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Survey of Resources Allocation Techniques with a Quality of Service (QoS) Aware in a Fog Computing Environment

computers, Materials & Continua 2023年第7期76卷 1291-1308页

作者： Wan Norsyafizan WMuhamad Kaharudin Dimyati Muhammad Awais Javed Suzi Seroja Sarnin Divine Senanu Ametefe School of Electrical Engineering College of EngineeringUniversity Teknologi Mara40450Shah AlamSelangorMalaysia Department of Electrical Engineering Faculty of EngineeringUniversity Malaya50603KualaLumpurMalaysia Department of Electrical and Computer Engineering COMSATS University Islamabad45550Pakistan

The tremendous advancement in distributed computing and Internet of Things(IoT)applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud ***,suitable and effective applications could be performed to satisfy the applications’latency *** allocation techniques are essential aspects of fog networks which prevent unbalanced load *** resource management techniques can improve the quality of service *** to the limited and heterogeneous resources available within the fog infrastructure,the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT *** has been limited research on resource management strategies in fog networks in recent years,and a limited systematic review has been done to compile these *** article focuses on current developments in resource allocation strategies for fog-IoT networks.A systematic review of resource allocation techniques with the key objective of enhancing QoS is *** involved in conducting this systematic literature review include developing research goals,accessing studies,categorizing and critically analysing the *** resource management approaches engaged in this article are load balancing and task offloading *** the load balancing approach,a brief survey of recent work done according to their sub-categories,including stochastic,probabilistic/statistic,graph theory and hybrid techniques is provided whereas for task offloading,the survey is performed according to the destination of task *** load balancing and task-offloading approaches contribute significantly to resource management,and tremendous effort has been put into this critical ***,this survey presents an overview of these extents and a comparative ***,the study discusses ongoing research issues and potential future directio

关键词： Resource management task offloading load balancing QoS latency energy consumption

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Transistor-Level Metal Tube in Standard CMOS to Block Flying Crosstalk in BEOL Demonstrated in 38 GHz SPDT

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第6期46卷 904-907页

作者： Hao, Weiquan Li, Xunyu Pan, Zijin Miao, Runyu Yue, Zijian Wang, Albert University of California Department of Electrical and Computer Engineering RiversideCA92521 United States

Analog, mixed-signal and radio-frequency (AMX/RF) integrated circuits (IC) are sensitive to noises and interferers. Such crosstalk is particularly problematic to complex chips in advanced technologies. Global flying noises coupling through complex metal interconnects in the backend-of-the-line (BEOL) in CMOS become dominant that cannot be isolated using traditional in-substrate noise-isolation techniques. This letter reports a novel layout-only transistor-level stacked-via metal tube structure in standard CMOS BEOL to suppress global flying noises on a chip. The new technique is validated in simulation and measurement using 38GHz single-pole double-throw (SPDT) traveling wave switch circuits fabricated in a foundry 45nm silicon-on-insulator (SOI) CMOS technology, demonstrating ~7 dB global noise reduction. © 1980-2012 IEEE.

关键词： CMOS integrated circuits

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Estimating Synchronous Inertia in Power Systems Using Equal Area Criterion and Artificial Intelligence

Estimating Synchronous Inertia in Power Systems Using Equal ...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Amini, Shiva Golpîra, Hêmin Kamwa, Innocent Laval University Department of Electrical and Computer Engineering Canada University of Kurdistan Department of Electrical and Computer Engineering Iraq

ISBN: (纸本)9789531842976

In this paper, an advanced algorithm is presented that utilizes artificial neural networks (ANN) for estimating the inertia of synchronous generators (SGs). The algorithm is enhanced by integrating a modified equal area criterion method along with the kinetic energy concept to compute the maximum mechanical power (Pmax). This calculated Pmax is introduced as a novel input feature to the ANN model. Beyond the contributions already discussed, a supplementary proposal involves the development of a novel index designed to identify the most optimal fault location in power systems. The efficiency of the proposed algorithm was rigorously evaluated using simulations on the IEEE 39-bus New England test system. The simulation results demonstrated the algorithm's high accuracy, with an estimation error of less than 1% in determining the inertia of the generators. These findings underscore the algorithm's potential for enhancing the performance of power system stability analysis. © 2024 IEEE.

