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5G in Military applications: Challenges and Opportunities 4

5G in Military Applications: Challenges and Opportunities

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4th international conference on Communication Technology and Information Technology, ICCTIT 2024

作者： Wang, Zhihui Pang, Weijian Xiang, Zhining Wang, Bing Army Academy of Artillery and Air Defense Nanjing Campus Nanjing China Beijing Aeronautical Engineering Technology Research Institute Beijing China

ISBN: (纸本)9798331528973

The advent of 5G technology introduces significant advancements in communication, marked by high speed, low latency, and massive connectivity. These attributes position 5G as a promising technology for military applications, yet its design for civilian use presents challenges when adapted to the harsh conditions of the battlefield. The challenges 5G faces in military applications are examined in this paper, including differences in design objectives, antenna technologies, anti-jamming capabilities, core network dependencies, and resilience. It also explores the transformative opportunities 5G offers, such as real-time battlefield awareness, autonomous system coordination, and enhanced communication capacity. By bridging the gap between civilian and military requirements, 5G technology could revolutionize military communication systems. © 2024 ieee.

关键词： 5G mobile communication systems

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real-time Beamforming Testbed and Tracking Relay for mmWave applications

Real-time Beamforming Testbed and Tracking Relay for mmWave ...

引用

ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Lorenzo Bisulli Davide Scazzoli Francesco Linsalata Maurizio Magarini Marouan Mizmizi Christian Mazzucco Umberto Spagnolini Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy

ISBN: (数字)9798350387957

ISBN: (纸本)9798350387964

As the deployment of fifth generation (5G) mobile wireless networks continues to gain momentum, researchers are already focusing on the challenges and opportunities of the next sixth generation (6G). To meet the ever-increasing demand for higher data rates and support the development of new services, 6G is expected to exploit millimeter wave (mmWave) frequencies. However, the complex propagation characteristics at mmWave require beamforming technology, which introduces significant complexity in the communication system. Herein, we propose a real-time testbed platform to evaluate beamforming and other communication solutions designed for multiple-input multiple-output (MIMO) mmWave-based 6G networks. This platform serves as an enabler for 6G technologies evaluation under realistic propagation conditions, accelerating the development and deployment of robust and efficient 6G networks. To demonstrate the capabilities of our platform, we have implemented a smart relay with real-time beam control and tracking. The platform is able to perform an exhaustive search of 64 reception beams in less than 256 μs. Additionally, the platform can maintain the optimal beam even in mobility scenarios using a gradient-based tracking system that achieves a low overhead of less than 5%, with an update rate of 100 Hz.

关键词： 6G mobile communication Particle beams Array signal processing Wireless networks Millimeter wave technology Millimeter wave propagation real-time systems Synchronization Millimeter wave communication Relays

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Amanuensis: provenance, privacy, and permission in TEE-enabled blockchain data systems 42

Amanuensis: provenance, privacy, and permission in TEE-enabl...

引用

42nd ieee international conference on Distributed computing systems (ICDCS)

作者： Hardin, Taylor Kotz, David Dartmouth Coll Dept Comp Sci Hanover NH 03755 USA

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Blockchain technology is heralded for its ability to provide transparent and immutable audit trails for data shared among semi-trusted parties. With the addition of smart contracts, blockchains can track and verify arbitrary computations - which enables blockchain users to verify the provenance of information derived from data through the blockchain. This provenance comes at the cost of data confidentiality and user privacy, however, which is unacceptable for many sensitive applications. The need for verifiable yet confidential data sharing and computation has led some to add trusted execution environment (TEE) hardware to blockchain platforms. By moving sensitive operations (e.g., data decryption and analysis) off of the blockchain and into a TEE, they get both the confidentiality of TEEs and the transparency of blockchains without the need to completely trust any one party in the data-sharing ecosystem. In this paper, we build on our TEE-enabled blockchain datasharing system, Amanuensis, to ensure the freshness of accesscontrol lists shared between the blockchain and TEE, and to improve the privacy of users interacting within the system. We also detail how TEE-based remote attestation help us to achieve information provenance - specifically, how to achieve information provenance in the context of the Intel SGX trusted execution environment. Finally, we present an evaluation of our system, in which we test several real-world machine-learning applications (logistic regression, kNN, SVM) to determine the run-time overhead of information confidentiality and provenance. Each machine-learning program exhibited a slowdown between 1.1 and 2.8x when run inside of our confidential environment, and took an average of 59 milliseconds to verify the provenance of an input data set.

关键词： Support vector machines Data privacy Trusted computing Costs Smart contracts Prototypes Machine learning

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Semi-asynchronous Federated Learning Optimized for NON-IID Data Communication based on Tensor Decomposition 21

Semi-asynchronous Federated Learning Optimized for NON-IID D...

