Journal of Network and Computer Applications最新文献

{"title":"ParallelC-Store: A committee structure-based reliable parallel storage mechanism for permissioned blockchain sharding","authors":"Lin Qiu ,&nbsp;Kaimin Zhang ,&nbsp;Xingwei Wang ,&nbsp;Bo Yi ,&nbsp;Fei Gao ,&nbsp;Yanpeng Qu ,&nbsp;Min Huang","doi":"10.1016/j.jnca.2025.104171","DOIUrl":"10.1016/j.jnca.2025.104171","url":null,"abstract":"<div><div>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 <span><math><mi>g</mi></math></span> Storage Committees (SCs) based on the existing BFT sharding protocol. Firstly, the <span><math><mi>g</mi></math></span> SCs engage in parallel implementation of data encoding and decoding of <span><math><mi>g</mi></math></span> distinct original blocks in a synchronous manner. Hence, the computational complexity/throughput per block of encoding and decoding can be decreased/increased by about <span><math><mi>g</mi></math></span>/<span><math><msup><mrow><mi>g</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> and <span><math><msup><mrow><mi>g</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>/<span><math><msup><mrow><mi>g</mi></mrow><mrow><mn>3</mn></mrow></msup></math></span> 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.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104171"},"PeriodicalIF":7.7,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746968","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":"Multi-agent reinforcement learning based dynamic self-coordinated topology optimization for wireless mesh networks","authors":"Qingwei Tang ,&nbsp;Wei Sun ,&nbsp;Zhi Liu ,&nbsp;Qiyue Li ,&nbsp;Xiaohui Yuan","doi":"10.1016/j.jnca.2025.104177","DOIUrl":"10.1016/j.jnca.2025.104177","url":null,"abstract":"<div><div>Wireless mesh network (WMN) technology enhances wireless communication coverage and increases end-to-end (E2E) delay. The delay in WMNs is influenced by various mesh topologies, which are shaped by transmission power factors. Due to the dynamic nature of WMNs, conventional offline topology optimization methods are ineffective. This paper presents a reinforcement learning (RL)-based dynamic collaborative optimization method to minimize E2E delay and power consumption in WMNs. First, we develop a numerical model that simulates real-world communication environments. Next, we design a baseline and a reward function tailored to this environment. We propose a novel dynamic self-coordinated topology optimization algorithm to address the challenges associated with high-dimensional state–action spaces and the need for coordinated actions among multiple terminal devices. By leveraging coordination signals from terminal agents and multiple optimization strategies, the algorithm enables automatic agent coordination. Experimental results and real-world simulations demonstrate that the proposed algorithm effectively reduces both E2E delay and device power consumption.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104177"},"PeriodicalIF":7.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725854","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":"Fair association and rate maximization in 6G UAV Aided HS only network and HetNet","authors":"Umar Ghafoor","doi":"10.1016/j.jnca.2025.104174","DOIUrl":"10.1016/j.jnca.2025.104174","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104174"},"PeriodicalIF":7.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768492","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":"SPARTA-GEMSTONE: A two-phase approach for efficient node placement in 3D WSNs under Q-Coverage and Q-Connectivity constraints","authors":"Quang Truong Vu ,&nbsp;The Minh Trinh ,&nbsp;Thi Hanh Nguyen ,&nbsp;Van Chien Trinh ,&nbsp;Thi Thanh Binh Huynh ,&nbsp;Xuan Thang Nguyen ,&nbsp;Cong Phap Huynh","doi":"10.1016/j.jnca.2025.104175","DOIUrl":"10.1016/j.jnca.2025.104175","url":null,"abstract":"<div><div>Wireless sensor networks (WSNs) face challenges in achieving robust target coverage and connectivity, particularly when varying priorities for targets are modeled with <span><math><mi>Q</mi></math></span>-Coverage and <span><math><mi>Q</mi></math></span>-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 <span><math><mi>Q</mi></math></span>-Coverage. Phase II employs GEMSTONE, a heuristic algorithm based on a minimum spanning tree, to ensure <span><math><mi>Q</mi></math></span>-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.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104175"},"PeriodicalIF":7.