Journal of Web Engineering最新文献_第3页

Adaptive Sampling for Real-Time Neural View Synthesis on the Web with Reinforcement Learning 基于强化学习的网络实时神经视图合成的自适应采样

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-06 DOI: 10.13052/jwe1540-9589.2521

OkHwan Bae;Chung-Pyo Hong

{"title":"Adaptive Sampling for Real-Time Neural View Synthesis on the Web with Reinforcement Learning","authors":"OkHwan Bae;Chung-Pyo Hong","doi":"10.13052/jwe1540-9589.2521","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2521","url":null,"abstract":"The proliferation of immersive 3D web applications, from e-commerce product viewers to virtual real estate tours, has created a critical need for high-quality, real-time rendering directly within the browser. Neural radiance fields (NeRF) offer unprecedented photorealism but are hamstrung by immense computational demands, making their deployment on resource-constrained web platforms a significant web engineering challenge. The core bottleneck is NeRF's reliance on dense point sampling for volume rendering. This paper introduces a novel framework that directly tackles this challenge through a pioneering adaptive sampling technique powered by reinforcement learning. We name this framework PPO-NeRF. It integrates the rapid training capabilities of Instant-NGP's hash encoding with an agent trained via proximal policy optimization (PPO). This agent learns to adaptively predict the minimal set of crucial sample points along each camera ray, dynamically pruning computationally redundant samples to optimize rendering specifically for web-based, real-time scenarios. Experimental results demonstrate that PPO-NeRF significantly lowers the barrier to web deployment. Compared to the original NeRF, it reduces training time by approximately 73.63%, enabling faster content iteration for web developers. More critically, our adaptive sampling slashes rendering time by approximately 44.7% and VRAM usage by approximately 29.9%, while maintaining comparable visual fidelity. These gains directly translate to faster load times, smoother user interaction, and broader device compatibility. In conclusion, PPO-NeRF provides a practical solution to NeRF's long-standing performance bottlenecks, establishing a viable pathway for deploying high-fidelity, interactive 3D experiences at scale across the modern web.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 2","pages":"135-152"},"PeriodicalIF":1.0,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11424339","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Towards Real-Time Underwater Object Detection and Identification: Integrating Acoustic Sensing with Edge Computing 面向实时水下目标检测与识别：声学传感与边缘计算的融合

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2532

Shekhar Tyagi;Akshat Shah;Abhishek Srivastava

{"title":"Towards Real-Time Underwater Object Detection and Identification: Integrating Acoustic Sensing with Edge Computing","authors":"Shekhar Tyagi;Akshat Shah;Abhishek Srivastava","doi":"10.13052/jwe1540-9589.2532","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2532","url":null,"abstract":"In this work, we present a method to streamline underwater object detection, environmental monitoring, and surveillance. The proposed system employs an underwater acoustic sensor (UAS) network to detect and analyses objects within a three-dimensional underwater space, considering constraints imposed by acoustic path loss. The approach combines three key techniques-Delaunay's convex hull-based reconstruction, the laws of magnetic equilibrium, and the Doppler effect-to improve the identification of object type, shape, location, and motion. Sensors are arranged in an optimized grid, with each grid containing eight sensors and a central insulated magnetometer to measure net magnetic field intensity. Data collected by the sensors is transmitted to a surface anchor or sink node for further processing and analysis. A prototypical deployment in an artificial pond further validates our approach, using a waterproof ultrasonic sensor, an electromagnetic coil, and a magnetometer synchronized via Arduino Uno. Real-time measurements confirm accurate detection and tracking of objects, demonstrating the effectiveness and feasibility of the proposed edge-enabled underwater monitoring framework.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 3","pages":"325-350"},"PeriodicalIF":1.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481602","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

LLM-Driven Multi-Agent Architecture for QoS-Aware Server Recommendation in Mobile-Edge-Cloud Environments 移动边缘云环境中qos感知服务器推荐的llm驱动多代理体系结构

