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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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Data-Driven Retention Strategies: Exploring the Efficacy of Composite Deep Learning for Customer Churn Prediction in Telecommunications 2

Data-Driven Retention Strategies: Exploring the Efficacy of ...

引用

2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Habelalmateen, Mohammed I. Bala Dhandayuthapani, V. Malathy, V. Pramodhini, R. Ramakrishna, D. The Islamic University Najaf Iraq College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Branch Department of It Oman Sr University Department of Ece Warangal India Nitte Meenakshi Institute of Technology Dept of Ece Bengaluru India Electronics and Communication Engineering Department Telangana Hyderabad India

ISBN: (纸本)9798350382952

The customer churn, otherwise known as subscriber loss, inclusive among one of the key challenges of the telecommunication industry (TCI). Forecasting churn gives rise to telecoms step-saving retentional strategies, serving as the means preventing losing revenue. To this research applies of the innovative customer churn prediction (CCP) model employing data transformation approaches and feature selection schemes. The work entail analyzing six data transformation methods (Log, Rank, Box-Cox, Z-score, Discretization, and weight-of-evidence) and eight classifiers such that each data conversion technique is applied or tested on multiple types of classifiers such as K-Nearest Neighbors (KNN), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF) The univariate way of feature selection is used to determine the features which have major effect and the proposal grid search is also adopted for hyperparameter optimisation. Experiments are conducted on four selected telecommunication industry (TCI) datasets. The evaluation of the model's performance involves using metrics such as accuracy and recall which are understood to be better than existing tools. © 2024 IEEE.

关键词： Telecommunication industry

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Identification of False Data Injection and Man in the Middle Cyber-Attacks Impact on Smart grid 3

Identification of False Data Injection and Man in the Middle...

引用

3rd international conference on Secure Cyber computing and Communications, ICSCCC 2023

作者： Vidya, Adarsh Madhukumar Sai, Deeraj D. Sarveshwaran, G. Mukesh, S.S. Chandrakala, K. R. M. Vijaya Amrita School of Engineering Department of Electrical and Electronics Engineering Amrita Vishwa Vidyapeetha Coimbatore India

ISBN: (纸本)9798350300710

There are numerous difficulties concerning cyber security in the smart grid, and a majority of such challenges faced across devices connected to the grid are in the form of nefarious attacks with the potential aim to tamper with power supplied to any consumer and breach of data respective to PMU and IP camera sensor. So, the best way to prevent such cyber-attack problems is by using security measures such as Network Intrusion Prevention Systems (NIPS) and firewalls equipped with each distributed system integrated into the grid. Many different attacks and prevention methods have been adopted to maintain the grid almost vulnerable to cyber-attacks. Therefore, this work aims to present the component-level cyber-attack analysis of PMU and IP camera sensors when connected to an IEEE 13-node system based on FDI and MitM attack scenarios. The study is simulated, and the results are obtained using gridAttackAnalyzer, a smart grid attack analysis framework. © 2023 IEEE.

关键词： Network security

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Exploring the Impact of Serverless computing on Peer To Peer Training Machine Learning 11

Exploring the Impact of Serverless Computing on Peer To Peer...

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11th IEEE international conference on Cloud Engineering (IC2E)

作者： Barrak, Amine Trabelsi, Ranim Jaafar, Fehmi Petrillo, Fabio Univ Quebec Chicoutimi UQAC Dept Comp Sci & Math Chicoutimi PQ Canada ETS Ecole Technol Super Dept Genie Log Montreal PQ Canada

ISBN: (纸本)9798350343946

The increasing demand for computational power in big data and machine learning has driven the development of distributed training methodologies. Among these, peer-to-peer (P2P) networks provide advantages such as enhanced scalability and fault tolerance. However, they also encounter challenges related to resource consumption, costs, and communication overhead as the number of participating peers grows. In this paper, we introduce a novel architecture that combines serverless computing with P2P networks for distributed training and present a method for efficient parallel gradient computation under resource constraints. Our findings show a significant enhancement in gradient computation time, with up to a 97.34% improvement compared to conventional P2P distributed training methods. As for costs, our examination confirmed that the serverless architecture could incur higher expenses, reaching up to 5.4 times more than instance-based architectures. It is essential to consider that these higher costs are associated with marked improvements in computation time, particularly under resource-constrained scenarios. Despite the cost-time trade-off, the serverless approach still holds promise due to its pay-as-you-go model. Utilizing dynamic resource allocation, it enables faster training times and optimized resource utilization, making it a promising candidate for a wide range of machine learning applications.

