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IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/miot.2023.10255784

引用次数: 0

Supporting 6G Mission-Critical Services on O-RAN 在O-RAN上支持6G关键业务

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/iotm.001.2300032

Rafael Kaliski, Shin-Ming Cheng, Cheng-Feng Hung

{"title":"Supporting 6G Mission-Critical Services on O-RAN","authors":"Rafael Kaliski, Shin-Ming Cheng, Cheng-Feng Hung","doi":"10.1109/iotm.001.2300032","DOIUrl":"https://doi.org/10.1109/iotm.001.2300032","url":null,"abstract":"In the era of 6G, cellular networks will no longer be locked into a small set of equipment manufacturers; instead, cellular networks will be disaggregated and support open interfaces. Thus, there is an inherent need for networking functions to be softwarized and virtualized so that customers can apply different vendors' solutions. 6G mission-critical networks must be dependable and secure, ultra-reliable and low latency, and support high connectivity, all while being flexible enough to support custom user deployments. 6G will integrate Artificial Intelligence (AI) into the network architecture to meet the diverse user requirements of 3 <sup xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">rd</sup> party solutions. A possible 6G candidate capable of supporting the requirements above is Open Radio Access Networks (O-RAN). O-RAN enables multiple levels of AI-based control for RAN Intelligent Controllers (RICs). RICs facilitate real-time sensing, reaction, policy determination, and management of radio resources. When coupled with Multi-access Edge Computing (MEC), O-RAN enables customized per-device AI service chains that can address the needs of dynamic, diverse 6G networks in real-time. This article presents an O-RAN architecture that supports split-plane multi-component cooperative AI models that utilize multiple RIC-centric and MEC-centric control loops. Through multiple example applications and O-RAN testbeds, we demonstrate the efficacy of our proposed architecture and how it can address the multitude of 6G requirements as necessitated for mission-critical Internet of Things applications.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Collabratec 移动Collabratec

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/miot.2023.10255781

引用次数: 0

UAV-Assisted Internet of Vehicles Over Licensed and Unlicensed Spectrum: Architecture, Intelligent Resource Management, and Challenges 授权和非授权频谱上的无人机辅助车辆互联网:架构、智能资源管理和挑战

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/iotm.001.2200273

Yuhan Su, Minghui Liwang, Zhong Chen, Xianbin Wang

{"title":"UAV-Assisted Internet of Vehicles Over Licensed and Unlicensed Spectrum: Architecture, Intelligent Resource Management, and Challenges","authors":"Yuhan Su, Minghui Liwang, Zhong Chen, Xianbin Wang","doi":"10.1109/iotm.001.2200273","DOIUrl":"https://doi.org/10.1109/iotm.001.2200273","url":null,"abstract":"Benefited from their flexibility and on-demand deployment capability, unmanned aerial vehicles (UAVs) have emerged as critical aerial communication platforms in future Internet of Vehicles (IoV). However, limited spectrum resources can lead to unsatisfying data rate of IoV, which thus incur large latency, especially under congested IoV network conditions. Although UAVs and road side units (RSUs) can work within the same spectrum and increase spectral efficiency, mutual interference becomes unavoidable. To this end, this article develops a heterogeneous network architecture, in which a UAV-assisted IoV system coexists with a Wi-Fi system: the RSUs can properly occupy unlicensed spectrum to increase the capacity of the UAV-assisted IoV system while mitigating interference, without affecting the performance of the Wi-Fi system. A case study of resource management over licensed and unlicensed spectrum is investigated under the proposed architecture, where time and power are jointly optimized to maximize the sum user satisfaction of the system. We further provide an intelligent solution to tackle the problem in the considered case study. Simulations demonstrate that our proposed case can efficiently improve the sum user satisfaction of the system. Key challenges and opportunities for UAV-assisted IoV over licensed and unlicensed spectrum are discussed, while recommendable future research directions are investigated.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Slice-Level Performance Metric Forecasting in Intelligent Transportation Systems and the Internet of Vehicles 智能交通系统和车联网中的片级性能指标预测

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/iotm.001.2300035

Dimitrios Michael Manias, Ali Chouman, Anwer Al-Dulaimi, Abdallah Shami

{"title":"Slice-Level Performance Metric Forecasting in Intelligent Transportation Systems and the Internet of Vehicles","authors":"Dimitrios Michael Manias, Ali Chouman, Anwer Al-Dulaimi, Abdallah Shami","doi":"10.1109/iotm.001.2300035","DOIUrl":"https://doi.org/10.1109/iotm.001.2300035","url":null,"abstract":"The intricate web of vehicles connected in the fifth-generation (5G) wireless infrastructure forms the Internet of Vehicles (IoV) and enabling technologies, such as Multi-Access Edge Computing (MEC) and network slicing, are employed in guaranteeing application requirements in the IoV and optimizing network resource allocation. In particular, network slicing allows mobile network operators to support virtualized end-to-end networks with diverse slice requirements that are typically grouped into use case classes such as Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (uRLLC), and Massive Machine-Type Communication (mMTC). These enabling technologies rely on Performance Metrics, monitored and gathered within the network, in order to evaluate and suggest improvement for slice configuration. As such, this article considers a forecasting model for Performance Metrics at the network slice level by leveraging the use of the Network Data Analytics Function (NWDAF) and its edge placements. The results and analysis, including the scalability of the forecasting model, are assessed as a step towards total automation of network slice management within the 5G network. This evaluation is later illustrated using an end-to-end IoV use case incorporating the edge NWDAF placements to guide decision-making regarding management and orchestration for future networks.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Security in the Industrial Internet of Drones 无人机工业互联网中的安全问题

