Journal of Web Engineering最新文献

{"title":"Overcoming Terrain Challenges with Edge Computing Solutions: Optimizing WSN Deployments Over Obstacle Clad-Irregular Terrains","authors":"Shekhar Tyagi;Abhishek Srivastava","doi":"10.13052/jwe1540-9589.2384","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2384","url":null,"abstract":"Wireless sensor networks (WSNs) are primarily used for real time data collection and monitoring, especially in environments where direct human involvement is challenging due to harsh conditions. Optimized deployment of WSN nodes is a long standing issue and several ideas have been proposed to address this. Existing deployment strategies are mostly based on the assumption that the terrain for deployment of nodes is perfectly regular. This is an impractical assumption and in this paper we address this gap by proposing a deployment strategy for WSN nodes over irregular terrains. Such terrains comprise uneven elevations, morphology and vegetation based obstacles, rocky obstacles, and so on. Our approach comprises extraction of satellite images of the region of interest (RoI) from Google Earth and generating a KML file (Keyhole Markup Language) for the RoI containing the latitude, longitude, and elevation values of each and every point in the RoI. These points are used to generate a contour map of the RoI containing detailed terrain morphology. A radio frequency path loss model in combination with an advanced inverse distance weighted (IDW)-interpolation technique is proposed to ensure connectivity and coverage in such irregular terrains with varying nature of obstacles. The technique effectively detects occlusions and enables effective deployment. This edge computing approach involves real-time decision-making at the network edge (the sensor nodes) leading to a deterministic deployment of motes in diverse terrain conditions with various obstacles. The approach is compared with existing deployment techniques and the results validate its efficacy. To demonstrate the practicality of our approach, we have also implemented a deployment in real-world environmental conditions, validating our approach in challenging terrains.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 8","pages":"1127-1154"},"PeriodicalIF":0.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Software Practice and Experience on Smart Mobility Digital Twin in Transportation and Automotive Industry: Toward SDV-Empowered Digital Twin Through EV Edge-Cloud and AutoML","authors":"Jonggu Kang","doi":"10.13052/jwe1540-9589.2385","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2385","url":null,"abstract":"A digital twin is a virtual representation of a physical asset that serves as a pivotal convergence technology that facilitates real-time prediction, optimization, monitoring, control, and improved decision-making. It can be widely applied to various domains, such as automotive, manufacturing, logistics, and smart cities. The automotive industry, in particular, is actively integrating digital twins throughout the product life cycle, from research and development, production, sales, and services to enhance the overall customer experience. This paper presents insights and lessons learned on software practice and experience related to implementing smart mobility digital twins, focusing on the potential of transportation digital twins built from data collected by electric vehicles (EVs) with EV edge cloud and automated machine learning (AutoML). Despite current limitations in data sufficiency, we forecast that, as the SDV trend accelerates and the adoption of EVs increases, the digital twin will become essential for the intelligent transportation system (ITS) in future smart cities, enabling accurate traffic predictions even in areas with limited road infrastructure. The successful integration of real-time data, high-performance prediction models, and automated service environments will enhance the effectiveness toward an SDV edge-empowered transportation digital twin.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 8","pages":"1155-1180"},"PeriodicalIF":0.7,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Web Intelligent Hotel Management Framework Based on IoT and Generative AI","authors":"Ling Luo","doi":"10.13052/jwe1540-9589.2371","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2371","url":null,"abstract":"The hotel industry has faced numerous opportunities and challenges due to the advent of the artificial intelligence (AI) and the data-driven era. To address this, a novel augmented online performance analysis model is proposed for hotel management operations. This model seamlessly integrates the Internet of Things (IoT), generative AI technologies, and web engineering, allowing for the collection and analysis of multifaceted operational data. Consequently, real-time insights pertaining to room reservations, occupancy rates, and revenue streams are derived, serving as the basis for data-driven optimization strategies. Moreover, by incorporating generative AI technologies, the proposed model demonstrates the ability to dynamically generate predictive models, simulate scenarios, synthesize actionable insights, and adapt to evolving trends. As a result, it offers adaptive solutions for complex hotel management scenarios that were previously beyond the reach of traditional methods.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"885-912"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10815717","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890234","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}