关键词： Serverless FaaS Function as a Service P2P peer-to-peer architecture distributed Training Machine Learning

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Application Analysis and Development Strategy of Cloud computing Technology in Computer Data Processing 2

Application Analysis and Development Strategy of Cloud Compu...

引用

2nd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Lina, Liu Changchun Humanities and Sciences College China

ISBN: (纸本)9798350347456

In the past, data processing was completed on a computer or a server. This is because the resources available at that time were limited. However, with the progress of technology, it is possible to use multiple computers and servers to process large amounts of data. This is where cloud computing comes into play. Cloud computing allows users to access data from anywhere at any time using an Internet connection. It also reduces the cost of enterprises because they do not have to buy additional hardware or software for each user. Aiming at the problems of single scale of traditional computer data processing and poor degree of adaptive parallel computing, this paper proposes a multi-source information accelerated data processing method of cloud computing technology, analyzes the application of cloud computing technology in computer data processing, and adopts the dynamic optimization technology of cloud computing speed to build a dynamic adjustment model of multi-source information data flow application of cloud computing, so as to reduce the energy cost of cloud computing, Combined with the experience of data processing users, the model can support multi-user computing entity sharing in the cloud to improve the running efficiency of data flow applications and reduce the energy cost of computer data processing. This article first outlines the basic meaning of cloud computing technology, starting with providing conditions for data transmission and sharing, and highlighting the application value of cloud computing technology. It analyzes the trend of cloud computing technology, and combines the modeling of cloud computing technology in computer data processing to propose application countermeasures for cloud computing technology in computer data processing. © 2023 IEEE.

关键词： Cloud computing

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A Modified Dual Loop Droop Control for parallel Operation of grid-forming Converters 8

A Modified Dual Loop Droop Control for Parallel Operation of...

引用

8th IEEE international conference for Convergence in Technology, I2CT 2023

作者： Awasthi, Anshul Bera, Souvik Ragavan, K. Indian Institute of Technology Electrical Engineering Gandhinagar India

ISBN: (纸本)9798350334012

distributed Generators (DGs) are becoming more integrated into the existing power system due to the growing popularity of renewable energy sources. However, in contrast to synchronous generators in a conventional power system, most renewable-based DGs are connected to the grid via a low inertial power electronic interface, which can impact the system stability significantly due to their uncertain generation. These power electronic converters can operate in grid following or grid forming mode. However, the latter taxonomy is the most widely used topology since it can operate in grid-connected or standalone modes and can self-restore the nominal frequency and voltage conditions. This article presents a modified dual loop droop control technique to operate two grid-forming converters in parallel, acquire precise power sharing, and maintain voltage regulation according to the DGs' rated capacities. The mathematical formulation and the simulation of the proposed control strategy are performed in MATLAB/Simulink, while OPAL-RT is utilized for the real-time digital simulation of the framework in Software in loop (SIL) mode. © 2023 IEEE.

关键词： Phase locked loops

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Enhancing Storage Efficiency of HDFS for Small Files by Dynamic File Pooling

Enhancing Storage Efficiency of HDFS for Small Files by Dyna...

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international conference on parallel distributed and grid computing (PDGC)

作者： Raveena Aggarwal Jyoti Verma Manvi Siwach Department of Computer Engineering JC Bose University of Science &Technology YMCA Faridabad India Department of Computer Applications JC Bose University of Science & Technology YMCA Faridabad India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

The technology is evolving fast. The data is growing faster. Apache Hadoop comes up as a capable platform to foster this rapidly progressing data. However, it is quite evident that the framework for Hadoop has been designed to manage large files. As soon as it has to face a lot of small files, the performance sinks. This further leads to metadata overheads, processing overheads, network clogging and a list of other issues. This paper proposes a novel framework for merging these small files into large files known as pools. These pools can be updated dynamically whenever subsequent datasets are fed into the system according to the empty space available. Dynamic file pooling significantly improves the storage efficiency of Hadoop distributed File System (HDFS). The results are obtained over a smaller dataset which can be scaled for over a million of files in real scenario.

关键词： File systems Merging Cluster computing Metadata grid computing Faces

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Improving the Heterogeneous computing Node Performance of the Desktop grid When Searching for Orthogonal Diagonal Latin Squares 11th

Improving the Heterogeneous Computing Node Performance of th...

