Journal of Network and Computer Applications最新文献

{"title":"DS-RAM: A dynamic sharding and reputation-based auditing mechanisms for blockchain consensus in IIoT","authors":"Jiali Zheng,&nbsp;Jinhui Chen,&nbsp;Shuainan Liu","doi":"10.1016/j.jnca.2025.104362","DOIUrl":"10.1016/j.jnca.2025.104362","url":null,"abstract":"<div><div>Sharding is an effective strategy to improve the scalability of blockchain, especially in the context of massive data processing in Industrial Internet of Things (IIoT) scenarios. However, existing sharding schemes often overlook factors such as node reputation, resource capacity, and historical behavior, leading to imbalanced resource allocation, which in turn causes delays in real-time data processing and compromises system security. The blockchain consensus mechanism determines how nodes reach consensus, serving as the core of system efficiency and security. However, traditional consensus mechanisms lack effective detection of malicious nodes and insufficient supervision of consensus nodes, making the system vulnerable to attacks and malicious actions. To address these issues, this paper proposes DS-RAM (Dynamic Sharding and Reputation-based Auditing Mechanism), a dynamic sharding mechanism based on the weighted K-Medoids and Canopy algorithms. It comprehensively considers factors such as node geographical location, reputation, interaction frequency, and historical behavior to optimize node allocation, ensuring balanced distribution of sharding resources, thus improving system throughput and security. Additionally, DS-RAM introduces an auditing node module, which provides additional supervision of consensus nodes based on the reputation mechanism, enabling timely detection and isolation of potential malicious nodes, thereby effectively enhancing the fault tolerance of the consensus mechanism and system security. Simulation results demonstrate that, compared to traditional sharding schemes and reputation-based blockchains, the proposed method can effectively improve sharding security and blockchain sharding performance.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104362"},"PeriodicalIF":8.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261939","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":"Blockchain for the metaverse: Recent advances, taxonomy, and future challenges","authors":"Abdullah Yousafzai ,&nbsp;Muhammad Mohsan Sheeraz ,&nbsp;Ganna Pogrebna ,&nbsp;Jon Crowcroft ,&nbsp;Ibrar Yaqoob","doi":"10.1016/j.jnca.2025.104355","DOIUrl":"10.1016/j.jnca.2025.104355","url":null,"abstract":"<div><div>The metaverse is a shared virtual 3D space that combines immersive experiences with applications in gaming, social interactions, commerce, and more. It is rapidly becoming a reality, driven by advances in virtual reality, augmented reality, artificial intelligence, blockchain, and other emerging technologies. Among these, blockchain technology enables secure and decentralized ownership as well as seamless interoperability of virtual assets. Non-fungible tokens ensure verifiable ownership and fraud prevention, while smart contracts facilitate automated peer-to-peer transactions. Blockchain’s security and transparency promote trust and innovation, laying the foundation for a connected and user-driven metaverse ecosystem. In this paper, we explore the role of blockchain technology as a key enabler for the metaverse, providing solutions for decentralization, governance through decentralized autonomous organizations, interoperable mechanisms, digital asset ownership, traceability, auditing, and identity management. We present the key difference between traditional virtual worlds and the metaverse, and why blockchain is preferred over other decentralized technologies for the metaverse. We comprehensively review recent advances in metaverse system architectures, focusing on state-of-the-art solutions and lessons learned. We compare the existing literature based on key parameters; namely, contributions, advantages, limitations, and applications. We present key challenges, including deepfake threats, identity theft and brand infringement risks, mental health risks, digital safety and gambling risks, virtual world laws and regulations, and privacy and data security concerns. We outline future recommendations for enabling a sustainable and user-friendly metaverse ecosystem.