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Developing cloud computing time slot-availability predictions using an artificial neural network

IEIE Transactions on Smart Processing and Computing 2020年第1期9卷 49-57页

作者： Rayan, Alanazi Khan, Muhammad Ashfaq Alhazemi, Fawaz Alshammari, Hamoud Nah, Yunmook Department of Computer Science Engineering Jouf University Al-Qurayyat Saudi Arabia Department of Computer Engineering Dongguk University Seoul-30-pildong-ro-1-gil-jung-gu Korea Republic of Department of Computer and Network Engineering College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Jouf University Al-Qurayyat Saudi Arabia Department of Applied Computer Engineering Dankook University Yongin-si Gyeonggi-do Korea Republic of

Abstract: Over the last decade, cloud computing has exponentially transformed the ways of computing. In spite of its various advantages, cloud computing suffers from several challenges that affect performance. Two of the fundamental challenges are power consumption and dynamic resource scaling. An efficient resource allocation strategy could help cloud computing to improve overall performance and operational costs. In this paper, we design a novel approach to available time slot prediction in a data node, based on an artificial neural network (ANN), which predicts the time at which the required resources will be available. We conducted experiments on several nodes, obtaining up to 98%, and outperforming state-of-the-art available time slot prediction approaches. We claim that available time slot prediction for cloud computing based on an ANN will lead to optimum resource allocation and to minimizing energy consumed while maintaining the essential performance level. © 2020 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Neural networks

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Predictive Analytics for Ear Health Management Using IoT and Ensemble Learning

Predictive Analytics for Ear Health Management Using IoT and...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Saravanan, S.K. Parvathy, Palaniraj Rajidurai Meenakshi, R. Prabu, K. Ganeshbabu, T.R. Meenakshi, B. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Big Data and Network Security Tamil Nadu Chennai India Mphasis Corporation ChandlerAZ United States Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Gojan School of Business and Technology Department of Electronics and Communication Engineering Redhills Tamil Nadu Chennai India Department of Electronics and Communication Tamil Nadu Namakkal India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331527495

Proactive health monitoring solutions are becoming more important due to a growing population of older people. To better manage the ear health of the elderly, this research investigates ensemble learning methods within the domain of predictive analytics using the Internet of Things (IoT). It provides an ensemble learning approach that uses IoT capabilities to predict potential ear health problems in this population. It evaluates the efficacy of many ensembles learning approaches, including bagging, boosting, and stacking, using real-world sensor data acquired from IoT devices. Our results show that ensemble learning methods considerably improve prediction accuracy compared to standalone models. Ensemble learning overcomes the limitations of individual algorithms and maximizes their combined prediction potential by efficiently combining varied models. Our findings have important implications for the management of healthcare for the elderly, providing new opportunities to enhance early diagnosis and intervention techniques for ear health concerns via the use of predictive analytics provided by the IoT. It highlights the potential of ensemble learning approaches to improve predictive analytics in the senior healthcare sector, especially with IoT-driven solutions. © 2025 IEEE.

关键词： mHealth

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Design and Simulation of a 3-Transistor Active Pixel Sensor Using MATLAB Simulink

Design and Simulation of a 3-Transistor Active Pixel Sensor ...

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Information Technology (ACIT)

作者： Anas Al Tarabsheh Huda Alheeh Department of Electrical Biomedical and Computer Engineering Abu Dhabi University Abu Dhabi UAE Electrical Engineering Department Faculty of Engineering The Hashemite University Jordan Department of Network and Communication Engineering Al Ain University Abu Dhabi UAE

ISBN: (数字)9798350320244

ISBN: (纸本)9798350320251

This paper proposes a Simulink model to simulate the pixel circuit with variable light intensities to investigate the impact of the light intensity on the CMOS image sensor pixels. This article also explores the CMOS image sensor pixel categories and presents the design and the simulation of the 3- Transistor (3T) Active Pixel Sensor (APS) in the MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single-pixel sensing circuit which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for pixel operation; reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including the dark case, is simulated, and it is shown its inverse proportionality with the light intensity. As a result, the Cpd discharges faster if the amount of light is increased. The more the light intensity, the lower value for the output voltage.