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11th international conference on High-Performance computing Systems and Technologies in Scientific Research, Automation of Control and Production (HPCST)

作者： Albertian, Alexander M. Kurochkin, Ilya I. Vatutin, Eduard, I Russian Acad Sci Fed Res Ctr Comp Sci & Control Vavilova St 44Bldg 2 Moscow 119333 Russia Russian Acad Sci Inst Informat Transmiss Problems Bolshoy Karetny Lane 19Bldg 1 Moscow 127051 Russia Southwest State Univ 50 Let Oktyabrya St 94 Kursk 305040 Russia

ISBN: (纸本)9783030941413;9783030941406

The main goal of the work was aimed to create a parallel application using a multithreaded execution model, which will allow the most complete and efficient use of all available computing resources. At the same time, themain attention was paid to the issues of maximizing the performance of the multithreaded computing part of the application and more efficient use of available hardware. During the development process, the effectiveness of various methods of software and algorithmic optimization was evaluated, taking into account the features of the functioning of a highly loaded multithreaded application, designed to run on systems with a large number of parallel computing threads. The problem of loading all available computing resources at the moment was solved, including the dynamic distribution of the involved CPU cores/threads and the computing accelerators, installed in the system.

关键词： distributed computing system Desktop grid system Desktop grid Performance enhancement Xeon Phi Latin squares

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Attention Based Generative Adversarial Networks to Augment Image Data for Rapid Training

Attention Based Generative Adversarial Networks to Augment I...

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international conference on parallel distributed and grid computing (PDGC)

作者： Vijayakumar Adaickalam Sadagopan Selvarasu Gowthul Alam M A Suresh Kumar S Annamalai Sangeetha N School of Computer Science and Engineering and Information Presidency University Bangalore Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Chennai School of Computer Science and Engineering JAIN (Deemed-to-be University) Bangalore Department of AI & ML City Engineering College Bangalore

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

In this paper, we develop an Attention based Generative Adversarial Networks (AGAN) to augment image data for the purpose of robust training for efficient processing of the hyper spectral imaging. The AGAN model enables generation of images from the sample images that helps in training the classifier and in this study a fundamental classifier namely a convolutional neural network is used. A robust training is conducted to test the accuracy of detecting the instances effectively using the dataset. The simulation shows that the proposed AGAN-CNN attains improved accuracy after robust training than the existing methods.

关键词： Training Accuracy Training data Imaging Production Computer architecture Generative adversarial networks grid computing Convolutional neural networks Hyperspectral imaging

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Flexible Power Sharing Control of Modular Isolated Input-parallel-Output-parallel AC-DC Converters Based on High Frequency Link Current Estimation

Flexible Power Sharing Control of Modular Isolated Input-Par...

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2023 IEEE international conference on Power Electronics, Smart grid, and Renewable Energy, PESGRE 2023

作者： Nayak, Gourahari Dasgupta, Anindya Indian Institute of Space Science and Technology Department of Avionics Thiruvananthapuram India

ISBN: (纸本)9798350310573

This work proposes a voltage balance and flexible power sharing control strategy for modular input-parallel-output-parallel (IPOP) AC-DC converters with high frequency link (HF-link) isolation. Besides cell-to-cell power balancing, this scheme also enables controlled flexible power sharing. This control strategy is built upon the estimation of HF-link current fundamental component of each cell. The parameter estimation of each HF-link inductance based on fundamental current perturbation algorithm is proposed. This strategy requires measurement of only two currents: grid current and load current, irrespective of the number of cells, without any cell-to-cell current measurement. The proposed scheme is validated through PLECS simulation performed on a three cell modular isolated IPOP AC-DC converter. © 2023 IEEE.

关键词： estimation IPOP Isolated AC-DC converter parameter estimation state observer voltage and power balance

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distributed Task Allocation in Network of Agents Based on Ant Colony Foraging Behavior 23

Distributed Task Allocation in Network of Agents Based on An...

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24th international conference on Computer Systems and Technologies, CompSysTech 2023

作者： Minarolli, Dorian Polytechnic University of Tirana Tirana Albania

ISBN: (纸本)9798400700477

Task allocation is an important problem that is encountered in different distributed computing environments such as grid and cloud computing. In this paper we take a multi-Agent learning approach for task allocation in distributed systems composed of network of nodes where each node is connected to a fixed number of neighbor nodes. We developed an approach for distributed task allocation based on principles of ant colony foraging behavior. Ant colony systems as part of more general swarm intelligence systems are notorious for their self-organization, scalability, adaptability and robustness. Because of these properties these systems are very suitable for our distributed task allocation problem. We compared our approach with other heuristic based algorithms. Simulation results on different tasks lengths, load levels, node types and random network graphs show improved performance of our algorithm compared to other approaches. Especially, combining the ant colony based algorithm with an heuristic approach gives the best performance. © 2023 ACM.

关键词： Ant colony optimization

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