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High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

Tsinghua Science and technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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A Hypergraph Matching-Based Subchannel Allocation for Multi-Platoon's Communications

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IEEE Access 2023年 11卷 139345-139365页

作者： Huang, Chung-Ming Lam, Dan-Nguyen Dao, Duy-Tuan National Cheng Kung University Department of Computer Science and Information Engineering Tainan70101 Taiwan The University of Danang-University of Science and Technology Faculty of Electronics and Telecommunications Engineering Da Nang50000 Viet Nam

In a platoon communication scenario, the Platoon Leader (PL) vehicle interacts with the gNodeB (gNB) to obtain some assigned radio resources and then the obtained radio resources are allocated to the PL vehicle and its Platoon Member (PM) vehicles. The high transmission delay in the platoon network affects the quality of vehicles' connectivity. Therefore, the issues of improving radio resource's spectral efficiency and stability of the vehicle platooning with limited radio resources need to be tackled. This work proposes the 2-STage Resource Allocation (2-STRA) method for multi-platoon communication to reduce the transmission latency of platoon vehicles, i.e., it can improve the data transmission rates of platoon vehicles for the conditions of various speeds and various numbers of subchannels. In the $1^{st}$ stage, a greedy algorithm that jointly considers subchannel allocation and power control for PL vehicles' resource allocation is devised. In the $2^{nd}$ stage, the resource allocation for PM vehicles, which is based on the subchannels that are not allocated to PL vehicles, is resolved. A tripartite hypergraph, in which a tripartite hyperedge links:I 1) cluster of PM vehicles that use the same subchannel;2) individual cellular user;and 3) subchannel, is adopted to devise the PM vehicles' resource allocation algorithm. The simulation results show that the proposed 2-STRA method can have better performance in terms of spectral efficiency and the sum of data transmission rate comparing with the other methods. © 2013 IEEE.

关键词： Quality of service

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Optimizing AODV Routing Protocol to Improve Quality of Service Performance for V2V Communication

Optimizing AODV Routing Protocol to Improve Quality of Servi...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Bintoro, Ketut Bayu Yogha Priyambodo, Tri Kuntoro Musthofa, Muhammad Nurul Gadjah Mada University Faculty of Mathematics and Computer Sciences Dept.of Computer Science and Electronics Yogyakarta Indonesia Universitas Trilogi Faculty of Sciences Technology and Design Dept. of Informatic Engineering Jakarta Indonesia

ISBN: (纸本)9798350364101

The study focuses on Quality of Service (QoS) issues in learning automata-based AODV (LA-AODV) for V2V communication protocols. It analyzes and compares the LAAODV protocol with the original AODV protocol in dynamic traffic situations. The study evaluates critical metrics such as the number of vehicles, average speed, congestion spots, and vehicle time loss across various traffic scenarios, including smooth traffic, steady flow traffic, and heavy traffic. NS3 and SUMO are used as essential tools for this evaluation. The study finds that the LA-AODV protocol performs better in smooth traffic conditions than AODV. It demonstrates a 38.27% higher packet delivery ratio (PDR), an 85.26% lower packet loss ratio (PLR), and a remarkable 56.62% increase in average throughput compared to AODV. Both protocols exhibit similar performance in steady flow traffic with high PDRs (97.60% and 96.87%, respectively) and low PLRs (2% and 3%, respectively). However, AODV outshines LA-AODV with a higher PDR (97.60%)) than LA-AODV (96.87%) in heavy traffic. LA-AODV, on the other hand, excels in average throughput by 17.24% in heavy traffic. The study offers valuable insights for improving V2V communication protocols and enhancing communication efficiency to handle dynamic and traffic situations. © 2024 IEEE.

关键词： Quality of service

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engineering Framework for Smart Poultry Farming Using Internet of Things

Engineering Framework for Smart Poultry Farming Using Intern...

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2024 International Conference on Intelligent and Innovative Practices in engineering and Management, IIPEM 2024

作者： Manju, K. Dinesh, P.M. Deepa, K. Kathan, Karthik Lakshmi, G. Prasanna Alagarsamy, Manjunathan Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruchirapalli India Kongunadu College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Trichy621215 India Sandip University School of Computer Science and Engineering Maharashtra Nashik India K.Ramakrishnan College of Technology Department of Electronics and Communication Engineering Tamil Nadu Trichy621112 India

ISBN: (纸本)9798350390049

Automation is more important now. This article focuses on automating chicken farms using mobile communication devices and wireless sensor networks. Chicken is the world's most popular food because it contains more protein, less fat, and less cholesterol than other poultry. Chicken's nutrition is another benefit. This project utilizes the Internet of Things to monitor and adjust chicken farm environmental conditions. Temperature, moisture, water level, ammonia gas, and waste level were considered. This research aimed to improve chicken farm chick growth. The individual also monitors chicken behavior and feeding. Another usage for the sensor module is water level management and monitoring. If all sensors are connected to the microcontroller, all sensor data may be gathered. After that, a Wi-Fi module uploads the data to a website. A computer or mobile device connected to the internet allows the poultry farm owner to examine its interior surroundings. This informs the owner on agricultural conditions. This system will maintain temperature, humidity, and water level without human intervention using a DC motor, ventilation window, and co-exhaust fan. This will be done without human intervention. Devices will activate as needed when threshold values are attained. Our method allows semi-automated chicken product production and bird behavior monitoring. This allows us to deliver nutritious chicken meat while reducing bird killing. © 2024 IEEE.