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104355"},"PeriodicalIF":8.0,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261937","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":"Next-generation AI for advanced threat detection and security enhancement in DNS over HTTPS","authors":"Basharat Ali,&nbsp;Guihai Chen","doi":"10.1016/j.jnca.2025.104326","DOIUrl":"10.1016/j.jnca.2025.104326","url":null,"abstract":"<div><div>The widespread adoption of DNS over HTTPS(DoH) has inaugurated a new paradigm of network privacy through the encryption of DNS queries; paradoxically, this very mechanism has been weaponized by malicious actors to orchestrate convert cyberattacks ranging from polymorphic malware delivery and data exfiltration to command-and-control (C2) operations. Classic signature-based solutions that rely on static security policies and packet-depth inspection are rendered useless in the face of encrypted DoH traffic, and today’s AI-driven defense solutions typically fail to achieve adversarial robustness, explainability, and real-time scalability. Bridging these gaps, this paper proposes an AI framework that integrates the best practices in machine learning together with secure execution environments to offer resilience, transparency, and low-latency DoH threat detection. Specifically, Capsule Networks (CapsNets) are used to learn hierarchical traffic flow patterns, Graph Transformers to uncover temporal anomalies, and Contrastive Self-Supervised Learning (CSSL) to leverage massive unlabeled datasets. Adversarial robustness is reinforced through perturbation-aware training and mutation-driven fuzzing simulations, while interpretability is enhanced via SHAP and LIME, rendering AI decision-making processes more intelligible to analysts. A distributed Apache Flink/Kafka pipeline enables real-time processing of DoH streams at scale, reducing detection latency by 50% compared to batch-oriented systems. Furthermore, Trusted Execution Environments(TEEs) safeguard model inference against tempering, mitigating insider threats and runtime exploitation. Empirical evaluation on the doh_real_world_2022 dataset demonstrates 99.1% detection accuracy with CapsNets, 98.8% with Graph Transformers, and an 80% improvement in adversarial resilience. These developments collectively propel the discipline of encrypted traffic analysis and establish a benchmark for safeguarding cybersecurity protocols such as QUIC and HTTP/3 that are gaining traction. The findings validate the feasibility of AI-driven, privacy-augmented security systems during an era of escalating cyber-attacks and demands algorithmic transparency.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104326"},"PeriodicalIF":8.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261665","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":"Reinforcement learning based multi-agent system for smart microgrid","authors":"Niharika Singh ,&nbsp;Kishu Gupta ,&nbsp;Ashutosh Kumar Singh ,&nbsp;Perumal Nallagownden ,&nbsp;Irraivan Elamvazuthi","doi":"10.1016/j.jnca.2025.104339","DOIUrl":"10.1016/j.jnca.2025.104339","url":null,"abstract":"<div><div>Smart microgrid (SMG) communication networks face significant challenges in maintaining high Quality of Service (QoS) due to dynamic load variations, fluctuating network conditions, and potential component faults, which can increase latency, reduce throughput, and compromise fault recovery. The growing integration of distributed renewable energy resources demands adaptive and intelligent routing mechanisms capable of operating efficiently under such diverse and fault-prone conditions. This paper presents a Q-Reinforcement Learning-based Multi-Agent Bellman Routing (QRL-MABR) algorithm, which enhances the traditional MABR approach by embedding a Q-learning module within each network agent. Agents dynamically learn optimal routing policies, balance exploration and exploitation action selection with adaptive temperature scaling, and jointly optimize latency, throughput, jitter, convergence speed, and fault resilience.</div><div>Simulations on IEEE 9, 14, 34, 39, and 57 bus SMG testbeds demonstrate that QRL-MABR significantly outperforms conventional routing protocols (MABR, RIP, OLSR, OSPFv2) and advanced RL-based algorithms (SN-MAPPO, DDQL, MDDPG, SARSA-<span><math><mi>λ</mi></math></span>, TD3), achieving 16%–28% delay reduction, 14%–16% throughput gains, 17%–21% jitter improvement, and superior fault recovery. Thus, QRL-MABR provides a robust, scalable, and intelligent framework for next-generation smart microgrids.