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IEEE Conference on Global Communications (GLOBECOM)

作者： Juan Luis Herrera Domenico Scotece Jaime Galán-Jiménez Javier Berrocal Giuseppe Di Modica Paolo Bellavista Luca Foschini Dipartamento di Informatica Scienza e Ingegneria University of Bologna Italy Dept. of Computer Systems and Telematics Engineering University of Extremadura Spain

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The Software-Defined Networking (SDN) paradigm disaggregates the data plane, embodied by switches that only forward data, from the control plane, embodied by SDN controllers that communicate with said switches. SDN also proposes a third, application layer, which implements various functions such as firewalls or service discovery by communicating with the controllers through the northbound interface. However, while state-of-the-art works propose the deployment of multiple, distributed SDN controllers, the software architecture of these controllers is still monolithic, requiring not only the controller runtime but also all the network-level applications to be deployed across all SDN controller hardware. On the other hand, state-of-the-art SDN controllers such as MSN allow treating network-level applications as microservices, which comes with the challenge of orchestrating the microservices across the network. In this paper, we present Grex, a framework to orchestrate network-level applications across microservice-based SDN controllers. We test and validate the optimization model of Grex by performing experiments in a realistic network testbed using the MSN controller.

关键词： Hands Runtime Software architecture Optimization models Microservice architectures Quality of service control systems Hardware Global communication Software defined networking

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PointNetPGAP-SLC: A 3D LiDAR-based Place Recognition Approach with Segment-level Consistency Training for Mobile Robots in Horticulture

arXiv

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arXiv 2024年

作者： Barros, T. Garrote, L. Conde, P. Coombes, M.J. Liu, C. Premebida, C. Nunes, U.J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Dept. of Aeronautical and Automotive Engineering LUCAS Lab Loughborough University United Kingdom

3D LiDAR-based place recognition remains largely underexplored in horticultural environments, which present unique challenges due to their semi-permeable nature to laser beams. This characteristic often results in highly similar LiDAR scans from adjacent rows, leading to descriptor ambiguity and, consequently, compromised retrieval performance. In this work, we address the challenges of 3D LiDAR place recognition in horticultural environments, particularly focusing on inter-row ambiguity by introducing three key contributions: (i) a novel model, PointNetPGAP, which combines the outputs of two statistically-inspired aggregators into a single descriptor;(ii) a Segment-Level Consistency (SLC) model, used exclusively during training to enhance descriptor robustness;and (iii) the HORTO-3DLM dataset, comprising LiDAR sequences from orchards and strawberry fields. Experimental evaluations conducted on the HORTO-3DLM and KITTI Odometry datasets demonstrate that PointNetPGAP outperforms state-of-the-art models, including OverlapTransformer and PointNetVLAD, particularly when the SLC model is applied. These results underscore the model’s superiority, especially in horticultural environments, by significantly improving retrieval performance in segments with higher ambiguity. The dataset and the code will be made publicly available at https://***/Cybonic/*** © 2024, CC BY.

关键词： Deep learning

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Evolutionary Computation for Latency Minimization in SDN Microservice Architectures

Evolutionary Computation for Latency Minimization in SDN Mic...

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IEEE International Conference on Communications (ICC)

作者： José Gómez-delaHiz Juan Luis Herrera Domenico Scotece Jaime Galán-Jiménez Javier Berrocal Giuseppe Di Modica Luca Foschini Dept. of Computer Systems and Telematics Engineering University of Extremadura Spain Dipartamento di Informatica Scienza e Ingegneria University of Bologna Italy

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In recent years, Software-Defined Networking (SDN) research literature has proposed the integration of multiple SDN controllers into the same network, improving the scalability and reliability of the network. However, while this evolution has focused on control plane hardware, the architecture of SDN controller software is still monolithic, and its communication with the application plane through the northbound interface is done by the integration of the network-level applications' codebase with the controller software. The proposal of SDN Mi-croservices Architectures (SDN MSAs) is aimed at transforming the application plane, from a monolithic architecture to a set of independently deployable modules named SDN microservices. However, the promising paradigm of SDN MSAs also increases the complexity of network management, as these microservices must be placed through the SDN controllers. This placement is especially complex due to its NP-hard nature. In this work, we present Genetic Algorithm for SDN MSA (GASM), an evolutionary computation-based heuristic to solve this issue in tractable times. Experimental results show that GASM represents an average speed-up of 846.33 × compared to optimal solvers.

关键词： Scalability Microservice architectures computer architecture Minimization Software Hardware Software reliability

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Asymptotic Stability Preservation of Input Delayed Nonlinear systems under Sampled-Data Feedback

Asymptotic Stability Preservation of Input Delayed Nonlinear...