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725771","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":"Self-adaptive cyber defense for sustainable IoT: A DRL-based IDS optimizing security and energy efficiency","authors":"Saeid Jamshidi ,&nbsp;Ashkan Amirnia ,&nbsp;Amin Nikanjam ,&nbsp;Kawser Wazed Nafi ,&nbsp;Foutse Khomh ,&nbsp;Samira Keivanpour","doi":"10.1016/j.jnca.2025.104176","DOIUrl":"10.1016/j.jnca.2025.104176","url":null,"abstract":"<div><div>The Internet of Things (IoT) has revolutionized industries by creating a vast, interconnected ecosystem. Still, the rapid deployment of IoT devices has introduced severe security risks, including DDoS, DoS GoldenEye, DoS Hulk attacks, and Port scanning. Traditional Machine Learning (ML)-based Intrusion Detection Systems (IDS) often operate passively, detecting threats without taking action, and are rarely evaluated under real-time attacks. This limits our understanding of their performance within the resource constraints typical of IoT systems—an essential factor for stable, resilient systems. This paper proposes a Security Edge with Deep Reinforcement Learning (SecuEdge-DRL) specifically designed for the IoT edge, aiming to enhance security while maintaining energy efficiency, contributing to sustainable IoT operations. Our IDS integrates DRL with the MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) control loop, enabling real-time detection and adaptive response without relying on predefined data models. DRL allows continuous learning, while MAPE-K provides structured self-adaptation, ensuring the system remains effective against evolving threats. We also implemented four targeted security policies tailored to a specific attack type to enhance the IDS’s threat mitigation capabilities. Experimental findings indicate that the proposed SecuEdge-DRL achieves an average detection accuracy of 92% across diverse real-world cyber threats (e.g., DoS Hulk, DoS GoldenEyes, DDoS, and Port scanning). Statistical analysis further validates that these security policies enhance IoT systems’ defense without compromising performance, establishing our approach as a resilient, resource-efficient security solution for the IoT ecosystem.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104176"},"PeriodicalIF":7.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738940","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":"ASL: An Accurate and Stable Localization algorithm for multi-hop irregular networks","authors":"Xingsheng Xia ,&nbsp;Jiajia Yan ,&nbsp;Chenhuang Wu ,&nbsp;Chao Meng ,&nbsp;Xiaoyong Yan","doi":"10.1016/j.jnca.2025.104172","DOIUrl":"10.1016/j.jnca.2025.104172","url":null,"abstract":"<div><div>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 <u>A</u>ccurate and <u>S</u>table <u>L</u>ocalization 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 (<u>S</u>lime <u>M</u>ould <u>A</u>lgorithm) 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%.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104172"},"PeriodicalIF":7.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143758986","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":"Secure data migration from fair contract signing and efficient data integrity auditing in cloud storage","authors":"Changsong Yang ,&nbsp;Yueling Liu ,&nbsp;Yong Ding ,&nbsp;Hai Liang","doi":"10.1016/j.jnca.2025.104173","DOIUrl":"10.1016/j.jnca.2025.104173","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"239 ","pages":"Article 104173"},"PeriodicalIF":7.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725853","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":"Kinitos: Dynamic network-aware scheduling and descheduling in Kubernetes clusters with mobile nodes","authors":"Tsvetan Tsokov,&nbsp;Hristo Kostadinov","doi":"10.1016/j.jnca.2025.104157","DOIUrl":"10.1016/j.jnca.2025.104157","url":null,"abstract":"<div><div>The current Cloud/Edge/Fog platforms, available in practice, do not support dynamic management of computational and network resources in clusters with moveable and constraint nodes, like in applications such as: connected vehicles, Internet of Things (IoT), spacecraft computing, etc. This leads to increased total response time and low QoS for the long-living applications composed of many inter-dependent microservices with stringent and configurable network latency and bandwidth requirements. This problem is further complicated by the mobile end-users. The paper presents a novel framework for network-aware dynamic scheduling and descheduling (migration) of containers on mobile clusters based on Kubernetes (K8s), named Kinitos. It is composed of plugins in the K8s scheduler, descheduler and Application Group and Network Topology controllers, providing a mechanism for configuration of application microservice dependencies with specific computational (CPU, memory, storage) and network (latency, bandwidth) requirements. In clusters with dynamic, moveable and constraint nodes, it migrates application containers on optimal nodes to satisfy network and computational requirements continuously at runtime. The performed experiments with real world node movement patterns on K8s ARM64 testbed cluster show an improvement in the total end-to-end network latency of a long-living edge-native application by up to 60% compared to the K8s default scheduler and up to 50% compared to the latest K8s network-aware scheduler plugin, with only 0.55 s (32.5%) increase in the average pod deployment time. Its implementation can be used not only for theoretical research, but in practice.