页
    查看更多>>摘要：The traditional spectrum management paradigm is no longer sufficient to meet the increasingly urgent demand for efficient utilization of spectrum resources by Internet of Things (IoT) devices. Dynamic spectrum access, as an emerging solution, allows devices to intelligently select appropriate spectrum resources based on real-time demands and environmental changes. In this paper, we propose a dynamic spectrum access scheme based on a federated deep reinforcement learning framework, incorporating federated learning, graph neural networks (GNN), and deep Q networks (DQN). In the method, the GNN undertakes the Q-value prediction task, giving full play to its ability to capture inter-device relationships and environmental features. Meanwhile, the DQN learns by interacting with the environment and continuously adapts its strategy to maximize long-term cumulative rewards. To enhance the stability and learning efficiency of the model, we also apply techniques such as empirical playback buffering and updating the target network at fixed intervals. In particular, the use of the FedAge algorithm in federated learning helps to coordinate knowledge sharing and model updates across multiple devices, further enhancing the performance and operational efficiency of the entire system. After several simulation training, the results show that the system model of this paper's scheme is close to or even better than the traditional federated deep reinforcement learning model in terms of convergence effect and stability while maintaining the privacy-preserving advantages of federated learning. Particularly noteworthy is that in terms of operational efficiency, this paper's scheme significantly outperforms traditional federated deep learning models.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    paper Fair association and rate maximization in 6G UAV Aided HS only network and HetNet

    Ghafoor, Umar
    1.1-1.18页
    查看更多>>摘要：Advancements in technology are driving the demand for high-speed, real-time interactive applications with requirements for faster data rates, reduced latency, and expanded network capacity to deliver immersive user experiences. Additionally, the increasing connectivity needs surpass the capabilities of fifth-generation (5G) networks. Sixth-generation (6G) networks are emerging to address these demands. To maximize capacity in 6G networks, various strategies such as enhanced coverage, unmanned aerial vehicle (UAV)-assisted high-powered base station (HS) networks, and heterogeneous networks (HetNets) are being explored. This paper introduces a novel approach utilizing mobile device clustering (MDC) in combination with downlink hybrid multiple access (H-MA) techniques in UAV-assisted HS-only networks and HetNets. The objective is to jointly optimize mobile device (MD) admission in clusters, MD association with base stations, and network sum rate while ensuring fairness. To solve the resulting mixed integer non-linear programming (MINLP) problem, an outer approximation algorithm (OAA) is employed. The effectiveness of this approach is evaluated and compared in both UAV-assisted HS-only network and HetNet scenarios. The results demonstrate the superior performance of UAV-assisted HetNets in terms of performance indicators (PIs) like sum rate maximization, MD cluster admission, MD base station association, power allocation to MDs, and MD fair association with base stations (MDFAS). Furthermore, the proposed technique outperforms existing methods, including [36], across all PIs, highlighting its outstanding performance.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Task offloading strategy of vehicle edge computing based on reinforcement learning

    Wang, LinglingZhou, WenjieZhai, Linbo
    1.1-1.12页
    查看更多>>摘要：The rapid development of edge computing has an impact on the Internet of Vehicles (IoV). However, the high-speed mobility of vehicles makes the task offloading delay unstable and unreliable. Hence, this paper studies the task offloading problem to provide stable computing, communication and storage services for user vehicles in vehicle networks. The offloading problem is formulated to minimize cost consumption under the maximum delay constraint by jointly considering the positions, speeds and computation resources of vehicles. Due to the complexity of the problem, we propose the vehicle deep Q-network (V-DQN) algorithm. In V-DQN algorithm, we firstly propose a vehicle adaptive feedback (VAF) algorithm to obtain the priority setting of processing tasks for service vehicles. Then, the V-DQN algorithm is implemented based on the result of VAF to realize task offloading strategy. Specially, the interruption problem caused by the movement of the vehicle is formulated as a return function to evaluate the task offloading strategy. The simulation results show that our proposed scheme significantly reduces cost consumption.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    ParallelC-Store: A committee structure-based reliable parallel storage mechanism for permissioned blockchain sharding