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104339"},"PeriodicalIF":8.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223412","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":"Anonyma: Anonymous invitation-only registration in malicious adversarial model","authors":"Sanaz Taheri Boshrooyeh,&nbsp;Alpteki̇n Küpçü,&nbsp;Öznur Özkasap","doi":"10.1016/j.jnca.2025.104337","DOIUrl":"10.1016/j.jnca.2025.104337","url":null,"abstract":"<div><div>In invitation-based systems, a new user can register only after obtaining a threshold number of invitations from existing members. The newcomer submits these invitations to the system administrator, who verifies their legitimacy. In doing so, the administrator inevitably learns who invited whom. This inviter–invitee relationship is itself privacy-sensitive information, since knowledge of it can enable inference attacks in which an invitee’s profile (e.g., political views or location) is deduced from the profiles of their inviters. To address this problem, we propose <span><math><mrow><mi>A</mi><mi>n</mi><mi>o</mi><mi>n</mi><mi>y</mi><mi>m</mi><mi>a</mi></mrow></math></span>, an anonymous invitation-based system in which even a corrupted administrator, colluding with a subset of members, cannot determine inviter–invitee relationships. We formally define the notions of <em>inviter anonymity</em> and <em>invitation unforgeability</em>, and provide formal proofs that <span><math><mrow><mi>A</mi><mi>n</mi><mi>o</mi><mi>n</mi><mi>y</mi><mi>m</mi><mi>a</mi></mrow></math></span> achieves both against a <em>malicious</em> and <em>adaptive adversary</em>. Our design ensures constant cost for authenticating new registrations, unlike existing approaches where invitation generation and verification incur overhead linear in the total number of members. Moreover, <span><math><mrow><mi>A</mi><mi>n</mi><mi>o</mi><mi>n</mi><mi>y</mi><mi>m</mi><mi>a</mi></mrow></math></span> scales efficiently: once a user joins, the administrator can immediately issue credentials enabling the newcomer to act as an inviter without re-keying existing members. We also design <span><math><mrow><mi>A</mi><mi>n</mi><mi>o</mi><mi>n</mi><mi>y</mi><mi>m</mi><mi>a</mi><mi>X</mi></mrow></math></span>, a cross-network extension that supports anonymous third-party authentication, allowing invitations issued in one system to be used for registration in another.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104337"},"PeriodicalIF":8.0,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223413","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":"HERALD: Hybrid Ensemble Approach for Robust Anomaly Detection in encrypted DNS traffic","authors":"Umar Sa’ad ,&nbsp;Demeke Shumeye Lakew ,&nbsp;Nhu-Ngoc Dao ,&nbsp;Sungrae Cho","doi":"10.1016/j.jnca.2025.104342","DOIUrl":"10.1016/j.jnca.2025.104342","url":null,"abstract":"<div><div>The proliferation of encrypted Domain Name System (DNS) traffic through protocols like DNS over Hypertext Transfer Protocol Secure presents significant privacy advantages but creates new challenges for anomaly detection. Traditional security mechanisms that rely on payload inspection become ineffective, necessitating advanced strategies capable of detecting threats in encrypted traffic. This study introduces the Hybrid Ensemble Approach for Robust Anomaly Detection (HERALD), a novel framework designed to detect anomalies in encrypted DNS traffic. HERALD combines unsupervised base detectors, including Isolation Forest (IF), One-Class Support Vector Machine (OCSVM), and Local Outlier Factor (LOF), with a supervised Random Forest meta-model, leveraging the strengths of both paradigms. Our comprehensive evaluation demonstrates HERALD’s exceptional performance, achieving 99.99 percent accuracy, precision, recall, and F1-score on the CIRA-CIC-DoHBrw-2020 dataset, while maintaining competitive computational efficiency with 110s training time and 2.2ms inference time. HERALD also demonstrates superior generalization capabilities on cross-dataset evaluations, exhibiting minimal performance degradation of only 2-4 percent when tested on previously unseen attack patterns, outperforming purely supervised models, which showed 5-8 percent degradation. The interpretability analysis, incorporating feature importance, accumulated local effects, and local interpretable model-agnostic explanations, provides insights into the relative contributions of each base detector, with OCSVM emerging as the most influential component, followed by IF and LOF. This study advances the field of network security by offering a robust, interpretable, and adaptable solution for detecting anomalies in encrypted DNS traffic that balances a high detection rate with a low false-positive rate.