关键词： Power system analysis

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GraphAush: Combining Adversarial Learning and Graph Embedding for a Novel Shilling Attack Model Towards Robust Recommender Systems 11

GraphAush: Combining Adversarial Learning and Graph Embeddin...

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11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Barnett, Clayton Kashef, Rasha Toronto Metropolitan University Electrical Computer and Biomedical Engineering Toronto Canada

ISBN: (纸本)9798350367300

Recommender systems (RS) are integral to modern e-commerce and content platforms. Yet, their reliance on user-item interaction data makes them vulnerable to shilling attacks, where fake data is injected to manipulate recommendations. Traditional shilling attack strategies utilize basic statistical properties of user-item data to create deceptive profiles. Still, recent advancements have shifted towards model-based attacks leveraging machine learning to enhance effectiveness and evade detection. This paper introduces GraphAush, a novel neural shilling attack model that employs Generative Adversarial Networks (GANs) with a novel generator shilling loss tailored to manipulate the user-item interaction graph. By incorporating a novel generator shilling loss function that leverages Node2Vec embeddings, GraphAush optimizes fake profile generation to maximize the effectiveness of attacks while minimizing detectability. This method overcomes the limitations of previous models, which either require intricate knowledge of the target RS or use indirect graph-based approaches. The efficacy of GraphAush was validated through experiments with multiple benchmark datasets, revealing its strong performance against traditional heuristic and other GAN-based attack methods. This innovative approach highlights a significant advancement in adversarial techniques for RS and sets a new benchmark for evaluating shilling attack strategies. © 2024 IEEE.

关键词： Generative adversarial networks

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Guest Editorial: EV charging impacts on power system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2024年第6期18卷 1091-1094页

作者： [Anonymous] Department of Electrical Engineering and Automation Aalto University Espoo Finland School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical Engineering São Paulo State University Ilha Solteira Brazil Electrical Engineering Department Sharif University of Technology Tehran Iran School of Industrial Engineering University of Castilla-La Mancha Ciudad Real Spain

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Comparison of Two-Wheel and Four-Wheel Steering Using Event-Triggered Predictive Motion Control and Scale Vehicles

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ASME Letters in Dynamic Systems and Control 2024年第3期4卷 031002页

作者： Zhou, Zhaodong Rother, Christopher Chen, Jun Department of Electrical and Computer Engineering Oakland University RochesterMI48309 United States

This study compares the trajectory tracking performance of two- and four-wheel steering systems, especially under normal driving conditions. Specifically, the lateral motion is controlled by an event-triggered model predictive control (MPC), which activates either when consecutive control steps surpass the predictive horizon or when tracking error exceeds a predetermined lateral offset. Using a modified 1/10th scale Tamiya TT-02 RC car as a test platform, the tracking performance of both two- and four-wheel systems are evaluated. Results from the experiments highlight the better tracking performance of the four-wheel steering system over the traditional two-wheel systems and demonstrate the benefit of using event-triggered MPC for lateral motion control even under normal driving conditions, contrary to common belief that four-wheel steering systems are beneficial only in tight steering maneuvers. © 2024 by ASME.

关键词： Model predictive control

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D-band Stacked Common-Base Power Amplifier with 19.2dBm oP1dBin 55 nm SiGe BiCMOS 50

D-band Stacked Common-Base Power Amplifier with 19.2dBm oP1d...

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50th IEEE European Solid-State Electronics Research Conference, ESSERC 2024

作者： Bilato, Andrea Pirbazari, Mahmoud M. Mazzanti, Andrea University of Pavia Computer and Biomedical Engineering Dept. of Electrical Italy

ISBN: (纸本)9798350388138

This paper presents the design and experimental validation of a stacked common-base power amplifier (PA) tailored for D-band communication systems. Leveraging 55 nm SiGe BiCMOS technology, the proposed PA architecture combines the superior gain compression performance of the common-base topology with the higher voltage swing provided by stacked-transistor power amplifiers. Experimental results demonstrate a peak output power of 19.7 dBm with only a 0.5 dB lower 1-dB compression point (o P1dB) of 19.2 dBm at 135 GHz. The power added efficiency (PAE) reaches 12.1% at saturation and 11.5% at o P1dB. © 2024 IEEE.