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IEEE Conference on Decision and control

作者： Xin Yu Wei Lin School of Electrical Engineering and Automation Jiangsu Normal University Xuzhou China Dept. of Electrical Systems and Computer Engineering Case Western Reserve University Cleveland Ohio

We study the problem of global asymptotic stability preservation (GASP) for $C^systems$ non-smoothly stabilizable systems with input delay under sampled-data feedback. With the aid of Halanay inequality and the notion of ... 详细信息

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We study the problem of global asymptotic stability preservation (GASP) for $C^control$ non-smoothly stabilizable systems with input delay under sampled-data feedback. With the aid of Halanay inequality and the notion of homogeneity, the following sampled-data control results are established under a fast sampling: 1) GAS is preservable if the nonlinear system is homogeneous of degree zero and globally asymptotically stabilizable by homogeneous feedback; 2) As a consequence, GAS via sampled-data feedback is achieved for a class of non-smoothly stabilizable systems with input delay in a lower-triangular or upper-triangular form.

关键词： Asymptotic stability State feedback Simulation Aerospace electronics Delays Nonlinear systems

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The Effect of Balanced and Imbalanced Dataset on Voice Pathology Detection Using Online Sequential Extreme Learning Machine (OSELM)

The Effect of Balanced and Imbalanced Dataset on Voice Patho...

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Advanced Telecommunication and Networking Technologies (ATNT), IEEE International Conference on

作者： N. F. S. Md Sazihan N. M. Abdul Latiff N. N. N. Abd Malik S. Mashohor K. Alaghbari F. T. AL-Dhief Faculty of Electrical Engineering Universiti Teknolgi Malaysia UTM Johor Bahru Malaysia Dept. of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Malaysia

ISBN: (数字)9798350353501

ISBN: (纸本)9798350353518

Voice pathology detection is crucial for early diagnosis and treatment of vocal disorders. This research studies the effect of balanced and imbalanced datasets on the accuracy of voice pathology detection using Online Sequential Extreme Learning Machine (OSELM) on the Saarbruecken Voice Database (SVD). The dataset's balance has been identified as having a significant influence on the performance of the machine learning models. In this work, the voice signals from vowel /a/ of pathology and non-pathology classes are taken from SVD. The dataset is divided into two category which are balanced and imbalanced dataset. Then, the features of the voice signals are then extracted using Mel-Frequency Cepstral Coefficient (MFCC) and fed into classifier called OSELM. The result of balanced and imbalanced dataset is assessed for its accuracy. The results showed that the model achieved an accuracy of 66.25% with the balanced dataset compared to 48% for the imbalanced dataset. These findings highlight the importance of addressing dataset balance to enhance the reliability and effectiveness of voice pathology detection systems.

关键词： Pathology Accuracy Extreme learning machines Databases Machine learning Feature extraction Communications technology Telecommunication network reliability Mel frequency cepstral coefficient

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Numerical Assessment of Microwave Bone Imaging: Reconstruction of Realistic Phantoms for Diagnosing Different Bone Diseases 24

Numerical Assessment of Microwave Bone Imaging: Reconstructi...

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24th International Conference on Applied Electromagnetics and Communications, ICECOM 2023

作者： Cannata, Alessia Shahzad, Atif O'halloran, Martin Elahi, Adnan Pasian, Marco Di Meo, Simona Matrone, Giulia Amin, Bilal University of Pavia Dept. of Electrical Computer and Biomedical Engineering Pavia Italy University of Birmingham Centre for Systems Modelling and Quantitative Biomedicine Institute of Metabolism and Systems Research Birmingham United Kingdom University of Galway School of Medicine Galway Ireland University of Galway Translational Medical Device Lab Galway Ireland

ISBN: (纸本)9798350313017

Microwave imaging (MWI) can be used as an alternative modality for monitoring human bone health. So far, studies on microwave bone imaging have considered bone as a homogenous tissue;however, bone is composed of a cortical and trabecular layer having significantly different dielectric properties and microarchitecture. The trabecular bone is more susceptible to diseases like osteoporosis. Contrarily, osteoarthritis, another significant bone disease, has a more severe impact on cortical bone. Therefore, considering cortical and trabecular bone as two different bone types is of paramount importance for diagnosing different bone diseases. To this end, this study has made the first attempt to design and reconstruct the cortical and trabecular bone phantoms separately. The bone phantoms were designed as a single-layered heel-shaped structure. A Distorted Born Iterative Method (DBIM) approach in combination with the Iterative Method with Adaptive Thresholding for Compressed Sensing (IMATCS) has been employed for solving the electromagnetic inverse scattering problem. The simulation results have shown that the cortical and the trabecular bone can be distinguished based on the reconstructed dielectric properties even for low values of the signal-to-noise ratio (SNR). The findings of this study have shown that the adopted approach can be used to reconstruct the cortical and trabecular bones with reasonable accuracy and hence aid in monitoring different bone diseases based on their reconstructed dielectric properties. © 2023 IEEE.