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104342"},"PeriodicalIF":8.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223445","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":"A robust fault-tolerant framework for VM failure predication and efficient task scheduling in dynamic cloud environments","authors":"S. Sheeja Rani ,&nbsp;Oruba Alfawaz ,&nbsp;Ahmed M. Khedr","doi":"10.1016/j.jnca.2025.104340","DOIUrl":"10.1016/j.jnca.2025.104340","url":null,"abstract":"<div><div>Due to the dynamic nature of cloud computing, maintaining fault-tolerance is essential to ensure the reliability and performance of virtualized environments. Failures in Virtual Machines (VMs) disrupt the seamless operation of cloud-based services, making it vital to implement a strong failure prediction system. As a solution, this work proposes a Segmented Regressive Learning-based Multivariate Raindrop Optimized Lottery Scheduling (SRL-MROLS) for dynamic cloud environments. Initially, the VM failure prediction is carried out using a Segmented Regressive Q-learning algorithm, where a set of VMs is provided as input. Segmented regression analyzes the average failure rate of VMs, while a reward-based framework guides the decision-making process for accurate failure prediction. Once a failure is predicted, a relocation process is triggered, involving the migration of workloads or tasks from the failing VM to an alternate VM. Next, a Multivariate Elitism Raindrop Optimization approach is employed to identify the optimal VM for task migration. Finally, a Deadline-Aware Stochastic Prioritized Lottery Scheduling is employed for efficient allocation of tasks to the selected VMs, maintaining seamless operations even in the event of VM failures. This process significantly improves task scheduling by maximizing throughput and minimizing response time in cloud environments. Experimental results demonstrate the superior performance of SRL-MROLS across different metrics. Specifically, it achieves an average improvement of 6.4% in failure prediction accuracy, 27.4% in throughput, and a 13% reduction in response time. Additionally, it reduces failure prediction time by 15%, migration cost by 14.3%, and makespan by 15%, significantly outperforming conventional techniques.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104340"},"PeriodicalIF":8.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181227","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":"Securing edge based smart city networks with software defined Networking and zero trust architecture","authors":"Abeer Iftikhar ,&nbsp;Faisal Bashir Hussain ,&nbsp;Kashif Naseer Qureshi ,&nbsp;Muhammad Shiraz ,&nbsp;Mehdi Sookhak","doi":"10.1016/j.jnca.2025.104341","DOIUrl":"10.1016/j.jnca.2025.104341","url":null,"abstract":"<div><div>Smart cities are rapidly evolving by adopting Internet of Things (IoT) devices, edge and cloud computing, and mobile connectivity. While these advancements enhance urban efficiency and connectivity, they also significantly increase the risk of cyber threats targeting critical infrastructure. Modern interdependent systems require flexible resilience, allowing them to adapt to changing conditions while maintaining core functions. Smart city networks, however, face unique security vulnerabilities due to their scale and heterogeneity. Altered to industry expectations and requirements, traditional security models are generally restrictive. With its \"never trust, always verify' motto, the Zero Trust (ZT) security model starkly differs from traditional models. ZT builds on network design by mandating real time identity verification, giving minimum access permission and mandating respect for the principle of least privilege. Software Defined Networking (SDN) extends one step further by offering central control over the network, policy based autonomous application and immediate response to anomalies. To address these challenges, our proposed Trust-based Resilient Edge Networks (TREN) framework integrates ZT principles to enhance smart city security. Under the umbrella of SDN controllers, SPP, the underpinning component of TREN, performs real time trust analysis and autonomous policy enforcement, for instance, applying high level threat defense mechanisms. TREN dynamically defends against advanced threats like DDoS and Sybil attacks by isolating malicious nodes and adapting defense tactics based on real-time trust and traffic analysis. Trust analysis and policy control modules provide dynamic adaptive coverage, permitting effective proactive defense. Mininet-based simulations demonstrate TREN's efficacy, achieving 95 % detection accuracy, a 20 % latency reduction, and a 25 % increase in data throughput when compared to baseline models.