引用

21st ieee international Symposium on Parallel and Distributed Processing with applications, 13th ieee international conference on Big Data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Wu, Qidong Fu, Xuemei Yang, Xiangli Zhao, Ruonan Wu, Chengqian Zhang, Tinghua Hainan University School of Computer Science and Technology Haikou China Hainan University School of Information and Communication Engineering Haikou China

ISBN: (纸本)9798350329223

Federated Learning (FL) is a new distributed machine learning framework that enables reliable collaborative training without collecting users' private data, it can successfully address the issue of data silos. However, FL has had trouble scaling to statistically varied data and large-scale models because of its frequent communication and average aggregation procedures. In this paper, we propose a Semi-asynchronous Stochastic Controlled Averaging based on Tensor Decomposition for Federated Learning (SATD-SCAFFOLD), in which we perform tensor decomposition on the client model to reduce communication costs. In addition, we design a semi-asynchronous aggregation approach for the server, which can prevent server from wasting too much time waiting for data from late clients in the case of an unstable network, and the overall model still has excellent performance. Thorough experiments demonstrate that our proposed SATDSCAFFOLD algorithm can reduce both the communication cost and convergence time while maintaining good performance. © 2023 ieee.

关键词： Stochastic systems

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Enhancing Smart Agriculture Scenarios with Low-code, Pattern-oriented functionalities for Cloud/Edge collaboration 19

Enhancing Smart Agriculture Scenarios with Low-code, Pattern...

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19th Annual international conference on Distributed computing in Smart systems and the Internet of Things, DCOSS-IoT 2023

作者： Fatouros, Georgios Kousiouris, George Lohier, Theophile Makridis, Georgios Polyviou, Ariana Soldatos, John Kyriazis, Dimosthenis University of Piraeus Dept. of Digital Systems Piraeus Greece Innov-Acts Ltd Nicosia Cyprus Harokopio University Dept. of Informatics and Telematics Athens Greece CybeleTech Montrouge France University of Nicosia Dept. of Management Nicosia Cyprus

ISBN: (纸本)9798350346497

The integration of cloud computing and Internet of Things (IoT) technologies has brought significant advancements in the agriculture domain. However, the implementation of such systems often requires significant time and resources, making it challenging for smart agriculture providers to offer optimized yet affordable services for small and medium-sized farmers at scale. Low-code development platforms can be a viable solution to address these challenges, enabling non-experts to adapt or enhance existing applications with minimal coding. This paper presents a low-code approach to enhance smart agriculture scenarios with pattern-oriented functionality blocks for cloud/edge collaboration. It highlights the usage of a pattern collection for redesigning the implementation of smart agriculture applications that can enhance the data collection process as well as real-time decision-making and efficient resource management in the continuum. The effectiveness of the presented approach is demonstrated through the implementation of a case study in smart agriculture greenhouses. Evaluation results show that this approach can significantly reduce the time and effort required to deploy smart agriculture applications and provide data resilience. © 2023 ieee.

关键词： Internet of things

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Proceedings of the 21st ACM international conference on computing Frontiers 2024 Workshops and Special Sessions, CF 2024 Companion

Proceedings of the 21st ACM International Conference on Comp...

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21st ACM international conference on computing Frontiers, CF 2024

ISBN: (纸本)9798400704925

The proceedings contain 27 papers. The topics discussed include: a general-purpose analog computer to population protocol compiler;compile-time optimization of the energy consumption of numerical computations;effective HPC programming via domain specific abstractions and compilation;high-level synthesis for complex applications: the Bambu approach;relaxed threshold implementations;using a performance model to implement a superscalar CVA6;seeing beyond the order: a LEN5 to sharpen edge microprocessors with dynamic scheduling;integrating SystemC-AMS power modeling with a RISC-V ISS for virtual prototyping of battery-operated embedded devices;a gigabit, DMA-enhanced open-source ethernet controller for mixed-criticality systems;and model theft attack against a tinyML application running on an ultra-low-power open-source SoC.

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Enhancing Automated real-time Data Analysis systems with Machine Learning

Enhancing Automated Real-Time Data Analysis Systems with Mac...

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2023 ieee international conference on Paradigm Shift in Information Technologies with Innovative applications in Global Scenario, ICPSITIAGS 2023

作者： Ravivarman, G. Ravikumar, V. Futane, Pravin R. Yadav, Dhananjay Nivesh Mandal, Sanjeev Kumar Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology U.P. India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Karnataka Bangalore India

ISBN: (纸本)9798350329773

Arid Amir, bathroom Fat Hang and Shall Husain that discusses the capability of the use of machine gaining knowledge of to decorate automatic real-time facts analysis structures. The authors present an overview of system learning techniques in addition to a conceptual framework for its application in automatic actual-time facts analysis. The paper consists of a literature review of existing system getting to know algorithms applied in actual-time records analysis in addition to case research inspecting the effectiveness of these algorithms in one of kind scenarios. Moreover, the paper explores challenges and possibilities in making use of device mastering in automatic real-time data evaluation and suggests techniques for dealing with them. Finally, the paper presents a roadmap for developing exceptionally powerful computerized actual-time records analysis systems enabled via gadget learning to in addition harness the capacity of statistics-pushed innovation. © 2023 ieee.

