ICT Express最新文献_第4页

Recurrent DQN for radio fingerprinting with constrained measurements collection

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.08.001

Nicola Novello, Andrea M. Tonello

引用次数: 0

Optimizing smart city planning: A deep reinforcement learning framework

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.11.005

Junyoung Park, Jiwoo Baek, Yujae Song

引用次数: 0

Digital Twin-empowered intelligent computation offloading for edge computing in the era of 5G and beyond: A state-of-the-art survey

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2025.01.002

Hoa Tran-Dang, Dong-Seong Kim

{"title":"Digital Twin-empowered intelligent computation offloading for edge computing in the era of 5G and beyond: A state-of-the-art survey","authors":"Hoa Tran-Dang, Dong-Seong Kim","doi":"10.1016/j.icte.2025.01.002","DOIUrl":"10.1016/j.icte.2025.01.002","url":null,"abstract":"<div><div>Edge computing has emerged as a promising paradigm for addressing the latency, bandwidth, and scalability challenges associated with traditional cloud-centric architectures. Computation offloading, the process of transferring computational tasks from edge devices to more powerful remote servers or cloud infrastructure, plays a crucial role in optimizing performance and resource utilization in edge computing systems. However, traditional computation offloading techniques often face limitations related to latency, network dependency, and scalability. In this survey, we explore the integration of digital twin (DT) technology into edge computing environments to empower intelligent computation offloading decisions. DTs, virtual representations of physical entities or systems that mirror their real-world counterparts, offer opportunities to enhance situational awareness, optimize resource allocation, and enable more informed decision-making at the edge. We provide a comprehensive overview of DTs empowered intelligent computation offloading, covering the fundamentals of DTs, traditional computation offloading techniques, and their limitations in edge computing. Additionally, we discuss how DTs can address these challenges and improve computation offloading strategies, along with practical applications and use cases across various domains. Finally, we identify open research challenges and opportunities for future exploration in this emerging field. Through this survey, we aim to provide researchers, practitioners, and stakeholders with insights into the potential of DTs to revolutionize computation offloading for edge computing and drive innovation in this rapidly evolving area.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 167-180"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

On the road to the metaverse: Point cloud video streaming: Perspectives and enablers

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.11.001

Patrick Enenche , Dong Ho Kim , Dongho You

{"title":"On the road to the metaverse: Point cloud video streaming: Perspectives and enablers","authors":"Patrick Enenche , Dong Ho Kim , Dongho You","doi":"10.1016/j.icte.2024.11.001","DOIUrl":"10.1016/j.icte.2024.11.001","url":null,"abstract":"<div><div>In the rapidly evolving metaverse ecosystem, video streaming plays a vital role, offering immersive, on-demand experiences and engaging users in dynamic 3D virtual environments. Point cloud video streaming enables detailed 3D representations for applications like 3D scanning, AR, and VR. However, high data demands and complex encoding pose challenges, requiring efficient resource and latency management. As a result, user experience (UX) is critical in the metaverse, where metrics like real-time feedback, Quality of Experience (QoE), and adaptive UX design are essential for sustaining engagement in immersive 3D environments. Therefore, this paper closely examines the latest developments in point cloud video streaming, specifically focusing on user-centric, AI-driven, and low-latency techniques, transcending traditional video streaming methods. We investigate a variety of techniques, pinpoint obstacles, and chart prospective routes for elevating both the quality and depth of immersive experiences. Furthermore, our work includes a detailed qualitative comparison of these streaming paradigms. We also shed light on pivotal metaverse enhancers, such as Mobile Edge Computing (MEC), Visible Light Communication (VLC), advanced network coding techniques, and the integration of the Data Plane Development Kit (DPDK). These enablers—particularly when combined with DPDK’s capabilities in efficient data packet processing—have the potential to optimize resource allocation, strengthen reliability, reduce latency, and improve the sustainability of point cloud video streaming. Our study, therefore, offers a holistic overview of the advancing area of point cloud video streaming and outlines paths for future research and development.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 93-104"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 accurate positioning: Directionality-enhanced fingerprinting radio map

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.12.004

Beomju Shin , Taehun Kim , Taikjin Lee

{"title":"Towards accurate positioning: Directionality-enhanced fingerprinting radio map","authors":"Beomju Shin , Taehun Kim , Taikjin Lee","doi":"10.1016/j.icte.2024.12.004","DOIUrl":"10.1016/j.icte.2024.12.004","url":null,"abstract":"<div><div>The most essential element of location based service is accurate user localization. Considering the existing indoor infrastructure of the internet of things and WiFi access points, along with the widespread use of smartphones by individuals, fingerprinting technology emerges as the most promising indoor navigation system in terms of cost-effectiveness, performance, and accessibility. To estimate the user's location by fingerprinting, a fingerprinting radio map must be created in advance. The radio map contains received signal strength indicator (RSSI) vectors and its collection locations. In an indoor environment, RSSI values vary greatly depending on the collection direction, even if they are received from the same location. To compensate for this feature of RSSI, this paper proposes a new fingerprinting radio map that considers directionality. Since pedestrians can move in various directions indoors, all RSSI values collected along those directions are included in the radio map. In the location estimation step, the current location is estimated by comparing the spatial RSSI sequence of the current pedestrian with the reference points in different directions that have the highest correlation. To validate the proposed method, we analyzed the user location results using the existing radio map and the proposed radio map and found that the proposed radio map improved the positioning performance.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 149-156"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Deep learning-driven methods for network-based intrusion detection systems: A systematic review