关键词： Humidity sensors

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Production Cost and Emissions Minimization Based on Renewable Energy Using Superiority of Feasible Solutions- Moth Flame Optimization 4

Production Cost and Emissions Minimization Based on Renewabl...

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4th International Conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Alam, Mohammad Khurshed Sayem, Shaoran Sulaiman, Mohd Herwan Ferdowsi, Asma Islam, Mishiba Islam, Mohammad Zohurul American International University-Bangladesh Faculty of Electrical & Electronics Engineering Technology Dhaka Bangladesh Faculty of Electrical & Electronics Engineering Technology Pahang Pekan26600 Malaysia Sir Salimullah Medical College Hospital Pharmacology Department Dhaka1206 Bangladesh University of Louisiana at Lafayette Department of Electrical and Computer Engineering LA United States

ISBN: (纸本)9798331530938

This paper introduces a refined version of the Moth Flame Optimization (MFO) algorithm, Superiority of Feasible Solutions-Moth Flame Optimization (SF-MFO), in recognition of the significant influence of renewable energy on both production costs and secretion reduction in energy structure. To improve the symmetry among scrutiny and fleecing also to resolve the limitations of the early MFO, SF-MFO implements two significant enhancements. The algorithm's objective is to reduce emissions and optimize production costs by utilizing renewable energy sources, resulting in a combined reduction in both. Its primary intention is to decrease the total operating expense of the production system, as well as to address active power loss, voltage deviations at load buses, and the cost and emissions of combined units. The SF-MFO is analyse on IEEE 30-bus and IEEE 118-bus structure by transforming this multi-objective problem into a single-objective function with specific constraints and utilizing a bus location index to refine the list of candidate buses. The effectiveness and benefits of the suggested SF-MFO are then highlighted by contrasting the outcomes with those of other published algorithms. © 2025 IEEE.

关键词： Premixed flames

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Multi-Access Edge Computing Using Intelligent Mobile User Resource Allocation In 6G 4

Multi-Access Edge Computing Using Intelligent Mobile User Re...

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4th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2024

作者： Saeed, Mamoon M. Saeed, Rashid A. Mokhtar, Rania A. Gaid, AbdulGuddoos S. A. Ahmed, Zeinab E. Elbasheir, Mohammed S. Faculty of Engineering Department of Communications and Electronics Engineering Yemen Taif University Faculty of Engineering Department of Electrical and Electronic Engineering Altaif Saudi Arabia College of Computers and Information Technology Taif University Department of Computer Engineering Taif21944 Saudi Arabia Taiz University Faculty of Engineering & Information Technology Dept. of Communication & Computer Engineering Taiz Yemen International Islamic University Malaysia Department of Electrical and Computer Malaysia School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan

ISBN: (纸本)9798350372632

Edge computing plays a crucial role in the advancement of Beyond 5G (B5G) and 6G networks. The substantial growth in network traffic and computational requirements necessitates the implementation of multi-access edge computing (MEC) as a viable solution. MEC aims to bring the capabilities of cloud computing closer to end-users by integrating them into the radio access network (RAN). This research introduces an optimal approach to connect mobile users with MEC hosts and access points, effectively distributing radio and computing resources to individual mobile users. The objective is achieved by lowering the total user transmit power while abiding by latency constraints in both the communication and computation phases, using the Grey Wolf Optimization technique (GWO). A comparison to alternative smart techniques demonstrates the effectiveness of the suggested approach © 2024 IEEE.

关键词： 5G mobile communication systems

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A Perspective Analysis of Optical Biosensors in Machine Learning Applications 18

A Perspective Analysis of Optical Biosensors in Machine Lear...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Kumar, B. Naveen Panduranga Rao, M.V. Sharan, Preeta Varun, K.R. Kallam, Suresh Kumaresan, M. Faculty of Engineering and Technology Department of Computer Science and Engineering Bengaluru India The Oxford College of Engineering Department of Electronics and Communication Engineering Bengaluru India The Oxford College of Engineering Department of Mechanical Engineering Bengaluru India