    Qiu, LinZhang, KaiminWang, XingweiYi, Bo...
    1.1-1.15页
    查看更多>>摘要：The storage performance of blockchain suffers from serious limitations due to its employed full-replication strategy, especially in large-scale network services such as Jointcloud computing and big data processing. To address this challenge, some storage partitioning mechanisms integrating Erasure Coding with Byzantine Fault Tolerant (BFT) consensus protocol are developed, like BFT-Store and PartitionChain. Whilst promising, there still exist three major issues impacting system effectiveness, scalability and stability. Firstly, the high computational complexity of coding consumes substantial computing time. Secondly, the signature schemes for verifying the integrity and correctness of encoded data lead to massive transmitted data over the network. Thirdly, each process necessitates the participation of all nodes, causing extended time overhead and interruption of system operation. To optimize the above three aspects, this paper presents a parallel storage partitioning mechanism called ParallelC-Store, where the nodes are divided into g Storage Committees (SCs) based on the existing BFT sharding protocol. Firstly, the g SCs engage in parallel implementation of data encoding and decoding of g distinct original blocks in a synchronous manner. Hence, the computational complexity/throughput per block of encoding and decoding can be decreased/increased by about g/g2 and g2/g3 times respectively. Secondly, Merkle Tree and Bloom Filter are employed to generate the verification proof of encoded data, which avoids heavy communication burdens. Thirdly, all processes for different scenarios can be implemented exclusively within a specific SC when a node joins/quits the system or a single crashed node needs repair. The experimental results demonstrate that the proposed mechanism generally outperforms the comparison mechanisms in terms of storage consumption, coding efficiency and system scalability.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    SPARTA-GEMSTONE: A two-phase approach for efficient node placement in 3D WSNs under Q-Coverage and Q-Connectivity constraints

    Vu, Quang TruongTrinh, The MinhNguyen, Thi HanhTrinh, Van Chien...
    1.1-1.20页
    查看更多>>摘要：Wireless sensor networks (WSNs) face challenges in achieving robust target coverage and connectivity, particularly when varying priorities for targets are modeled with Q-Coverage and Q-Connectivity constraints. However, existing studies often neglect minimizing the number of nodes under these constraints in 3D environments or focus on sensor-to-sensor connections, which are less suitable for target-oriented networks. This paper bridges these gaps by proposing a novel two-phase heuristic approach. In Phase I, we introduce SPARTA, with two variants (SPARTA-CC and SPARTA-CP), to address Q-Coverage. Phase II employs GEMSTONE, a heuristic algorithm based on a minimum spanning tree, to ensure Q-Connectivity. Our method is evaluated on a real-world 3D dataset and compared against baseline methods. The results demonstrate that our approach significantly reduces the number of nodes while improving running speed. Our proposal can save 13% of the node count while running 2370 times faster than the current state-of-the-art method. These contributions advance the state of the art in WSN design and hold significant implications for efficient and fault-tolerant network deployment in practical scenarios.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Secure data migration from fair contract signing and efficient data integrity auditing in cloud storage

    Yang, ChangsongLiu, YuelingDing, YongLiang, Hai...
    1.1-1.12页
    查看更多>>摘要：With the rapid development of cloud storage, a growing number of data owners prefer to outsource their large-scale data to the remote cloud data centers, thus effectively avoiding the heavy burden of storing the massive data by themselves in local. Due to the promising market prospect, plenty of companies invest cloud storage and offer data storage services, which equipped with different access speed, using price, security, storage capacity, etc. For enjoying more suitable services, data owners might dynamically change cloud service providers and migrate the outsourced data blocks from a cloud data center to another one. However, the data integrity cannot be guaranteed during the migration process. In this paper, we study the challenge of secure outsourced data migration supporting fair contract signing and efficient data integrity auditing. Subsequently, we propose an efficient and practical solution to address this problem. Specifically, we adopt public blockchain to design a fair three-party contract signing protocol for outsourced data migration, which can effectively prevent data owners and cloud data centers from slandering each other maliciously. Meanwhile, we combine public blockchain and multicopy Merkle hash tree (M2HT) to design a secure data migration protocol with efficient data integrity auditing, which can guarantee the data integrity during the migration process. Next, we provide the formal security analysis, which demonstrates that our scheme can satisfy all of the expected security requirements without trusted third party. Finally, we also develop a prototype implementation and provide the performance evaluation, which can show the high-efficiency and practicality of our scheme.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    On the network coding-based D2D collaborative recovery scheme for scalable video broadcasting