{"title":"An Effective Scheme to Accelerate NeRF for Web Applications Using Hash-Based Caching and Precomputed Features","authors":"OkHwan Bae;Chung-Pyo Hong","doi":"10.13052/jwe1540-9589.2376","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2376","url":null,"abstract":"In recent years, 3D reconstruction and rendering technologies have become increasingly important in various web-based applications within the field of web technology. In particular, with the emergence of technologies such as WebGL and WebGPU, which enable real-time 3D content rendering in web browsers, immersive experiences and interactions on the web have been significantly enhanced. These technologies are widely used in applications such as 3D visualization of virtual products or 3D exploration of building interiors on real estate websites. Through these advancements, users can experience 3D content directly in their browsers without the need to install additional software, greatly expanding the possibilities of the web. Amidst this trend, the neural radiance field (NeRF) has garnered attention as a cutting-edge technology that improves the accuracy of 3D reconstruction and rendering. NeRF is a technique widely used in computer vision and graphics for reconstructing 3D spaces from 2D images taken from multiple viewpoints. By predicting the color and density of each pixel, NeRF captures the complex 3D structure and optical properties of a scene, enabling highly accurate 3D reconstructions. However, NeRF's primary limitation is the time-consuming nature of both the training and inference processes. Research efforts to address this issue have focused on two key areas: optimizing network architectures and training procedures to accelerate scene learning, and improving inference speed for faster rendering. While progress has been made in enhancing training speed, challenges remain in improving the inference process. To address these limitations, we propose a two-step approach to significantly improve NeRF's performance. First, we optimize the training phase through a multi-resolution hash encoding technique, reducing the computational complexity and speeding up the learning process. Second, we accelerate the inference phase by caching the input data of the NeRF MLP, which allows for faster rendering without sacrificing quality. Our experimental results demonstrate that this approach reduces training time by 68.42% and increases inference speed by 98.18%.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"1041-1056"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10815716","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890391","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}

{"title":"Cluster-Based Data Sharing for Web 3.0 in Intelligent Transportation Systems","authors":"Mohammed Alkhathami","doi":"10.13052/jwe1540-9589.2375","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2375","url":null,"abstract":"Intelligent transportation system (ITS) applications are dependent on secure and robust wireless data sharing among vehicles and roadside units (RSUs). Multiple types of data are shared among the ITS devices which include safety information, road services, web based information retrieval and task computation. Web 3.0 offers a decentralized, distributed and secure data sharing mechanism for ITSs. Allocation of wireless channel resources are critical to enable an efficient ITS system. In this paper, a novel data sharing technique for Web 3.0 based ITS is presented that relies on an intelligent clustering algorithm. In the first step, the proposed technique uses a K-means algorithm to find groups of vehicles with similar speeds. In the second step, each cluster is assigned an RSU which has the highest average data rate with all vehicles in the cluster. This is achieved by using a stable matching technique so that there is no contention and each cluster is assigned a separate RSU. The algorithm periodically updates the clusters and RSU allocation for web data sharing between vehicles and RSUs. Simulation results show that the proposed clustering-based data sharing technique improves sum-rate by 20% and reduces network delay by 23%.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"1025-1040"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10815633","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890389","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}

{"title":"A Data Alignment Method for Network Packet Capture Based on DBSCAN","authors":"Jiarui Lu;Qinggang Su","doi":"10.13052/jwe1540-9589.2374","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2374","url":null,"abstract":"This paper investigates the issues of packet alignment and consistency among PLC devices based on industrial network environments, aiming to ensure the integrity and accuracy of packets from sender to receiver. To achieve this goal, we propose an anomaly detection method that combines the DBSCAN clustering algorithm with the 3-sigma principle to identify and handle abnormal packets that may occur during transmission. By comparing the data between the sending and receiving ends, and analyzing based on timestamps and data content, we validate the alignment of packets in the network environment. Experimental results demonstrate that the proposed method effectively detects and corrects packet loss or delay jitter, thereby enhancing the reliability of communication between PLC devices and the consistency of data transmission. The scheme presented in this paper enables quicker and more precise identification of packet loss and delays, adapting well to various network load conditions. Further experimental analysis indicates that this method excels in reducing both false positive and false negative rates, and it exhibits good scalability, making it applicable to data alignment and consistency verification in other industrial automation scenarios. Ultimately, this novel solution provides stability and accuracy for data transmission among devices in a network environment.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"1003-1023"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10815714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890307","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}