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/iotm.001.2200260

Alisson R. Svaigen, Azzedine Boukerche, Linnyer B. Ruiz, Antonio A. F. Loureiro

{"title":"Security in the Industrial Internet of Drones","authors":"Alisson R. Svaigen, Azzedine Boukerche, Linnyer B. Ruiz, Antonio A. F. Loureiro","doi":"10.1109/iotm.001.2200260","DOIUrl":"https://doi.org/10.1109/iotm.001.2200260","url":null,"abstract":"The Industrial Internet of Things (IIoT) has played a key role in enabling an efficient and interconnected industry through real-time communication and processing systems, thereby building on the principles of Industry 4.0. Nowadays, industrial systems are in the process of transitioning towards Industry 5.0, where humans will once again take center stage in decision-making, supported by Artificial Intelligence (AI)-based methods. In this context, drones have emerged as a feasible device for enhancing environmental sensing tasks, reducing operational costs, alleviating communication bottlenecks, and cooperating with humans through the use of Virtual Reality (VR) and Augmented Reality (AR) platforms. Therefore, Internet of Drones (IoD) network paradigm has been adopted in the industry, giving rise to the Industrial Internet of Drones (IIoD). Given these aspects, there have been changes in the privacy and security requirements for this network environment, which demands a thorough analysis of these modifications, including the challenges that arise and possible solutions to overcome them. Consequently, this study analyzes the privacy and security issues related to IIoD. Namely, we highlight the elements of IIoD which require protection, the threats and the countermeasures. We also present how these aspects differ from the general IoD environment. Lastly, we discuss the challenges regarding IIoD security and privacy, leveraging the future directions to address Industry 5.0 aspects.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Comsoc Training Comsoc培训

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/miot.2023.10255788

引用次数: 0

Blockchain and Machine Learning in Internet of Vehicles: Applications, Challenges, and Opportunities 车联网中的区块链和机器学习:应用、挑战和机遇

IEEE Internet of Things Magazine Pub Date : 2023-09-01 DOI: 10.1109/iotm.001.2300073

Mina Zamanirafe, Pegah Mansourian, Ning Zhang

{"title":"Blockchain and Machine Learning in Internet of Vehicles: Applications, Challenges, and Opportunities","authors":"Mina Zamanirafe, Pegah Mansourian, Ning Zhang","doi":"10.1109/iotm.001.2300073","DOIUrl":"https://doi.org/10.1109/iotm.001.2300073","url":null,"abstract":"The Internet of Vehicles (IoV) has emerged as a promising technology for transforming transportation systems by leveraging intelligent services and data-driven decision-making. Leveraging machine learning (ML) techniques, IoV data offers various benefits, including enhanced traffic management, improved road safety, and personalized user experiences. However, centralized ML methods face challenges in scalability and security, hampering their effectiveness in large-scale IoV deployments. This article presents a scalable and secure framework that incorporates distributed machine learning and blockchain technologies into the IoV ecosystem to overcome these limitations. The proposed framework enables the distribution of ML algorithms among participating vehicles, with each vehicle training a local model using its data. By executing a consensus algorithm, Roadside Units (RSUs) aggregate local models to provide more personalized and intelligent services in a scalable manner. Furthermore, the integration of blockchain ensures safety, transparency, and untampered features, thereby enhancing the overall security of the IoV system. This framework holds the potential to advance the efficiency, scalability, and security of IoV applications, paving the way for the widespread adoption of intelligent services in the transportation domain.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A DT Machine Learning-Based Satellite Orbit Prediction for IoT Applications 基于DT机器学习的物联网卫星轨道预测

IEEE Internet of Things Magazine Pub Date : 2023-06-01 DOI: 10.1109/IOTM.001.2200271

Xinchen Xu, Hong Wen, Huan-huan Song, Yingwei Zhao

{"title":"A DT Machine Learning-Based Satellite Orbit Prediction for IoT Applications","authors":"Xinchen Xu, Hong Wen, Huan-huan Song, Yingwei Zhao","doi":"10.1109/IOTM.001.2200271","DOIUrl":"https://doi.org/10.1109/IOTM.001.2200271","url":null,"abstract":"Satellite orbit prediction has important applications in the field of space situation awareness, such as space collision warning and observation scheduling. The expansion of space information network challenges the low delay, high-accuracy transmission and real-time response of satellite orbit prediction tasks. The traditional orbit prediction process is affected by the measurement error, the estimation error, the unmodeled orbit perturbation and other factors, resulting in low accuracy orbit prediction results. In order to meet the requirements of high accuracy requirements, we built a satellite digital twin system based on the Docker container to predict, optimize and control the satellite orbit status in low consumption. The proposed digital twin system uses the container technology to build each module, which makes the updating of the orbit prediction model more convenient. In addition, in the designed digital twin system, we present an orbit error prediction model based on machine learning. Compared with the traditional physical dynamic model, the proposed machine learning model can effectively correct the error value of orbit prediction and improve the accuracy of orbit prediction. Finally, the validity of the corresponding model is verified in the simulation environment.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124950115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LiDAR Technology for Human Activity Recognition: Outlooks and Challenges 用于人类活动识别的激光雷达技术:展望与挑战

IEEE Internet of Things Magazine Pub Date : 2023-06-01 DOI: 10.1109/IOTM.001.2200199

Omar Rinchi, Hakim Ghazzai, Ahmad Alsharoa, Y. Massoud

引用次数: 1