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"238 ","pages":"Article 104157"},"PeriodicalIF":7.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698104","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}

{"title":"A MLOps architecture for near real-time distributed Stream Learning operation deployment","authors":"Miguel G. Rodrigues,&nbsp;Eduardo K. Viegas,&nbsp;Altair O. Santin,&nbsp;Fabricio Enembreck","doi":"10.1016/j.jnca.2025.104169","DOIUrl":"10.1016/j.jnca.2025.104169","url":null,"abstract":"<div><div>Traditional architectures for implementing Machine Learning Operations (MLOps) usually struggle to cope with the demands of Stream Learning (SL) environments, where deployed models must be incrementally updated at scale and in near real-time to handle a constantly evolving data stream. This paper proposes a new distributed architecture adapted for deploying and updating SL models under the MLOps framework, implemented twofold. First, we structure the core components as microservices deployed on a container orchestration environment, ensuring low computational overhead and high scalability. Second, we propose a periodic model versioning strategy that facilitates seamless updates of SL models without degrading system accuracy. By leveraging the inherent characteristics of SL algorithms, we trigger the model versioning task only when their decision boundaries undergo significant adjustments. This allows our architecture to support scalable inference while handling incremental SL updates, enabling high throughput and model accuracy in production settings. Experiments conducted on a proposal’s prototype implemented as a distributed microservice architecture on Kubernetes attested to our scheme’s feasibility. Our architecture can scale inference throughput as needed, delivering updated SL models in less than 2.5 s, supporting up to 8 inference endpoints while maintaining accuracy similar to traditional single-endpoint setups.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"238 ","pages":"Article 104169"},"PeriodicalIF":7.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642734","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":"Comprehensive phishing detection: A multi-channel approach with variants TCN fusion leveraging URL and HTML features","authors":"Ali Aljofey ,&nbsp;Saifullahi Aminu Bello ,&nbsp;Jian Lu ,&nbsp;Chen Xu","doi":"10.1016/j.jnca.2025.104170","DOIUrl":"10.1016/j.jnca.2025.104170","url":null,"abstract":"<div><div>Phishing represents a major threat to the financial and privacy security of Internet users, and often serves as a precursor to cyberattacks. While many deep learning-based methods focus on analyzing URLs to detect phishing due to their simplicity and efficiency, they face challenges. Hidden phishing websites may employ tactics like concealing URL addresses, deceiving deep learning models, and attackers frequently change URLs, which presents obstacles to effective detection. In this study, we introduce a robust multi-channel temporal convolutional network (TCN) approach designed for precise phishing website detection, emphasizing the extraction of features from both URL and HTML components. Our hybrid methodology combines URL character embedding and various handcrafted features, using a two-channel input structure. These inputs undergo embedding and SpatialDropout1D before integration into diverse TCN layers, capturing features effectively. Outputs from TCN layers in both channels are concatenated, globally max-pooled, and late fused for binary webpage classification. Our approach demonstrates notable contributions, including novel features, meticulous architecture, and heightened accuracy. Experimentally, our approach achieves 99.81% accuracy on our dataset and 98.16% and 98.96% on two benchmark datasets, respectively. It outperforms state-of-the-art methods on real phishing webpages, demonstrating superior performance with reduced reliance on labeled data.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"238 ","pages":"Article 104170"},"PeriodicalIF":7.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654552","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}