关键词： Semiconductor device modeling Software packages Active pixel sensors Voltage CMOS image sensors Discharges (electric) Photodiodes

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Triple-Fault-Tolerant Binary MDS Array Codes with Lower Encoding Complexity

Triple-Fault-Tolerant Binary MDS Array Codes with Lower Enco...

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International Symposium on Problems of Redundancy in Information and Control Systems (RED)

作者： Hanxu Hou Linqi Song Dongguan Key Lab of Artificial Information Network School of Electrical Engineering & Intelligentization Dongguan University of Technology Department of Computer Science City University of Hong Kong

In this paper, we present a new construction of maximal distance separable (MDS) array codes with three parity columns. We present an efficient encoding algorithm for our new codes and show that our new codes have lower encoding complexity than all the existing MDS codes under the same parameters. The essential reasons of obtaining lower encoding complexity for our codes are of two-folds: (i) our codes are well-designed in a cyclic polynomial ring with only cyclic shifts and XORs being involved in the operations; (ii) our codes are designed based on the efficient schedule algorithm that can minimize the number of operations in the coding procedure. Moreover, our codes can support much more parameters compared with the existing MDS array codes, such as the EVENODD codes and STAR codes. We also present an efficient decoding method for the proposed codes.

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Scale-Based Slicer Placement in Elastic Optical networks

Scale-Based Slicer Placement in Elastic Optical Networks

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OptoElectronics and Communications Conference, OECC

作者： Nattapong Kitsuwan Praphan Pavarangkoon Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan School of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

This paper proposes a scale-based slicer placement scheme to reduce bandwidth blocking rate (BBR) in elastic optical networks (EONs). In EONs, a slicing-stitching technology is adopted to overcome a spectrum slot allocation rule that the spectrum slots of the same request must be consecutive on the same link. This technology is done by slicers to split a spectrum band into multiple sub-spectrum components. In EONs with limited slicers, determining equally the number of slicers on every node may not result in a low BBR since the traffic volume on each node is not the same. We investigate and determine the number of slicers needed for each node as a scale-based policy. The simulation results show that our scheme achieves a BBR reduction of 91%, compared to the conventional scheme.

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

arXiv

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arXiv 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan The Beijing Key Laboratory of Network System Architecture and Convergence The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing China Singapore The Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Department of Industrial and Systems Engineering University of Miami Coral GablesFL33146 United States The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Department of Computer Science North Carolina State University RaleighNC27695 United States The Beijing Key Laboratory of Network System Architecture and Convergence China The Beijing Advanced Information Network Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025, CC BY-NC-SA.

关键词： Markov processes

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On the MDS Condition of Generalized Expanded-Blaum-Roth Codes

On the MDS Condition of Generalized Expanded-Blaum-Roth Code...

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International Symposium on Problems of Redundancy in Information and Control Systems (RED)

Generalized Expanded-Blaum-Roth (GEBR) codes [You et al. 2020] are designed for large-scale distributed storage systems that have larger recoverability for single-symbol failures, multi-column failures and multi-row failures, compared with locally recoverable codes (LRC). GEBR codes encode an α × k information array into a pτ ×(k + r) array such that lines of slope i with 0 ≤ i ≤ r −1 have even parity and each column contains pτ−α local parity symbols, where p is an odd prime and k +r ≤ pτ. Necessary and sufficient conditions for GEBR codes to be (n, k) recoverable (i.e., any k out of n = k+r columns can retrieve all information symbols) are given in [Hou et al. 2023] for α = (p −1)τ. However, the (n, k) recoverable condition of GEBR codes is unknown when α < (p − 1)τ. Note that the (n, k) recoverable condition is reduced to be MDS condition if there is no local parity symbol in each column. In this paper, we present the (n, k) recoverable condition for GEBR codes for α < (p − 1)τ. Moreover, we characterize the necessary and sufficient (n, k) recoverable condition for GEBR codes when p is a special prime.

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Introduction of the Up-to-Date Current Development Activities and the Power Beam Control Experiment Project from the LEO for the Realization of the Operational SSPS 74

Introduction of the Up-to-Date Current Development Activitie...

