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检索条件"任意字段=14th International Conference on COMmunication Systems and NETworkS, COMSNETS 2022"

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Heterogeneous Wireless Device Management in Edge Computing systems for IoT Services 14

Heterogeneous Wireless Device Management in Edge Computing S...

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14th international conference on Information and communication Technology Convergence, ICTC 2023

作者： Vitumbiko, Mafeni Kim, Younghan School of Electronic Engineering Seoul Korea Republic of

ISBN: (纸本)9798350313277

In a heterogeneous Internet of things (IoT) setup, it is impractical and requires human intervention to deploy workloads for every device after enrolment, especially considering the diverse range of wireless technologies involved. Furthermore, it is extremely complex to design and develop a large-scale system that can accommodate and integrate heterogeneous wireless technologies to achieve interoperability between the devices. As the number of devices increases, it is necessary to dynamically adjust workloads to accommodate the growing demand and maintain quality of service. In this paper we employ a state-of-art solution called Project-Flotta, which is utilized for managing edge devices and edge workloads. However, Project-Flotta does not provide a way of automating and managing heterogeneous wireless technologies for an IoT service. therefore, we propose a system based on Project-Flotta leveraging its kubernetes custom resources by extending its functionality to adapt diverse wireless technologies. © 2023 IEEE.

关键词： automation edge compuning heterogenous horizontal pod auto scaling kubernetes Project-Flotta wireless sensor

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SENN: Self-evolving Neural Network to Recognize Motor Imagery thought Patterns 14th

SENN: Self-evolving Neural Network to Recognize Motor Imager...

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14th international Joint conference on Computational Intelligence, IJCCI 2022

作者： Chug, Stuti Agarwal, Vandana Department of Computer Science and Information Systems BITS Pilani Pilani Campus India

ISBN: (纸本)9789897586118

the EEG-based motor imagery task classification has been a challenge for researchers due to the complex nature of EEG data. Human thoughts are a complex combination of different body limb activations and it is difficult to capture only one thought at a time. the data belonging to different motor imagery thought classes are also not separable linearly. In this paper, a novel technique for efficient and improved motor imagery task classification is proposed. Two major issues in motor imagery task classification of EEG data are addressed - channel selection and radial basis function neural network centers. the channel selection is posed as a combinatorial problem and an evolutionary nature-inspired algorithm PSOCS is proposed to select the most informative and discriminative channels using the Particle Swarm Optimization algorithm. the features are extracted using the selected channels and are subjected to classification. In this paper, a selfevolving radial basis functions neural network (SENN) is proposed based on sub-clusters within each motor imagery task class. the number, centers, and spread of hidden neurons are obtained by the k-means clustering algorithm. the proposed algorithm is validated using the benchmarked datasets BCI Competition IV 2a and BCI Competition IV 2b data set. the proposed technique outperforms some of the existing techniques and classifies the motor imagery tasks efficiently. Copyright © 2022 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Particle swarm optimization (PSO)

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Power Allocation for Non-Coherent Multi-Carrier FSK Underwater Acoustic communication systems with Uneven Transmission Source Level 14

Power Allocation for Non-Coherent Multi-Carrier FSK Underwat...

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14th international conference on Signal Processing systems, ICSPS 2022

作者： Zhao, Yunfei Wan, Lei Chen, Yougan Cheng, En Xu, Feng Liang, Lei Xiamen University Dept. of Information and Communication Engineering Xiamen China Xiamen University Dept. of Applied Marine Physics and Engineering Xiamen China Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9798350336313

Non-coherent multi-carrier Frequency Shift Keying (FSK) is widely used in underwater acoustic communication systems due to its high reliability, low receiving complexity, and less susceptibility to channel conditions. In practical underwater acoustic communication systems, due to the wide band nature of the signal, the overall transmitting source level is usually not flat. Targeting at this issue, this paper proposes power allocation methods based on genetic algorithm and adaptive greedy algorithm, which maximize channel capacity and system robustness. Results based on simulated and pool experimental channels show that our methods can achieve higher channel capacity and lower bit error rate than power averaging scheme, therefore better system performance can be obtained. © 2022 IEEE.

关键词： Underwater acoustic communication

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Optimizing Cloud Energy Consumption Using Static Task Scheduling Algorithms: A Comparative Study

Optimizing Cloud Energy Consumption Using Static Task Schedu...