{"title":"Advancing Educational Management with the ATT-MR-WL Intelligent Question-Answering Model","authors":"Ying Ba","doi":"10.13052/jwe1540-9589.2373","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2373","url":null,"abstract":"Higher education plays a critical role in cultivating talent, preserving culture, and promoting social progress. However, current challenges, such as inefficient information dissemination and low problem-solving efficiency among students, highlight the need for intelligent question-answering systems. These systems, leveraging artificial intelligence and natural language processing technologies, enable rapid and accurate responses to student queries, thereby providing intelligent support for higher education management. This study introduces the ATT-MR-WL model, a generative AI system integrating Mask R-CNN and Word2Vec+LSTM to enhance intelligent question-answering functionality. The model, customized to handle both text and visual data, is evaluated using the established VQA v2.0 dataset and a specially developed EM dataset reflecting university management scenarios. The ATT-MR-WL model demonstrates a 3% accuracy improvement over traditional methods and enhances its ability to handle multimodal queries. This research provides important insights for enhancing the efficiency and quality of higher education management and advancing the process of educational informatization.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"973-1002"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10815715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890308","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}

{"title":"Examining the Empirical Relationship Between Quality of Service (QoS) and Trust Mechanisms of Cloud Services","authors":"Pooja Goyal;Sukhvinder Singh Deora","doi":"10.13052/jwe1540-9589.2372","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2372","url":null,"abstract":"Service selection has emerged as a prominent challenge due to the flourishing demand for computing services and the dynamic nature of its resources. The increasing demand for cloud services makes it challenging to choose a provider offering equal services and facilities at costs that match those of competing providers. Apart from educating customers in the process of choosing cloud services, trust mechanisms include user reviews, reputation systems, and certifications assist to boost consumers' confidence in cloud services. The service measurement index (SMI) offers a disciplined framework combining both functional and non-functional quality of service indicators concurrently, therefore easing decision-making. The main emphasis of the research is on the fundamental elements influencing the choice of cloud services in the present environment, the identification of extra characteristics of cloud services transcending SMI, and the identification of the most suitable approach for some services. By means of the measurement of customer enjoyment and experience, QoS traits provide some insight on the impact of trust mechanisms on service acceptance. Comparisons of SMI and QoS measurements before and after trust mechanism deployment provide insightful analysis. Empirical research guides these comparisons. This study aims to clarify the interactions among QoS, trust mechanisms, and cloud service adoption as well as highlight the implications these elements have for customers and service providers. Furthermore, presented in this paper is an algorithm using a comprehensive method to trust estimation in order to ascertain the degree of confidence worthiness of certain people.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 7","pages":"913-971"},"PeriodicalIF":0.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Implementation of Sports Science and Technology Integration Infrastructure: A Case Study of Speed Skating Utilizing Web and Mobile Applications, and Information Visualization Technologies","authors":"Minkyu Kim;Soojung Park","doi":"10.13052/jwe1540-9589.2367","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2367","url":null,"abstract":"In the field of sports, there is an active discussion on and an attempt to apply technologies that integrate sports with cutting-edge science and technology for the purpose of enhancing athletic performance. In line with this trend, South Korea is supporting research on the fusion of sports and science technology at an interdepartmental level. For the improvement of performance in elite sports, it is important to consider the athlete's skills, the coach's information analysis, the scientification of equipment, and the environmental optimization. Accordingly, this study aims to propose web and mobile app technologies to establish an integrated infrastructure of sports science and technology for the three factors of athletes, equipment, and environment to improve the performance of speed skating. Furthermore, it aims to make policy recommendations to activate this integration. The application of such technologies and policy recommendations can be transferred and organically integrated into other sports, including track and field, which are time-based competitions. Additionally, it is expected that this approach will lead to the formation of new theories that consider the emotional aspects occurring in sports situations.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 6","pages":"849-868"},"PeriodicalIF":0.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10747172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595029","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}

{"title":"Research on Quantum Key, Distribution Key and Post-Quantum Cryptography Key Applied Protocols for Data Science and Web Security","authors":"Kyu-Seok Shim;Boseon Kim;Wonhyuk Lee","doi":"10.13052/jwe1540-9589.2365","DOIUrl":"https://doi.org/10.13052/jwe1540-9589.2365","url":null,"abstract":"Currently, data security is one of the most concerning research topics. The traditional RSA encryption system has become vulnerable to quantum algorithms such as Grover and Shor, leading to the development of new security systems for the quantum. As a result, quantum cryptography is gaining importance as a key element of future communication security. This study focuses on quantum key distribution protocols for data quantum encryption, aiming to achieve quantum robustness in all stages of quantum cryptography communication processes. Quantum cryptography communication requires robust quantum encryption not only between end-nodes but also between all components. Therefore, this study demonstrates the process of end-to-end data quantum encryption and proves the overall quantum robustness in this process.","PeriodicalId":49952,"journal":{"name":"Journal of Web Engineering","volume":"23 6","pages":"813-830"},"PeriodicalIF":0.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10747171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594991","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}