ISBN: (纸本)9789380544519

Optical biosensors, a novel invention at the intersection of biotechnology and optics, are revolutionizing the field of biomedical diagnostics. Optical biosensors act by identifying variations in light's wavelength, phase, polarization, or intensity caused by interactions between a sensing element and the target analyte. Optical biosensors outperform other sensor types in sensing applications due to their quick, accurate, and extremely sensitive results. When evaluating optical sensors, total power, core power, efficient area, and indices are the most crucial variables to consider. Recent years have seen notable advancements in machine learning (ML), a branch of artificial intelligence (AI). This review investigates the complementary nature of optical biosensors and machine learning methods. Here, the potential utility of ML for optical biosensors is explored in detail. The advantages and drawbacks of the most popular machine learning methods are listed based on an analysis of the optical biosensing data. It highlights the possible effects of machine learning on improving the sensitivity, selectivity, and adaptability of optical biosensing devices, and it summarizes current advancements in the field. Finally, the study considers the challenges and limitations that associated with current optical biosensing techniques. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Machine learning optical biosensor photonic crystal surface plasmon resonance surface-enhanced Raman scattering

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A variable structure model of neurons’ application in computer vision

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Multimedia Tools and Applications 2025年 1-11页

作者： Sridi, Alaeddine Attia, Mouna Bouallegue, Kais Electronics and Micro-Electronics Laboratory Faculty of Sciences of Monastir University of Monastir Monastir Tunisia The Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse Tunisia Laboratory of Computer Science Parallelism and Intelligent Communicating Systems Faculty of Sciences of Tunisia University of Tunis ELManar Tunis Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the rise of neurocomputing, in which we try to digitally simulate human behavior. The goal being to better understand the human nervous system and gain more control over neuron-related diseases, helping doctors establish faster and more reliable medical diagnoses. In this context, we aim to simulate eye diseases and vision problems by convolving input images using a new class of neural networks based on a variable structure model of neurons presented in [1]. In this work, we focus on recreating the common convolution filters as a first step. This is the first time in neurocomputing literature that dendritic neurons have been used for dynamic convolution kernels generation and eye diseases simulation. We start with a presentation of our upgrades to the model’s flexibility and accuracy. Then, we propose a novel kernel generator algorithm to convolve the input images. Finally, we show its promising results in creating the outline, pixelization, and night convolution kernels, as well as control some metrics, including brightness and data retention. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Neurons

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Secured intelligent transportation with privacy retention through blockchain framework

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10507-10521页

作者： Kaur, Gaganpreet Shobana, M. Kavin, F. Sellakumar, S. Meenakshi, D. Bharathiraja, N. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Networking and Communications Faculty of Engineering and Technology SRM Institute of Science and Technology KTR Chengalput Tamil Nadu Chennai India Department of Electronics and Instrumentation M.S. Ramaiah Institute of Technology Karnataka India Department of Mechanical Engineering Saveetha Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Tagore Engineering College Tamil Nadu India

The Secured Independent Intelligent Transport System (SIITS) is poised to revolutionize traditional transport management systems, leveraging autonomous vehicles (AVs) connected through an open-channel Internet to link Traffic Command Centers (TCCs), Road Side Units (RSUs), and AVs within the SIITS framework. However, this reliance on the Internet exposes users to various security risks, safety vulnerabilities, and other challenges that impede the progress of SIITS applications. In this method, ensuring robust security management and trustworthiness is paramount for the long-term adoption of this innovative trend. While previous efforts have focused on integrating security methods from multiple disciplines into a unified reference design, this article presents a reference architecture primarily centered around ITS safety. Additionally, the article introduces a proposed framework for enhancing ITS safety, addressing the confidence issues. To further address these challenges, the article offers categorization of goods, Big Data methods and services, and validates the utility of ITS business analytics for corporate applications through a groundbreaking multi-tier ITS security architecture. © 2024 - IOS Press. All rights reserved.

关键词： Big data

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Knowledge-Enriched Graph Convolution Network for Hybrid Explainable Recommendation from Review Texts and Reasoning Path 7

Knowledge-Enriched Graph Convolution Network for Hybrid Expl...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Bastola, Rama Shakya, Subarna Nepal Open University Faculty of Science Health And Technology Lalitpur Nepal Tribhuvan University Pulchowk Campus Institute of Engineering Department of Electronics And Computer Engineering Lalitpur Nepal

ISBN: (纸本)9798350359299

In the digital era, organizations leverage technology to handle vast datasets, yet deriving meaningful insights remains a challenge. Recommender systems address this by using deep learning advancements to provide users with relevant content. However, ensuring transparency in recommendations, known as explainable recommendations, is difficult due to complex deep learning algorithms. Clarifying recommendations to both users and system designers to enhance comprehension and decision-making represents a significant research challenge in the field of explainable recommendation systems. Review-based explanations in human-like languages are intuitive to the general users while Reasoning-path based explanations are more informative to the system designers. The existing models focus on one of the above explanation approaches. This research proposes a hybrid explainable recommender model integrating review-based and reasoning path-based interpretation. The model utilizes external knowledge bases and review documents to create contextualized knowledge-enriched embeddings for users, items, and interactions. Path encoding with LSTM and attention mechanism is utilized for both rating prediction and reasoning path explanation. A Gated Recurrent Unit with a Copy Mechanism generates human-like recommendation explanations. The model yields both types of recommendation explanations and rating predictions comparable to state-of-the-art technologies. © 2024 IEEE.

关键词： Convolution

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