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2533

Eunjeong Ju;Junghwa Lee;Duksan Ryu;Suntae Kim;Jongmoon Baik

{"title":"LLM-Driven Multi-Agent Architecture for QoS-Aware Server Recommendation in Mobile-Edge-Cloud Environments","authors":"Eunjeong Ju;Junghwa Lee;Duksan Ryu;Suntae Kim;Jongmoon Baik","doi":"10.13052/jwe1540-9589.2533","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2533","url":null,"abstract":"Mobile edge computing (MEC) has become a key paradigm for supporting latency-sensitive and bandwidth-intensive applications. However, existing server recommendation methods rely on static heuristics and lack adaptability to dynamic environments with incomplete quality of service (QoS) data. This study aims to address these limitations by enabling adaptive and context-aware server recommendations that effectively manage user mobility and missing QoS information in real time. We propose an intelligent MEC server recommendation framework built on a multi-agent architecture spanning mobile, edge, and cloud layers. The mobility layer predicts user movement, the edge layer performs LLM-based decision-making, and the cloud layer imputes QoS through multi-source data fusion. Lightweight gRPC and WebSocket protocols ensure scalability across multi-user environments. Experiments demonstrate that the proposed system outperforms the baseline, achieving 85% Top-1 accuracy and confirming its effectiveness and scalability for real-world MEC applications.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 3","pages":"351-372"},"PeriodicalIF":1.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Project Evolution-Aware Prompting of LLMs for Just-in-Time Defect Prediction in Edge-Cloud Systems 边缘云系统中实时缺陷预测的llm项目进化感知提示

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2535

Inseok Yeo;Sungu Lee;Duksan Ryu;Jongmoon Baik

{"title":"Project Evolution-Aware Prompting of LLMs for Just-in-Time Defect Prediction in Edge-Cloud Systems","authors":"Inseok Yeo;Sungu Lee;Duksan Ryu;Jongmoon Baik","doi":"10.13052/jwe1540-9589.2535","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2535","url":null,"abstract":"Edge-cloud systems, which bring computing, storage, and networking resources closer to end-users, offer significant advantages in reducing latency and enabling real-time data processing. These systems are increasingly deployed across diverse domains, such as smart manufacturing, autonomous vehicles, and large-scale IoT networks, to support big data-driven services that require continuous analytics and rapid response. Ensuring software reliability in these environments is critical, which has led to growing attention on just-in-time (JIT) defect prediction as an effective technique for prioritizing testing efforts by identifying code changes likely to introduce defects. However, existing techniques struggle to perform accurately on new or low-data projects due to insufficient training data. In this paper, we propose PROPER-SDP, a prompt-based approach that leverages large language models. By incorporating project evolution data directly into prompts, our approach enables LLMs to effectively capture the contextual information essential for accurate JIT defect prediction. By doing so, we effectively address the cold-start problem, allowing accurate JIT defect prediction even in the absence of project-specific training data. Evaluation results demonstrate that our method significantly improves prediction performance, surpassing baseline methods by an average of 19.7% in F1-score. Our approach enables reliable JIT defect prediction even in rapidly evolving, resource-constrained edge-cloud systems.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 3","pages":"395-416"},"PeriodicalIF":1.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481603","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Spatio-Temporal Mamba for User Mobility Prediction in Mobile Edge Computing 移动边缘计算中用户移动性预测的时空曼巴

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2536

Jeonghwa Lee;Eunjeong Ju;Duksan Ryu;Suntae Kim;Jongmoon Baik

引用次数: 0

Data-Driven Adaptive ML-Enabled Edge-Cloud System Framework for Safe and Efficient Autonomous Systems 数据驱动的自适应机器学习边缘云系统框架，用于安全高效的自治系统

