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检索条件"任意字段=3rd International Conference on Distributed Computing and Internet Technology"

共 8195 条记录，以下是271-280 订阅

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Research on optimal scheduling of distributed flexible resources based on regional energy autonomous balancing architecture 3

Research on optimal scheduling of distributed flexible resou...

引用

3rd IEEE international conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Yuntong, Lv Peng, Tao Zhitao, Wang Hongbo, Li Wei, Huo Xin, Xin State Grid Hebei Electric Power Co. Ltd. Marketing Service Center Hebei Province Shijiazhuang050022 China

ISBN: (纸本)9798350380989

In order to solve the problem of optimizing distributed flexible resources, a distributed flexible resource optimization scheduling model based on regional energy self-balancing architecture is proposed. The regional energy autonomous architecture is analyzed, focusing on the role of edge computing in the architecture, and explaining the basic principles of autonomous scheduling. The basic connotation of flexible resources is analyzed and the basic characteristics of flexible resources are explained. A multi-objective optimization model based on cloud-side distributed power capacity optimization, side-side model cost optimization, and end-side model revenue optimization is proposed, and is solved using the augmented Lagrangian function. Finally, simulation analysis was conducted based on the 39-node model to demonstrate the effectiveness of the model proposed in this article. © 2024 IEEE.

关键词： distributed flexible resources optimal dispatch regional energy autonomy renewable energy

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A Cloud Based Information Retrieval Agent System Using Web Services 3

A Cloud Based Information Retrieval Agent System Using Web S...

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Gupta, Namit Ojha, Ananta Ramya, V. Subha College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India University Karnataka Bangalore India Vels Institute of Science Technology Advanced Studies Department of Biomedical Engineering Channai India

ISBN: (纸本)9798350330724

Large, scalable computer resources are made available to consumers as a service via the cloud computing system, which runs over the internet. Both the business and scientific communities have shown a lot of interest in this technology. Nevertheless, there are no mechanisms for information retrieval and knowledge discovery in the concept of cloud computing. In other words, clouds need autonomy and intelligence. Within cloud computing settings, Web Services are an essential part of Service Oriented computing (SOC). A single Web Service is unable to get targeted and specialized information from Web Services inside a cloud environment. Agents may be used to help in the successful composition of Web Services. The main goal of this project is to propose a system to extract information in cloud environment by employing web services along with concept of multi-agent systems. © 2023 IEEE.

关键词： Web services

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Using Machine Learning Regression Model to Predict the Optimum Election Algorithm for Parallel and distributed computing Systems 3

Using Machine Learning Regression Model to Predict the Optim...

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3rd international conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Dhariwal, Naman Vellore Institute of Technology Department of Software Systems Vellore India

ISBN: (纸本)9798350370867

Parallel and distributed computing has become a necessity when it comes to high-performance computing, artificial intelligence, big data analytics, machine learning, deep learning, signal processing and bioengineering. System engineers connect distributed systems, with large number of nodes, that then compute the solution for a problem concurrently. The distributed system has a leader that manages the overall coordination of these connected nodes. This research provides a novel approach to predict the most efficient and time-feasible election algorithm, that must be ran on a distributed system, using linear regression machine learning approach. This research implements the prediction process for three election algorithms and successfully predicts the most efficient and least time-consuming algorithm with 94.98% accuracy. Initially, the dataset for the regression model training was created by executing the three election algorithms parallelly using MPI running 16 parallel processors (cores). The research also presents three regression line equations, trained and modelled on this dataset, that can be used to predict the execution time for the three algorithms for a system with any number of nodes. The results are duly visualized, and regression lines are plotted for comparison. © 2023 IEEE.

关键词： Forecasting

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An Improved Image Steganography Method for Domestic internet of Things 3

An Improved Image Steganography Method for Domestic Internet...

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3rd international conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Jharaniya, Himanshu Choudhary, Nitin Shrivastava, Gourav Sage University School of Advanced Computing Bhopal India

ISBN: (纸本)9798331528201

Domestic internet of Things (DioT) environment of a household requires prompt considerations in order to develop proper protection mechanisms for the transfer of sensitive information between linked devices. This created the need for this research work to put forward an improved image steganography technique for DIoT which employs AES encryption to encrypt the cover image and Least Significant Bit (LSB) for the insertion of the secret information table. This paper explains the design and implementation of the proposed method with clear indication of the improvement in security while maintaining system performance for data transfer. Therefore, the results of the evaluation in this article demonstrate the effectiveness of the proposed hybrid solution for strengthening the confidentiality and integrity of data exchanged within the complex environment of domestic IoT. © 2024 IEEE.

关键词： AES DIoT Image LSB Steganography

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An IoT Device Recognition Method based on Convolutional Neural Network 3

An IoT Device Recognition Method based on Convolutional Neur...