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international conference on Information and communication systems (ICICS)

作者： Abdelhamid Khiat Networks and Distributed Systems Division Research Center on Scientific and Technical Information Algiers Algeria

Cloud data centers, comprising a diverse set of heterogeneous resources working collaboratively to achieve high-performance computing, face the challenge of resource dynamism, where performance fluctuates over time. this dynamism poses complexities in task scheduling, warranting further research on the resilience of existing static task scheduling algorithms when deployed in dynamic cloud environments. this study adapts three well-known task scheduling algorithms to the cloud computing context and conducts a comprehensive comparison to assess their resilience to dynamic conditions. the evaluation, employing simulation techniques, analyzes total energy consumption and total response time as key metrics. the results offer detailed insights into the effectiveness of the adapted algorithms, providing valuable guidance for optimizing task scheduling in dynamic cloud data centers.

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Design of 5G Non-Terrestrial Network Handover using Transparent Satellite

Design of 5G Non-Terrestrial Network Handover using Transpar...

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international conference on Information and communication Technology Convergence (ICTC)

作者： Kyung-Rak Lee Hee-Wook Kim Joon-Gyu Ryu Jin-Young Kang Satellite Communication Infra Research Section Electronics and Telecommunications Research Institute Daejeon Republic of Korea Semicolon Inc. Seoul Republic of Korea

Deploying actual satellites into space and conducting verification entail significant costs, time, and various challenges. In this paper, we aim to address these problems by developing a platform that simulates networks using terrestrial networks and satellite systems. the focus is particularly on simulating Terrestrial Network (TN) to Non Terrestrial Network (NTN) handover technology. this approach is devised to overcome the constraints of physically deploying and testing satellites, avoiding the high costs and time associated with space deployment. It aims to create a simulation environment for evaluating network behavior and performance without the need for costly and time-consuming space deployment.

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Effects of Supply Chain Volatility on Smart Greenhouses: Balancing Cost & System Availability 14

Effects of Supply Chain Volatility on Smart Greenhouses: Bal...

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14th international conference on Electronics, Computers and Artificial Intelligence, ECAI 2022

作者： Elnadi, Yasmine Refaat, Tarek K. Daoud, Ramez M. Amer, Hassanein H. Ali, Nora A. The American University in Cairo Electronics & Communications Engineering Department Cairo Egypt Mass Scale Infrastructure Group Cisco Systems Inc. OttawaON Canada

ISBN: (数字)9781665495356

ISBN: (纸本)9781665495356

this paper studies a 200m×40m greenhouse divided into five 40m×40m cells. To reduce cost, it is important to find the minimum number of Access Points (APs) required for correct operation. A 2% maximum Packet Loss Rate (PLR) is used as a criterion for successful communication between sensors, controller, and actuators. Riverbed simulations are conducted, to indicate that the specific greenhouse under study can safely survive three AP failures provided the remaining two APs are in (or relocated to) specific positions, for optimal coverage. Furthermore, with only one AP in the middle of the greenhouse, the system's performance is marginally acceptable. Another important contribution, of this research, is the proposal of a technique to help system designers manage the suitable balance between system cost (from the point of view of APs) and cost of downtime. System steady state availability is used to measure downtime. Finally, a use case is presented, demonstrating the point of diminishing returns, where investing in more APs was not justified from a cost point of view, with an insignificant impact on steady state availability. © 2022 IEEE.

关键词： Greenhouses

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Divide and Conquer: A Low-complexity Neural Network for Monophonic Speech Enhancement

Divide and Conquer: A Low-complexity Neural Network for Mono...

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14th Annual Summit and conference of the Asia-Pacific-Signal-and-Information-Processing-Association (APSIPA ASC)

作者： Fang, Bingxiao Liu, Liang Bigo Technol Pte Ltd Singapore Singapore

ISBN: (数字)9786165904773

ISBN: (纸本)9786165904773

Noise suppression is an essential speech enhancement method to reduce the background noise in communication systems. Although stationary-noise can be successfully suppressed with the conventional signal processing algorithm, the non-stationary noise, especially the instantaneous-noise, remains challenging. Impressive performance has been achieved after neural network introduced in noise suppression task in the past decade. However, good performance and low complexity is still alternative. In this study, we demonstrate a low-complexity neural network for monophonic speech enhancement, in which a divide and conquer strategy has been employed in the design of the neural network to separate the noise suppression task into an envelope enhancement module and a detail enhancement module, denoted as EDNet. this approach achieves significant quality improvements in terms of the perceptual evaluation of speech quality (PESQ), short-time objective intelligibility (STOI), and the Scale-Invariant Signal to Distortion Ratio (SI-SDR) with low computational complexity.

关键词： communication systems Neural networks Noise reduction Signal processing algorithms Information processing Speech enhancement Distortion

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UAV Based Optimized Virtual Cooperative Sensing Using Particle Swarm Optimization 14

UAV Based Optimized Virtual Cooperative Sensing Using Partic...

