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Comparative Analysis of Microservices and Monolithic Architecture

Comparative Analysis of Microservices and Monolithic Archite...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Victor Benavente Luiggi Yantas Isabel Moscol Ciro Rodriguez Ricardo Inquilla Yuri Pomachagua Software Engineering Department Universidad Nacional Mayor de San Marcos UNMSM Lima Peru Mechanical and Electrical Engineering Department Universidad de Piura UDEP Piura Peru Systems Engineering Department Universidad Nacional de Cañete Lima Peru Systems Engineering Department Universidad Nacional Federico Villarreal UNFV Lima Peru

ISBN: (纸本)9781665487726

A comparative study of microservices and monolithic architectures, the main characteristics of each architecture will be defined, such as important functionalities, error resolution capacity, response time, and the number of requests supported. the comparison finds out which architecture is more suitable and the reason to apply some of the main technological tools such as JMeter, Amazon, Java, Python, Play, Jax-RX, Spring Boot, and Angular, among others. the methodology to obtain the results consists of three cases where the response time, number of requests, and costs per million are analyzed by a certain technology for a microservice and monolithic architecture. Results obtained such as response time, the number of requests supported, and costs per million requests allow to select the proper architecture. When dealing with large and highly complex systems the microservices architecture can be advantageous since it simplifies the codebase, even the time demand in implementing the microservices system offsets the drawbacks associated with the monolithic architecture.

关键词： Resistance Java Costs Microservice architectures Computer architecture Containers Time factors

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Enhanced Lifetime with less energy consumption in WSN Using a Genetic Algorithm-based approach

Enhanced Lifetime with less energy consumption in WSN Using ...

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international conference on Computing and Networking Technology (ICCNT)

作者： Komuraiah Bejjam Navya Bollena Jhanvitha B Electronics & Communication Dept. Kitsw(Kakatiya University) Warangal Telangana

Enhanced lifetime means to increase or im- prove the value, quantity, desirability, or attractiveness. Energy efficiency simply refers to using less energy to complete the same task, thereby reducing energy waste. Energy efficiency protocols are used in wireless sensor networks to improve system energy conservation and lifespan. In a WSN, instead of using physical media for communication, transmission is accomplished through the deployment of nodes. the deployed nodes send data to the destination node or to the sink node. the process of gathering the nodes for improved communication is referred to as clustering. During clustering, neighboring nodes that are part of a compatible cluster send data to the cluster head, aggregating it and sending it to the sink. For the enhancement of WSN, many clustering algorithms have been created. In the case of the traditional approach, the node prefers a straight-line path hence it consumes more energy a reduction the lifetime. Hence, another genetic algorithm-based approach is VGDRA. Since the proposed method is dynamic rather than static, it has a higher energy efficiency than LEACH, because it takes the shortest path. Balanced load and optimization increase the likelihood of better results in lower loops, which other techniques cannot achieve. the proposed method's simulation results are generated using MATLAB R2022 b.

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Neural Network for Solving Ordinary Differential Equations

Neural Network for Solving Ordinary Differential Equations

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international conference on Computational Intelligence and communication networks (CICN)

作者： Wengyao Jiang Chen Xuan Department of applied mathematics Xi'an Jiaotong-liverpool University Suzhou China

ISBN: (纸本)9781665487726

Deep learning and machine learning are immensely prevalent and highly interactive in a myriad of fields, typically neural networks is widely used in mathematics. We outline a technique for employing artificial neural networks (ANN) to solve ordinary differential equations. For better illustration, we present the basic logic and formula of ANN and gradient computation, following with one typical first order differential equation as example. In order to research the flexibility and feasibility of our model, we compare several hyperparameters and different optimizer using control variable method. Finally, our neural networks model is applied into the second order differential equations with innovative modification by analogy. In this article, we illustrate the relatively novel method to solve the ordinary differential equations and examine our model through adjustable parameters, then convert into the second order which shows a wide application range.

关键词： Deep learning Computational modeling Artificial neural networks Ordinary differential equations Mathematical models Stability analysis communication networks

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Noise Audits Improve Moral Foundation Classification 14

Noise Audits Improve Moral Foundation Classification

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14th IEEE/ACM international conference on Advances in Social networks Analysis and Mining, ASONAM 2022

作者： Mokhberian, Negar Hopp, Frederic R. Harandizadeh, Bahareh Morstatter, Fred Lerman, Kristina Information Sciences Institute University of Southern California United States Amsterdam School of Communication Research University of Amsterdam Netherlands