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2531

Eunho Cho;In-Young Ko

{"title":"Data-Driven Adaptive ML-Enabled Edge-Cloud System Framework for Safe and Efficient Autonomous Systems","authors":"Eunho Cho;In-Young Ko","doi":"10.13052/jwe1540-9589.2531","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2531","url":null,"abstract":"Machine learning (ML)-enabled systems like autonomous driving systems (ADSs) face challenges meeting safety and performance requirements in diverse environments, especially in resource-constrained, latency-sensitive edge-cloud settings. These challenges often arise from the ML models' limitations, including poor generalization to unseen conditions. Static ML models often struggle to generalize to unseen scenarios, particularly under the latency and resource constraints of edge-cloud infrastructure. Adaptive algorithms using ML system switching have been proposed, but existing approaches frequently lack generalizability, support for common black-box systems, and effective use of distributed edge-cloud resources. This paper presents a novel adaptive ML-enabled edge-cloud system framework to address these shortcomings. Our framework combines cloud-based pre-runtime analysis, which leverages simulation for behavioral understanding and scenario-to-system mapping, with collaborative edge-cloud runtime adaptation featuring dynamic ML model switching. It supports black-box systems and aims to balance safety and efficiency by utilizing appropriate edge and cloud resources situationally. Preliminary CARLA-based evaluation of the edge runtime component suggests our framework can potentially improve the safety-efficiency tradeoff compared to single-model ADSs in some scenarios. Moreover, extensive experiments using the MetaDrive simulator with 100,000 randomized driving scenarios demonstrate that the adaptive system improves safety by 2.6% while doubling computational efficiency compared to a single-model baseline. These results validate the framework's scalability and the feasibility of data-driven scenario-system mapping for adaptive ML-enabled autonomous systems operating across edge and cloud environments.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 3","pages":"299-324"},"PeriodicalIF":1.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481601","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Learning by Experiencing: An Immersive Digital Twin Tool for ECG Education 体验式学习：心电教育的沉浸式数字孪生工具

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-03-01 Epub Date: 2026-04-14 DOI: 10.13052/jwe1540-9589.2534

Daniel Flores-Martin;Francisco Díaz-Barrancas;Pedro J. Pardo;Javier Berrocal;Juan M. Murillo

{"title":"Learning by Experiencing: An Immersive Digital Twin Tool for ECG Education","authors":"Daniel Flores-Martin;Francisco Díaz-Barrancas;Pedro J. Pardo;Javier Berrocal;Juan M. Murillo","doi":"10.13052/jwe1540-9589.2534","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2534","url":null,"abstract":"Practical training in electrocardiogram (ECG) interpretation remains uneven, particularly in resource-limited settings, despite the central role of ECGs in cardiovascular diagnosis. This work evaluates whether an ECG-focused digital twin that integrates interactive simulation and deep learning guidance can achieve educationally valid realism, improve recognition of patterns and abnormalities through interactivity, and enhance accuracy and learner motivation via predictive feedback. We present ECGTwinMentor, a cross-platform system that synthesizes parameterized ECG waveforms, enables fine-grained control of physiologic variables, and delivers immediate predictive feedback for formative assessment. The diagnostic model supports low-latency inference on modest hardware. Validation with healthcare experts and medical students showed positive evaluations for realism, usability, and integration potential. Experts reported average ratings between 3.5 and 4.5 out of 5, while students rated usability between 4.6 and 4.8 and motivation and realism at 5.0, with most items scoring at least 4. These findings support the conclusion that an interactive, predictive digital twin can narrow the gap between theory and practice in ECG interpretation, offering an accessible, scalable, and reproducible approach to ECG education.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 3","pages":"373-394"},"PeriodicalIF":1.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

PK-PoMLO: Public Key Proof of ML Ownership System PK-PoMLO: ML所有权的公钥证明系统

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-01-01 DOI: 10.13052/jwe1540-9589.2514

Joyeon Park;Jinah Seo;Do. KyoungHwa;Soo Yong Park

{"title":"PK-PoMLO: Public Key Proof of ML Ownership System","authors":"Joyeon Park;Jinah Seo;Do. KyoungHwa;Soo Yong Park","doi":"10.13052/jwe1540-9589.2514","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2514","url":null,"abstract":"In this study, we propose an on-chain-based ML ownership proof system (PK-PoMLO), which combines a digital signature and a blockchain timestamp value to generate a certificate of ownership that is publicly disclosed on-chain, enabling strong claim of ML ownership. First, the owner creates a certificate signed with their private key using the hash value of the ML model and a structured message, and includes a timestamp. This is then used to generate an ML ownership certificate and registered on-chain. At this time, the owner uses their private key to create a standard signature value as a 128-bit mark and embeds it in the ML model. Anyone wishing to verify ML ownership then uses the owner's public key to compare the hash value of the on-chain ML ownership certificate with the timestamp value to verify ML ownership. In other words, we can verify the authenticity of the owner by testing whether the bit error rate (BER) between the mark extracted from the ML ownership certificate and the internally stored mark string satisfies BER <tex>$leqtau$</tex>, and verifying it with the signature value of the ML ownership certificate. To verify the results of this study, we implement and evaluate a prototype on the MNIST MLP and the Ethereum Sepolia test network.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 1","pages":"51-66"},"PeriodicalIF":1.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370661","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Agentic AI Service Architecture Based on SOA 基于SOA的代理AI服务体系结构