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14th international conference on Information and communication Technology Convergence, ICTC 2023

作者： Gul, Noor Kim, Su Min Ali, Jehad Kim, Junsu University of Peshawar Department of Electronics Peshawar Pakistan Tech University of Korea Department of Electronics Engineering Siheung Korea Republic of Ajou University Department of Ai Convergence Network Suwon Korea Republic of

ISBN: (纸本)9798350313277

Spectrum sensing utilizing unmanned aerial vehicles (UAVs) has become increasingly popular due to their advantageous line of sight (LoS) communication links. In traditional cognitive radio networks (CRNs), secondary users (SUs) opportunistically access the primary user (PU) channel through cooperative spectrum sensing, aiming to ensure reliable sensing while minimizing disturbances for licensed users. In this study, we evaluate an overlay mode of the CRN where a UAV acts as the SU. Instead of employing multiple SUs as in a terrestrial cooperative spectrum sensing setup with a fusion center (FC), our approach involves a single UAV performing virtual cooperative sensing by following a circular flight trajectory. During the UAV's sensing period, it consists of virtual mini-sensing slots akin to a group of SUs. the UAV enhances sensing reliability by performing local spectrum sensing within each mini-slot and combines the collected data using the voting scheme to make collective decisions. Moreover, the mini-slot sensing radian is optimized using particle swarm optimization (PSO) to readjust the sensing time. the optimized sensing time has resulted in increased throughput and reduce sensing time for the virtual cooperative sensing environments. © 2023 IEEE.

关键词： line of sight communication particle swarm optimization throughput Unmanned aerial vehicles virtual cooperative sensing

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Design of a cheap pulse Oximeter for home care systems 14

Design of a cheap pulse Oximeter for home care systems

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14th international conference ELEKTRO, ELEKTRO 2022

作者： Skrvan, Adam Hudec, Robert Matuska, Slavomir University of Zilina Department of Multimedia and Information-Communication Technologies Zilina Slovakia

ISBN: (纸本)9781665467261

In the current pandemic time, one of the important parameters for assessing the health status of a patient with COVID 19 is level of blood oxygenation. the aim of our work is devoted to the development and construction of a pulse Oximeter based on MAX ICs. the initial pulse oxymetry studies were concerned with issues such as device size and power efficiency. Reduced power consumption and size are the major causes of our progress. We picked low-power electronic components to reduce power consumption. We used a diode field with two green, one red, one infrared, and two photodiodes as a light source and detector. A high-speed four-channel AD converter converts the signal from analog to digital. the signal is smoothed using an average filter in the algorithm. We found peaks that can be utilized to determine heart rate after smoothing the signal. the blood Oximeter level is calculated by processing the amplitude of red and infrared signals collected by a photodetector. Test algorithms were performed on the Arduino platform. the output of the device are values of blood oxygenation and heart rate. © 2022 IEEE.

关键词： Oximeters

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A Deep Learning-Based Spectral Efficiency Maximization in Multiple Users Multiple STAR-RISs Massive MIMO-NOMA networks 14

A Deep Learning-Based Spectral Efficiency Maximization in Mu...

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14th international conference on Ubiquitous and Future networks, ICUFN 2023

作者： Perdana, Ridho Hendra Yoga Nguyen, Toan-Van An, Beongku Hongik University Dept. of Software and Communications Engineering Graduate School Korea Republic of International University Vietnam National University School of Computer Science and Engineering HCM City Viet Nam Hongik University Dept. of Software and Communications Engineering Korea Republic of

ISBN: (纸本)9798350335385

In this paper, we investigate a deep learning-based spectral efficiency maximization in multiple users multiple simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) networks, where multiple STAR-RISs are deployed to assist a base station (BS) in communicating with multiple near and far users simultaneously. To improve spectral efficiency (SE), we formulate a joint optimization of the precoding matrix, the phase shift of reflection and transmission of the STAR-RIS problem subject to the individual quality of services (QoS) of each user, maximum power budget at BS and the discrete phase shift. the formulated problem belongs to the class of mixed-integer non-convex optimization problem, which is difficult to solve optimally. We first relax the formulated problem and then transform it into an equivalent non-convex one but with a more tractable form. We then apply the inner approximation method to approximate the non-convex parts iteratively. Towards real-time optimization, we propose a novel deep learning framework with a convolutional neural network (CNN) model to predict the downlink SE based on users' position information and channel gains. Numerical results show that the proposed approach improves the SE compared to the massive MIMO systems with conventional RIS. Besides, the DL framework for the proposed scheme predicts the optimal SE within a short time compared to the conventional approach. © 2023 IEEE.

关键词： Spectrum efficiency

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