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104341"},"PeriodicalIF":8.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145254748","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":"A profit-effective function service pricing approach for serverless edge computing function offloading","authors":"Siyuan Liu ,&nbsp;Li Pan ,&nbsp;Shijun Liu","doi":"10.1016/j.jnca.2025.104338","DOIUrl":"10.1016/j.jnca.2025.104338","url":null,"abstract":"<div><div>In recent years, edge computing services have continued to develop and have been better integrated with serverless computing, leading to the improvement of the performance and concurrent request handling capabilities of edge servers. Therefore, an increasing number of IoT devices are willing to pay a certain amount of service processing fees to offload some computing tasks to edge servers for execution, with the aim of meeting their latency requirements. However, the computing capacity and storage space of edge servers at a single base station are still limited. Therefore, base stations must decide which task images to cache for future execution and price these computing services to control the computing offloading of IoT devices, so as to maximize their expected profit under the constraints of limited computing capacity and memory space. In this paper, we stand from the perspective of base stations and formulate the caching and pricing of function images at a base station, as well as the function offloading process of IoT devices, as a Markov Decision Process (MDP). We adopt a Proximal Policy Optimization (PPO)-based function service pricing adjustment algorithm to optimize the profit of base stations. Finally, we evaluate our approach through simulation experiments and compare it with baseline methods. The results show that our approach can significantly improve base stations’ expected profit in various scenarios.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104338"},"PeriodicalIF":8.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160067","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":"Elastic RAN slicing technology with multi-timescale SLA assurances for heterogeneous services provision in 6G","authors":"Yamin Shen ,&nbsp;Ping Wang ,&nbsp;Chiou-Jye Huang ,&nbsp;Shenxu Kuang ,&nbsp;Song Li ,&nbsp;Zihan Li","doi":"10.1016/j.jnca.2025.104330","DOIUrl":"10.1016/j.jnca.2025.104330","url":null,"abstract":"<div><div>Digital transformation brings diverse applications along with varying Quality of Service (QoS) and isolation requirements. Network slicing, a key 5G technology anticipated to persist in 6G, aims to meet these heterogeneous requirements. However, due to conflicting usage of scarce resources among services, especially with multi-timescale Service Level Agreement (SLA) requirements including QoS and isolation, implementing slicing in the Radio Access Network (RAN) domain is a significant challenge. Therefore, this paper formulates the radio resource allocation problem posed by the coexistence of multiple URLLC (Ultra-Reliable and Low-Latency Communications) with varying delay requirements and eMBB (Enhanced Mobile Broadband) as a multi-timescale optimization problem. Consequently, a novel MPC (Model Predictive Control)-based RAN slicing resource allocation model called MPC-RSS is proposed. Specifically, MPC-RSS ensures elastic QoS through delay-tracking mechanism and far-sighted schemes. Meanwhile, it maintains elastic isolation by introducing logical and physical isolation constraint terms. Compared with the existing state-of-the-art approaches, simulation results show that MPC-RSS can achieve better and more elastic SLA performance. Our proposal provides a choice for 6G RAN to empower vertical industries achieving digital upgrades.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"244 ","pages":"Article 104330"},"PeriodicalIF":8.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223446","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}