ISBN: (纸本)9781665456616

Morality plays an important role in culture, identity, and emotion. Recent advances in natural language processing have shown that it is possible to classify moral values expressed in text at scale. Morality classification relies on human annotators to label the moral expressions in text, which provides training data to achieve state-of-the-art performance. However, these annotations are inherently subjective and some of the instances are hard to classify, resulting in noisy annotations due to error or lack of agreement. the presence of noise in training data harms the classifier's ability to accurately recognize moral foundations from text. We propose two metrics to audit the noise of annotations. the first metric is entropy of instance labels, which is a proxy measure of annotator disagreement about how the instance should be labeled. the second metric is the silhouette coefficient of a label assigned by an annotator to an instance. this metric leverages the idea that instances with the same label should have similar latent representations, and deviations from collective judgments are indicative of errors. Our experiments on three widely used moral foundations datasets show that removing noisy annotations based on the proposed metrics improves classification performance.11Our code can be found at: https://***/negar-mokhberian/noise-audits. © 2022 IEEE.

关键词： Classification (of information)

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Performance Evaluation of Various RISC Processor systems: A Case Study on ARM, MIPS and RISC-V 1

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14th international conference on Cloud Computing (CLOUD) Held as Part of the Services conference Federation (SCF)

作者： Liu, Yu Ye, Kejiang Xu, Cheng-Zhong Chinese Acad Sci Shenzhen Inst Adv Technol Guangdong Hong Kong Macao Joint Lab Human Machine Shenzhen 518055 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Macau Fac Sci & Technol State Key Lab IoTSC Macau Peoples R China

ISBN: (数字)9783030963262

ISBN: (纸本)9783030963262;9783030963255

RISC-V is a new instruction set architecture (ISA) that has emerged in recent years. Compared with previous computer instruction architectures, RISC-V has outstanding features such as simple instructions, modular instruction set and supporting agile development. Due to these advantages, a large number of chips have been designed based on RISC-V ISA. However, compared with other ISAs, the efficiency or performance of RISC-V architecture is still not clear. In this paper, we investigate the performance difference of three mainstream RISC processor systems (i.e., ARM, MIPS and RISC-V). We use two open source benchmark tools-UnixBench and LMbench, to widely evaluate the processor performance, such as computing efficiency, read and write file delay, local communication bandwidth, etc. A total of 19 detailed performance tests on these three ISA systems are carried out. the testing results show: i) MIPS achieves the highest scores and shortest context switching delay whether it has a large number of file copying or pipeline communication;ii) RISC-V has high local communication bandwidth and strong scientific computing capabilities, but has highest communication and file access delays;iii) ARM's local communication bandwidth is low, and the delay in all aspects is slightly higher than that of MIPS.

关键词： ISA RISC-V ARM MIPS

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Deep Learning for Aerial and Satellite Image Analysis: a CNN-Based Approach

Deep Learning for Aerial and Satellite Image Analysis: a CNN...

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international conference on communication systems and Network Technologies (CSNT)

作者： Sailesh Adda Hemanth Valeti Murali Krishna Enduri Gangireddy Salla Anupoju Tejaswi Department of CSE SRM University-AP India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Applications like disaster management, urban planning, and environmental monitoring rely on satellite image categorization. this project develops a machine learning pipeline using MobileNetV2, a CNN architecture, to classify high-resolution satellite images. It employs two convolutional layers (3x3 kernels) with ReLU activation, 2x2 max-pooling, a fully connected layer, and a SoftMax output for multi-class classification. Images are resized to 200x200 pixels (RGB) to balance detail and efficiency. MobileNetV2 was chosen for its low latency and high performance, using depth-wise separable convolutions and inverted residuals. the model, optimized with Adam and categorical crossentropy, achieved 98% validation accuracy and F1-scores above 0.96 across all classes, converging in 8 epochs. the architecture balances simplicity and performance for robust feature learning and generalization. this approach highlights CNNs' ability to classify satellite images effectively. Future work could explore transformer-based models or integrate temporal satellite data to enhance analysis. this work offers a scalable, automated solution for satellite image classification.

关键词： Representation learning Satellites Image recognition Urban planning Pipelines Transformers Satellite images Convolutional neural networks Low latency communication Kernel

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Application of LTE-U Technology in Train-Ground communication of Urban Rail Transit 14

Application of LTE-U Technology in Train-Ground Communicatio...