关键词： BiCMOS technology

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A Single-Pass Noise Covariance Estimation Algorithm in Nonswitching Multiple-Model Adaptive Kalman Filters for Nonstationary Systems

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Journal of Advances in Information Fusion 2024年第1期19卷 3-19页

作者： Kim, Hee-Seung Bienkowski, Adam Zhang, Lingyi Pattipati, Krishna R. Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269 United States

This paper presents a single-pass stochastic gradient descent (SGD) algorithm for estimating unknown noise covariances. The proposed algorithm is designed for nonswitching multiple-model adaptive Kalman filters, where the noise covariances can occasionally jump up or down by an unknown magnitude. Compared to our previous batch estimation or multipass decision-directed estimation methods, the proposed algorithm has the advantage of reading measurement data exactly once, leading to a significant improvement in computational efficiency and practicality. Moreover, the algorithm achieves an acceptable level of root mean square error (RMSE) in state estimates, making it suitable for real-time industrial applications. The proposed algorithm utilizes recursive fading memory estimates of the sample cross-correlations of the innovations and employs the root mean square propagation (RMSprop) accelerated SGD algorithm. The combination of these techniques enables the algorithm to achieve high accuracy in estimating the unknown noise covariances while maintaining superior computational efficiency over iterative batch methods. The paper presents a comparative evaluation of the proposed method on several test cases, which demonstrate its effectiveness in terms of computational efficiency and estimation accuracy. Overall, the proposed algorithm offers a promising approach for real-time noise covariance estimation in multiple-model adaptive Kalman filters. © 2024 JAIF.

关键词： Adaptive filters

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Exploration, Collaboration, and Applications in Multi-Agent Reinforcement Learning

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Performance Evaluation Review 2025年第3期52卷 31-34页

作者： Chen, Jingdi Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States

In recent years, the field of humancentric decision-making has emerged as a critical area of research, driven by its potential to fundamentally reshape how decisions are made across a variety of complex systems. Human-centric decision-making is characterized by considerable variability, which can be both advantageous and problematic. Variability is beneficial in contexts like brainstorming or problem-solving, where diverse perspectives lead to innovation. However, in situations where consistency is crucial- such as public health, safety, and fairness-this variability can have negative consequences. For instance, when radiologists interpret the same mammogram differently, it can result in unnecessary medical procedures. Similarly, in military operations, inconsistent judgments by sonar technicians regarding potential threats can jeopardize both crew safety and mission success. This highlights the critical need for a deeper understanding of decisions where the stakes are high. Thus, it is important to deepen our understanding of the decision-making process in completed and dynamic scenarios that involve multiple decisionmakers. This should guide the creation of validated methods to identify, measure, model, and adjust variability in judgments to improve decision-making in multi-agent environments. © 2025 Copyright is held by the owner/author(s).

关键词： Reinforcement learning

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Optimized Temporary Frequency Support for Wind Power Plants Considering Expanded Operational Region of Wind Turbines

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 51-64页

作者： Zhengyang Hu Bingtuan Gao Zhao Xu Sufan Jiang School of Electrical Engineering Southeast UniversityNanjing210096China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong Kong SARChina Department of Electrical Engineering and Computer Science The University of TennesseeKnoxvilleTN 37996 USA

Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated operations remain insufficiently investigated,highlighting the potential for further improvement of the frequency *** paper proposes a bi-level optimized temporary frequency support(OTFS)strategy for a *** implementation of the OTFS strategy is collaboratively accomplished by individual wind turbine(WT)controllers and the central WPP ***,to exploit the frequency support capability of WTs,the stable operational region of WTs is expanded by developing a novel dynamic power control approach in WT *** approach synergizes the WTs'temporary frequency support with the secondary frequency control of synchronous generators,enabling WTs to release more kinetic energy without causing a secondary frequency ***,a model predictive control strategy is developed for the WPP *** strategy ensures that multiple WTs operating within the expanded stable region are coordinated to minimize the magnitude of the frequency drop through efficient kinetic energy ***,comprehensive case studies are conducted on a real-time simulation platform to validate the effectiveness of the proposed strategy.

关键词： Active power control model predictive control optimized temporary frequency support wind power plant wind turbine

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