    Wang, LeiSun, JieChen, LiangYin, Jun...
    1.1-1.12页
    查看更多>>摘要：This paper examines the collaborative recovery issue for the scalable video broadcasting (SVB) system, where two proximate user nodes are able to maintain a local out-of-band device-to-device (D2D) pair to cooperatively recover their lost broadcasted packets. Traditional error protection methods, such as Forward Error Correction (FEC) and error concealment, often require the source node to dynamically adjust its broadcast content based on feedback from user nodes. However, in many practical SVB scenarios, such as mobile TV broadcasting systems and satellite-based video broadcast virtual file systems, user nodes are merely recipients of broadcast messages and cannot feasibly report their reception status back to the source node (i.e., feedback-free). To address these challenges, we propose the Network Coding based Collaborative recovery scheme for SVB, named NC2-SVB. NC2-SVB deviates from previous studies by employing a feedback-free transmission model, wherein the source node neither receives updates on reception status nor channel conditions from the user nodes, nor does it dynamically modify its broadcast content. By utilizing the designed coding window sliding mechanism and the collaborative video layer scheduling algorithm, each user node can independently maintain a sliding coding window, generate optimal network coded packets, and collaborate recovery for the partner in a timely manner. The theoretical bounds of reliability and decoding delay for NC2-SVB have been analyzed. Experimental results demonstrate that NC2-SVB, compared to existing schemes, enhances the collaboration throughput, achieves higher decoding rates, offers lower decoding delays, as well as improved video playback quality.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    An overview and solution for democratizing AI workflows at the network edge

    Cop, AndrejBertalanic, BlazFortuna, Carolina
    1.1-1.23页
    查看更多>>摘要：With the process of democratization of the network edge, hardware and software for networks are becoming available to the public, overcoming the confines of traditional cloud providers and network operators. This trend, coupled with the increasing importance of AI in 6G and beyond cellular networks, presents opportunities for innovative AI applications and systems at the network edge. While AI models and services are well-managed in cloud systems, achieving similar maturity for serving network needs remains an open challenge. Existing open solutions are emerging and are yet to consider democratization requirements. In this work, we identify key requirements for democratization and propose NAOMI, a solution for democratizing AI/ML workflows at the network edge designed based on those requirements. Guided by the functionality and overlap analysis of the O-RAN AI/ML workflow architecture and MLOps systems, coupled with the survey of open-source AI/ML tools, we develop a modular, scalable, and distributed hardware architecture-independent solution. NAOMI leverages state-of-the-art open-source tools and can be deployed on distributed clusters of heterogeneous devices. The results show that NAOMI performs up to 40% better in deployment time and up to 73% faster in AI/ML workflow execution for larger datasets compared to AI/ML Framework, a representative open network access solution, while performing inference and utilizing resources on par with its counterpart.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    A survey of secure semantic communications

    Meng, RuiGao, SongFan, DayuGao, Haixiao...
    1.1-1.55页
    查看更多>>摘要：Semantic communication (SemCom) is regarded as a promising and revolutionary technology in 6G, aiming to transcend the constraints of "Shannon's trap" by filtering out redundant information and extracting the core of effective data. Compared to traditional communication paradigms, SemCom offers several notable advantages, such as reducing the burden on data transmission, enhancing network management efficiency, and optimizing resource allocation. Numerous researchers have extensively explored SemCom from various perspectives, including network architecture, theoretical analysis, potential technologies, and future applications. However, as SemCom continues to evolve, a multitude of security and privacy concerns have arisen, posing threats to the confidentiality, integrity, and availability of SemCom systems. This paper presents a comprehensive survey of the technologies that can be utilized to secure SemCom. Firstly, we elaborate on the entire life cycle of SemCom, which includes the model training, model transfer, and semantic information transmission phases. Then, we identify the security and privacy issues that emerge during these three stages. Furthermore, we summarize the techniques available to mitigate these security and privacy threats, including data cleaning, robust learning, defensive strategies against backdoor attacks, adversarial training, differential privacy, cryptography, blockchain technology, model compression, and physical-layer security. Lastly, this paper outlines future research directions to guide researchers in related fields.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    ASL: An Accurate and Stable Localization algorithm for multi-hop irregular networks

    Xia, XingshengYan, JiajiaWu, ChenhuangMeng, Chao...
    1.1-1.15页
    查看更多>>摘要：Accurate geographical information about nodes is essential in wireless multi-hop networks. Most existing localization algorithms focus on locating nodes in regular network environments, posing challenges for irregular multi-hop networks. To mitigate the impact of irregularities on localization, we propose an Accurate and Stable Localization algorithm (ASL). ASL first infers a hop threshold based on the distribution characteristics of anchors, eliminating erroneous distances and avoiding them in the localization process. Next, under the constraint of the hop threshold, each normal node constructs its sub-region, including it, based on the estimated distance to the anchors. These sub-regions can avoid the occurrence of unreliable localization results and assist in decreasing communication overhead. Finally, the SMA (Slime Mould Algorithm) with the Halton sequence is introduced to search for the optimally estimated locations of normal nodes, which tends to accelerate convergence and improve localization accuracy. Extensive simulations demonstrate that our proposed ASL outperforms state-of-the-art algorithms regarding accuracy and stability when facing network irregularities. Specifically, our proposed ASL achieves a median improvement in localization accuracy ranging from 16.96% to 83.66%.
      原文链接:
    • NETL
    • NSTL
    • Elsevier