关键词： real time systems

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Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes

Vulnerability of Automatic Identity Recognition to Audio-Vis...

引用

ieee international Joint conference on Biometrics (IJCB)

作者： Korshunov, Pavel Chen, Haolin Garner, Philip N. Marcel, Sebastien Idiap Res Inst Martigny Switzerland

ISBN: (纸本)9798350337266

The task of deepfakes detection is far from being solved by speech or vision researchers. Several publicly available databases of fake synthetic video and speech were built to aid the development of detection methods. However, existing databases typically focus on visual or voice modalities and provide no proof that their deepfakes can in fact impersonate any real person. In this paper, we present the first realistic audio-visual database of deepfakes SWAN-DF, where lips and speech are well synchronized and video have high visual and audio qualities. We took the publicly available SWAN dataset of real videos with different identities to create audio-visual deepfakes using several models from DeepFaceLab and blending techniques for face swapping and HiFiVC, DiffVC, YourTTS, and FreeVC models for voice conversion. From the publicly available speech dataset LibriTTS, we also created a separate database of only audio deepfakes LibriTTS-DF using several latest text to speech methods: YourTTS, Adaspeech, and TorToiSe. We demonstrate the vulnerability of a state of the art speaker recognition system, such as ECAPA-TDNN-based model from SpeechBrain, to the synthetic voices. Similarly, we tested face recognition system based on the MobileFaceNet architecture to several variants of our visual deepfakes. The vulnerability assessment show that by tuning the existing pretrained deepfake models to specific identities, one can successfully spoof the face and speaker recognition systems in more than 90% of the time and achieve a very realistic looking and sounding fake video of a given person.

关键词： Database systems

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Knowledge Transfer In Cross Domain Recommender systems Using Deep Latent Embeddings

Knowledge Transfer In Cross Domain Recommender Systems Using...

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2024 international conference on IT and Industrial Technologies, ICIT 2024

作者： Islam, Muhammad Bilal Habib, Usman Usman, Muhammad FAST School of Computing National University of Computer and Emerging Sciences Islamabad Pakistan Department of Computing Khanpur Institute of Technology Rahim Yar Khan Pakistan

ISBN: (纸本)9798331504465

Traditional recommender systems often face challenges such as the cold-start problem and data sparsity, especially in cross-domain scenarios. These issues limit their ability to provide accurate recommendations for new users or items with minimal interaction data, reducing their effectiveness of personalized applications. To address these challenges, a novel approach is proposed leveraging knowledge transfer in cross-domain recommender systems using Deep Latent Embeddings. The proposed method uses an autoencoder-decoder architecture to learn latent representations of users and items in a source domain and transfers to a target domain with sparse data. By mapping data from both domains into a shared latent space, the proposed approach facilitates effective knowledge sharing, enabling personalized recommendations even in data-limited domains. The proposed system is evaluated on three real-world datasets from Amazon benchmark datasets i.e. Books, Digital Music, and Movies & TV, under three cross-domain scenarios: (1) Books to Digital Music, (2) Movies to Digital Music, and (3) Books to Movies & TV. Empirical results demonstrate significant improvements in recommendation quality, mitigating cold-start and data sparsity issues. This research advances cross-domain recommender systems, providing practical solutions to enhance user satisfaction and engagement in recommendation applications. © 2024 ieee.

关键词： Domain Knowledge

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Response time Analysis for Energy-Harvesting Mixed-Criticality systems

Response Time Analysis for Energy-Harvesting Mixed-Criticali...

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25th Design, Automation and Test in Europe conference and Exhibition (DATE)

作者： Wang, Kankan Lin, Yuhan Deng, Qingxu Northeastern Univ Shenyang Liaoning Peoples R China

ISBN: (纸本)9783981926361

With the increasing demand for real-time computing applications on energy-harvesting embedded devices which are deployed wherever it is not possible or practical to recharge, the worst-case performance analysis becomes crucial. However, it is difficult to bound the worst-case response time of tasks under both timing and energy constraints due to the uncertainty of harvested energy. Based on this motivation, this paper studies response time analysis for Energy-Harvesting Mixed-Criticality (EHMC) systems. We present schedulability analysis algorithm to extend the Adaptive Mixed Criticality (AMC) approach to EHMC systems. Furthermore, we develop two response time bounds for it. To our best knowledge, this is the first work of response time analysis for EHMC systems. Finally, we examine both the effectiveness and the tightness of the bounds by experiments.

关键词： Energy-harvesting mixed-criticality AMC response time analysis real-time scheduling

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