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2025.01.005

Ramya Chinnasamy , Malliga Subramanian , Sathishkumar Veerappampalayam Easwaramoorthy , Jaehyuk Cho

引用次数: 0

Adaptive beamforming scheme for coexistence of 5G base station and radar altimeter

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-01-31 DOI: 10.1016/j.icte.2025.01.003

Jiaqi Li, Seung-Hoon Hwang

引用次数: 0

Constellation design of 32-QAM by scaling two square 16-QAMs with dual-level coding

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-01-31 DOI: 10.1016/j.icte.2025.01.008

Minhui Yu, Seunggi Choi, Hosung Park

引用次数: 0

DMAE-HU: A novel deep multitasking autoencoder for hybrid hyperspectral unmixing in remote sensing

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-01-28 DOI: 10.1016/j.icte.2025.01.007

Suresh Aala , Prudhvi Krishna Pavuluri , Anuj Deshpande , Sravan Kumar Sikhakolli , Karthikeyan Elumalai , Sunil Chinnadurai , Eswar Panchakarla , Md. Abdul Latif Sarker , Dong Seog Han

{"title":"DMAE-HU: A novel deep multitasking autoencoder for hybrid hyperspectral unmixing in remote sensing","authors":"Suresh Aala , Prudhvi Krishna Pavuluri , Anuj Deshpande , Sravan Kumar Sikhakolli , Karthikeyan Elumalai , Sunil Chinnadurai , Eswar Panchakarla , Md. Abdul Latif Sarker , Dong Seog Han","doi":"10.1016/j.icte.2025.01.007","DOIUrl":"10.1016/j.icte.2025.01.007","url":null,"abstract":"<div><div>Hyperspectral unmixing (HU) is crucial for extracting material information from hyperspectral images (HSI) obtained through remote sensing. Although linear unmixing methods are widely used due to their simplicity, they only address linear mixing effects. Nonlinear mixing models, while more complex, often focus solely on the nonlinear aspects affecting individual pixels. However, in practice, light reflected from materials within a pixel experiences linear and nonlinear interactions, necessitating a hybrid mixing model (HMM) that leverages spatial and spectral information. This work proposes a novel deep learning-based autoencoder (AE) with dual-stream decoders to enhance spectral unmixing. Our approach employs multitask learning (MTL) to process spatial and spectral information concurrently. Specifically, one decoder stream performs linear unmixing from HSI patches, while the other stream utilizes fully connected layers to capture and model the nonlinear interactions within the data. By integrating linear and nonlinear information, our method improves the accuracy of unmixing the mixed spectrum. We validate the effectiveness of our architecture on three real-world HSI datasets and compare its performance against various baseline methods. Experimental results consistently demonstrate that our approach outperforms existing methods, as evidenced by superior spectral angle distance (SAD) and mean squared error (MSE) metrics.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 329-334"},"PeriodicalIF":4.1,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Enabling low-latency digital twins for large-scale UAV networks using MQTT-based communication framework

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-01-14 DOI: 10.1016/j.icte.2025.01.001

Dohyun An , Hyeontae Joo , Hwangnam Kim

{"title":"Enabling low-latency digital twins for large-scale UAV networks using MQTT-based communication framework","authors":"Dohyun An , Hyeontae Joo , Hwangnam Kim","doi":"10.1016/j.icte.2025.01.001","DOIUrl":"10.1016/j.icte.2025.01.001","url":null,"abstract":"<div><div>In recent developments within large-scale Unmanned Aerial Vehicle (UAV) networking, ensuring the accuracy and timeliness of real-time status updates has become increasingly critical. This paper proposes a new Centralized Message Queuing Telemetry Transport (MQTT)-based Communication framework(CMQC) specifically designed to improve real-time data transmission within a simulated large-scale UAV network. The primary objective of this study is to demonstrate the superior performance of the proposed framework in comparison to traditional communication methods such as MQTT, Transmission Control Protocol (TCP) socket-based communication, and Constrained Application Protocol (CoAP). Key performance metrics such as inter-process time interval, total completion time, jitter, and Age of Information (AoI) are evaluated to substantiate these improvements. Experimental results confirm that the MQTT-based framework significantly enhances real-time update capabilities, reduces latency, and improves overall network efficiency. These findings suggest that the proposed framework is a viable solution for enabling low-latency digital twins in large-scale UAV networks.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 264-269"},"PeriodicalIF":4.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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