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-01-01 DOI: 10.13052/jwe1540-9589.2511

Dong Bin Choi;Yunhee Kang;Young B. Park

{"title":"Agentic AI Service Architecture Based on SOA","authors":"Dong Bin Choi;Yunhee Kang;Young B. Park","doi":"10.13052/jwe1540-9589.2511","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2511","url":null,"abstract":"Service-Oriented Architecture (SOA) structures applications into collections of modular, independent, and reusable services. We propose an SOA-based intelligent service agent framework for building AI applications that decomposes complex tasks into independent functional units. In the framework, the agent operates as an intelligent executor that dynamically orchestrates and invokes diverse services and tools to achieve its goals. The agent is exposed as a self-contained service with a well-defined API, allowing external applications to invoke it directly. By instrumenting requests and responses at both the service and agent layers, the framework enables tracing of the agent's capabilities, performance, and decision-making. We present the design of an operational scheme for the agent with DID handling, verifiable credentials (VC), and verifiable presentations (VP). Each of the agents collaborates on a shared workspace based on blackboard to handle tasks to reach a goal. Finally, we demonstrate its feasibility through a proof-of-concept (PoC) for Agentic AI service architecture. This proof-of-concept, structured across Phase 1 (discovery, verification, and scoped authorization) and Phase 2 (problem posting and blackboard-mediated collaboration), demonstrates that DID-backed credentialing can securely support multi-agent execution under a least-privilege operational model.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 1","pages":"1-18"},"PeriodicalIF":1.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370646","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

KeyShield: Leakage-and-Loss-Resilient Private Key Protection for Web3 KeyShield：针对Web3的防泄漏和防丢失私钥保护

IF 1 4区计算机科学

Journal of Web Engineering Pub Date : 2026-01-01 DOI: 10.13052/jwe1540-9589.2515

Ziyang Ji;Jie Zhang;Yuji Dong;Ka Lok Man;Steven Guan;Mucheol Kim

{"title":"KeyShield: Leakage-and-Loss-Resilient Private Key Protection for Web3","authors":"Ziyang Ji;Jie Zhang;Yuji Dong;Ka Lok Man;Steven Guan;Mucheol Kim","doi":"10.13052/jwe1540-9589.2515","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2515","url":null,"abstract":"Effective management of private keys is crucial to ensure the security and ownership of users' data and digital assets in the Web3 environment. However, existing solutions often fail to adequately address private key management from the user's perspective. Private key leakage and loss incidents occur frequently, resulting in significant losses of digital assets. Moreover, the conventional approach of revoking both the private and public keys after a leakage or loss accident is inconvenient in Web3, where the public key serves as the user's wallet address or digital identity. To tackle the issue of user-side private key management in Web3, this paper presents KeyShield which is a leakage-and-loss-resilient private key protection scheme. KeyShield divides the user's private key into three shares, securely stored across a primary device and a secondary device owned by the user, and a third storage module owned by the user or a semi-trusted service provider. For daily use of the private key, the user only needs to connect the primary and secondary devices. In the event of a leakage or loss, such as device theft or attack, an update process will be triggered to update the three shares, immediately invalidating the leaked or lost share while causing no changes to the public key. As a demonstration of KeyShield, we developed KeyShieldECC accessible on both Android and iOS platforms for managing Elliptic Curve Cryptography (ECC) private keys. The testing results show that for a 256-bit ECC private key, the daily use only needs 0.05 seconds and update needs 0.25 to 0.3 seconds on an ordinary smart phone.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"25 1","pages":"67-102"},"PeriodicalIF":1.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146098437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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