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74th International Astronautical Congress, IAC 2023

作者： Ijichi, Koichi Yanagawa, Hiroki Kitabatake, Hidetoshi Inada, Hitomi Kashimura, Osamu Tanaka, Koji Ishikawa, Ryo Honjo, Kazuhiko Ishimura, Kosei Japan Space Systems 3-5-8 Shibakoen Minato-ku Tokyo105-0011 Japan Japan Aerospace Exploration Agency Institute of Space and Astronautical Science 3-1-1 Yoshinodai Chuo-ku Kanagawa Sagamihara252-5210 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Waseda University Dept. of Modern Mechanical Engineering School of Creative Science and Engineering 30401 Okubo Shinjuku-ku Tokyo169-8555 Japan

The outline of the project and the up-to-date status and the progress of the power transmission system towards the realization of the Space Solar Power System (SSPS) will be presented including newly started power transmission demonstration project from the LEO satellite to the ground based on the established technologies by the development projects preceded. Japan Space Systems and organized team have been engaged in the SSPS project for more than 30 years and the current power transmission system development project for SSPS was started under METI in the year 2019. The project consisted of three major tasks. The first is to develop system and to establish necessary technologies for so called power generation and transmission panel (PGTP) whose size is about 50 cm square and 10 cm thick, and the target weight should be less than 9 kg. This panel is going to be a unit to consist of the practical power generation and transmission system from the space for the operational SSPS in the GEO as the goal. The second is to improve the total efficiency from DC input to output RF power to exceed 60%. The third is to demonstrate long-range wireless power transmission from flying vehicle to the ground. And then, the power transmission demonstration experiment project from the LEO to the ground with 150kg class satellite started at the end of the year 2022, and is going to be introduced in this paper. This project consisted of the power beaming and configuring technologies from the on the orbit phase array transmission system integrated on the LEO satellite to the ground distributed beam configuration measuring system, and also to demonstrate power transmission based on the preceding development results. Copyright © 2023 by the International Astronautical Federation (IAF). All rights reserved.

关键词： LEO satellite Microwave Moon power SSPS WPT

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A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing

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computers, Materials & Continua 2021年第4期67卷 241-252页

作者： Wenbin Yu Hao Feng Yinsong Xu Na Yin Yadang Chen Zhi-Xin Yang Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Jiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering Michigan State UniversityEast Lansing48824MIUSA State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering University of Macao999078Macao

Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor *** computing,theoretically known as an absolutely secure way to store and transmit information as well as a speed-up way to accelerate local or distributed classical algorithms that are hard to solve with polynomial complexity in computation or *** this paper,we focus on the phase estimation method that is crucial to the realization of a general multi-party computing model,which is able to be accelerated by quantum algorithms.A novel multi-party phase estimation algorithm and the related quantum circuit are proposed by using a distributed Oracle operator with *** proved theoretical communication complexity of this algorithm shows it can give the phase estimation before applying multi-party computing efficiently without increasing any additional ***,a practical problem of multi-party dating investigated shows it can make a successful estimation of the number of solution in advance with zero communication complexity by utilizing its special statistic *** simulations present the correctness,validity and efficiency of the proposed estimation method.

关键词： Edge computing security multi-party computing quantum algorithm phase estimation communication complexity

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Remote Sensing Target Recognition Model Based on Small Sample Image Generation

Remote Sensing Target Recognition Model Based on Small Sampl...

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computer engineering and Intelligent Communications (ISCEIC), International Symposium on

作者： Lei Chen Liting Sun School of Space Information Space engineering University Beijing China General Department of Network and Information Security Beijing Institute of Computer Technology and Application Beijing China

In recent years, remote sensing object recognition methods based on deep learning have received extensive attention. Deep learning methods need to use a large number of labeled data to carry out network training. However, the cost of labeling remote sensing image data is very high. Therefore, how to use a small number of labeled target images to train the remote sensing target classifier with high performance is an urgent problem to be solved. In view of the above problems, this paper has carried out the following work. Firstly, based on WGAN-GP, this paper optimizes the constraint conditions of neural network and proposes a depth generation model, namely CCWGAN-GP, for remote sensing image generation. Secondly, this paper proposes a remote sensing target classification model SCLNet, which makes full use of the original one-hot label and the generated soft classification label to train the neural network. Experimental results show that the proposed model can generate highly similar images to real images, and can significantly improve the performance of the classifier under training conditions with only a few labels.

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