关键词： Dielectric properties

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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Electronic engineering (ICEEM), International Conference on

作者： Mahmoud Elshabrawy Marwa M. Eid Abdelaziz A. Abdelhamid El-Sayed M. El-Kenawy Abdelhameed Ibrahim Dept. of Communications & Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Dep. of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Engineering and Control Systems Dept. Faculty of Engineering University Mansoura Egypt

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models.

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Resource Allocation in STAR-RIS-Aided SWIPT with RSMA via Meta-Learning

arXiv

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arXiv 2024年

作者： Amiri, Mojtaba Vaezpour, Elaheh Javadi, Sepideh Mili, Mohammad Robat Yanikomeroglu, Halim Bennis, Mehdi School of Electrical and Computer Engineering University of Tehran Tehran Iran Dept. of Communication ICT Research Institute Tehran Iran Tehran Iran Dept. of Systems and Computer Engineering Carleton University OttawaON Canada Centre for Wireless Communications University of Oulu Oulu Finland

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a cutting-edge concept for the sixth-generation (6G) wireless networks. In this paper, we propose a novel system that incorporates STAR-RIS with simultaneous wireless information and power transfer (SWIPT) using rate splitting multiple access (RSMA). The proposed system facilitates communication from a multi-antenna base station (BS) to single-antenna users in a downlink transmission. The BS concurrently sends energy and information signals to multiple energy harvesting receivers (EHRs) and information data receivers (IDRs) with the support of a deployed STAR-RIS. Furthermore, an optimization is introduced to strike a balance between users’ sum rate and the total harvested energy. To achieve this, an optimization problem is formulated to optimize the energy/information beamforming vectors at the BS, the phase shifts at the STAR-RIS, and the common message rate. Subsequently, we employ a meta deep deterministic policy gradient (Meta-DDPG) approach to solve the complex problem. Simulation results validate that the proposed algorithm significantly enhances both data rate and harvested energy in comparison to conventional DDPG. © 2024, CC BY.

关键词： Energy harvesting

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High-Speed Operational Amplifier with a Differentiating Circuit of Transient Correction

High-Speed Operational Amplifier with a Differentiating Circ...

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IEEE NW Russia Young Researchers in Electrical and Electronic engineering Conference (EIConRusNW)

作者： Alexey E. Titov Irina A. Alferova Dmitry V. Kuznetsov dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia dept. of Scientific Research Don State Technical University Rostov-on-Don Russia dept. of Cyber Security of Information Systems Don State Technical University Rostov-on-Don Russia dept. of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

The relevance of the present research is related to the search for promising ideas for increasing the maximum slew rate of the output voltage ($\text{SR}_{\text{M}}$) of new-generation operational amplifiers (OpAmps). Proposed circuit techniques that provide (with simultaneous use) an increase in $\text{SR}_{\text{M}}$ by more than 2 orders of magnitude. Such high-speed operational amplifiers are in demand today for application in drivers of high-speed ADCs (AD9208, AD9691, etc.), and as active elements in circuits of analog-to-discrete filters on switched capacitors. It is proposed to introduce (according to the developed rules) a nonlinear differentiating RC-circuit realized based on an additional differential stage and a differentiating capacitor of small capacitance into the classical OpAmps with one integrating correction capacitance. Such circuit "additives" practically do not change the low-signal dynamic and static parameters of the OpAmp, and at a large signal during the transient front, when the input stage enters the nonlinear mode, form a large current overcharge of the integrating correction capacitor. Consequently, the $\text{SR}_{\text{M}}$ of the OpAmp is significantly increased.

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HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks

arXiv

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arXiv 2024年

作者： Mura, Raffaele Floris, Giuseppe Scionis, Luca Piras, Giorgio Pintor, Maura Demontis, Ambra Giacinto, Giorgio Biggio, Battista Roli, Fabio University of Cagliari Dept. of Electrical and Electronic Engineering Cagliari Italy Sapienza University of Rome Department of Computer Engineering Rome Italy University of Genoa Department of Computer Science Bioengineering Robotics and Systems Engineering Genoa Italy

Gradient-based attacks are a primary tool to evaluate robustness of machine-learning models. However, many attacks tend to provide overly-optimistic evaluations as they use fixed loss functions, optimizers, step-size schedulers, and default hyperparameters. In this work, we tackle these limitations by proposing a parametric variation of the well-known fast minimum-norm attack algorithm, whose loss, optimizer, step-size scheduler, and hyperparameters can be dynamically adjusted. We re-evaluate 12 robust models, showing that our attack finds smaller adversarial perturbations without requiring any additional tuning. This also enables reporting adversarial robustness as a function of the perturbation budget, providing a more complete evaluation than that offered by fixed-budget attacks, while remaining efficient. © 2024, CC BY.

关键词： Machine learning

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