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14th international conference on Intelligent Computation Technology and Automation, ICICTA 2021

作者： Song, C.Z. Liu, X.J. Liu, W.Z. School of Electronics and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China

With the development of intelligentizing of Urban Rail Transit (URT), the data that need to be transmitted between train and OCC (Operational Contral Center) has increased significantly, and the licensed spectrum range is gradually unable to satisfy the data transfer task of URT communication systems(URT-cs). therefore, this article considers to use LTE-U (Long-Term-Evolution in unlicensed spectrum) technology to deploy this communication system in unlicensed spectrum. In view of the interference caused by the introduction to WLAN system which have already been deployed in unlicensed spectrum, a dynamic spectrum range duty cycle adjustment scheme based on Q-learning algorithm is proposed to achieve coexistence of the two system. the scheme takes spectrum range as state, modelling the spectrum range allocation as a Markov Decision Process, obtains the spectrum range allocation strategy through Q-learning algorithm. Simulation results show that, compared with fixed spectrum allocation, the proposed scheme has a higher throughput and user satisfaction. Realizing the transmission task of URT-cs while meeting the user satisfaction of the WLAN system, and the problem of spectrum resources insufficiency of URT-cs is well solved. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Data transfer

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Evaluation of the Performance for IM-RED and IGRED Algorithms using Discrete-time Queues

Evaluation of the Performance for IM-RED and IGRED Algorithm...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Hussein Abdel-Jaber Jawad Hasan Alkhateeb Malak El-Amir Faculty of Computer Studies Arab Open University Saudi Arabia Computer Engineering Department Prince Mohammad Bin Fahd University Khobar Saudi Arabia

ISBN: (纸本)9781665487726

Active Queue Management (AQM) algorithms mainly aim to control congested networks. Managing the congestion situation leads to offer better performance for the networks. Both Improved Gentle Random Early Detection (IGRED) and Improved RED (IM-RED) algorithms are compared in this paper. the comparison is conducted to find out which algorithm presents better performance between IM-RED and IGRED. the results demonstrate that IGRED provides more acceptable results for the following parameters: the mean queue length (mql), the average queueing delay (D) and the overflow packet loss probability (PLoss) during the occurrence of the congestion. According to this congestion, fewer packets where dropped using the IM-RED prior filling the buffer.

关键词： Packet loss Filling Delays communication networks Computational intelligence

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Lightweight Deep Learning Model for Airborne Object Classification

Lightweight Deep Learning Model for Airborne Object Classifi...

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international conference on communication systems and Network Technologies (CSNT)

作者： Vamsi Krishna Puduru Bethi Pardhasaradhi Sagar Koorapati Linga Reddy Cenkeramaddi ICT Dept. University of Agder Norway CSE Dept. Indian Institute Of Information Technology Design & Manufacturing Kurnool India CPU Design Group Qualcomm Technologies Austin TX

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Airborne object detection and classification play an important role in applications like military surveillance, border security, and public safety. the ability to accurately distinguish between airplanes, helicopters, drones, and birds is essential for monitoring and responding to potential aerial threats in real-time. this study leverages the AOD 4 dataset, which contains a comprehensive collection of 22,516 images spanning diverse environmental conditions. After organizing the dataset into four distinct classes, a custom lightweight Convolutional Neural Network (CNN) was developed to classify airborne objects. the proposed lightweight CNN achieves a remarkable accuracy of 97.12% and is able to outperform state-of-the-art pre-trained models in terms of accuracy and model size. On top of it, the model is also targeted at the various processors to unleash its potential to run in a real-time environment. the proposed model infers in 2.9 milliseconds on intel core i7 processor, which is a fourfold improvement compared to the MobileNetv3Small model. the findings from this study contribute to advancing the field of airborne object classification and pave the way for more robust real-world implementations.

关键词： Deep learning Accuracy Program processors Atmospheric modeling Surveillance Computational modeling Real-time systems Public security Convolutional neural networks Security

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Security of Emerging Technologies in Computer networks 14th

Security of Emerging Technologies in Computer Networks

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14th international conference on Applications and Techniques in Information Security, ATIS 2024

作者： Balasubramanian, Kannan School of Computing SASTRA Deemed University Thanjavur613401 India

ISBN: (纸本)9789819797424

In this research article, the research challenges and potential solutions in five key areas of advanced computer networking, namely Network Function Virtualization (NFV), Machine Learning in Network Security, 5G networks, Blockchain-Based Solutions for IoT Security, and Software-Defined Networking (SDN) are introduced and discussed. NFV faces issues in management and performance of the network, and issues in transitioning from traditional hardware. ML in security has issues with data quality, transparency, and adversarial robustness. 5G networks encounter deployment, spectrum, and edge computing integration challenges. Blockchain for IoT security must overcome consensus and interoperability hurdles. SDN adoption is hindered by security concerns and traditional management issues. Addressing these challenges will enhance network agility, efficiency, and security, enabling innovative applications such as dynamic service provisioning, proactive security defenses, high-bandwidth applications, and secure IoT ecosystems, ultimately transforming network management and utilization. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： 5G mobile communication systems

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