引用

3rd international conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Lu, Minghao Gao, Yali Li, Linghui Li, Xiaoyong Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9798350335972

Device recognition is the primary step toward a secure IoT system. However, the existing equipment recognition technology often faces the problems of unobvious data characteristics and insufficient training samples, resulting in low recognition rate. To address this problem, a convolutional neural network-based IoT device recognition method is proposed. We first extract the background icons of various IoT devices through the internet, and then use the ResNet50 neural network to extract icon feature vectors to build an IoT icon library, and realize accurate identification of device types through image retrieval. The experimental results show that the accuracy rate of sampling retrieval in the icon library can reach 98.5%, and the recognition accuracy rate outside the library can reach 83.3%, which can effectively identify the type of IoT devices. © 2023 IEEE.

关键词： Convolutional neural networks

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A Scalable Framework for Attack Detection: SWIM Transformer with Feature Optimization and Class Balancing 3

A Scalable Framework for Attack Detection: SWIM Transformer ...

引用

3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Cheekati, Srinivas Rayala, Ramya Vani Madhura, G.K. Borra, Chandrakanth Reddy University of the Cumberlands Williamsburg United States Nitte Meenakshi Institute of Technology Department of Aiml Bengaluru India

ISBN: (纸本)9798331508456

With the use of internet-connected operating systems and the deployment of cutting-edge advanced knowledges like artificial intelligence (AI), internet of Things (IoT), cloud computing, and deep learning within corporate organisations, industrial automation systems are undergoing a revolutionary transition. These new and creative ideas are helping to make Industry 4.0 possible. But these technological developments and the high-quality solutions they make possible will also bring up new security issues, the effects of which must be determined. Modern systems need sophisticated models that can handle big datasets, extract pertinent features, and deal with issues of class imbalance in order to identify attacks effectively. This paper presents a new framework that combines the SMOTE (Synthetic Minority Over-sampling Technique) model for balancing imbalanced datasets with the SWIM Transformer architecture and the Improved Pelican Optimiser for feature selection. By using attention mechanisms, the SWIM Transformer is able to precisely identify harmful activity by capturing complex patterns and correlations inside data. By improving feature selection, the Improved Pelican Optimiser lowers computing complexity while maintaining essential characteristics for precise classification. SMOTE also makes ensuring minority classes are fairly represented, which lessens the effect of unbalanced data on model performance. Results from experiments show that the suggested strategy outperforms current means in terms of detection accuracy, precision, recall, and F1-score. Additionally, the framework significantly decreased false positives and negatives, guaranteeing robustness and dependability in a range of assault scenarios. With possible uses in cybersecurity, intrusion detection systems, and other domains needing sophisticated anomaly detection, this research offers a scalable and effective attack detection method. © 2025 IEEE.

关键词： Industrial internet of things (IIoT)

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distributed Clean Energy Planning Based on Energy internet 3

Distributed Clean Energy Planning Based on Energy Internet

引用

3rd international conference on New Energy and Power Engineering, ICNEPE 2023

作者： Tuo, Minglang Company: Changqing Engineering Design Co. Ltd Electronic Instrument and Information Design Department Xi'an China

ISBN: (纸本)9798350393224

At present, distributed clean energy has been invented and utilized to generate electric power for industries or individuals. With the continuous expansion of distributed clean energy, the planning of locations has significantly become an essential issue for extending the effectiveness and utilization ratio of clean energy. However, existing investigations are primarily concentrated on the user-required energy or the area that can generate the largest clean energy, which ignores the systematical information and physical environment when locating the distributed energy. In this work, we utilize the internet structure to combine the electrical network and distributed clean energy. We set the agent to coordinate the energy supply information and realize the effective supplement. Finally, a distributed clean Energy internet structure is established by deploying the cell automation model. From our experimental results, we can conclude that the proposed planning system can achieve high effectiveness for distributed clean energy with a minimum response period. © 2023 IEEE.

关键词： Cell Automation distributed Clean Energy Energy internet System Network Planning

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Proceedings - 2023 3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

Proceedings - 2023 3rd International Conference on Pervasive...

引用

3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

ISBN: (纸本)9798350322842

The proceedings contain 293 papers. The topics discussed include: battery energy management systems in active distribution network;FMCG market analysis for wholesalers and retailers using machine learning;detection of insider threats using deep learning;bio-inspired optimization with transfer learning based crowd density detection on sparse environment;an overview on breast cancer detection and classification methods using machine learning techniques;disease prediction using random forest classifier by machine learning application;a study on working and applications of sequential deep learning models;internet of Things towards the implementation of a smart city;enhancing supply chain traceability with blockchain technology: a study on dairy, agriculture, and seafood supply chains;and customer segmentation and market analysis for portfolio generation.

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Optimized Bidirectional Long Short-Term Memory Model for distributed Denial of Service Attack Detection in Wireless Sensor Networks 3

Optimized Bidirectional Long Short-Term Memory Model for Dis...

引用

3rd international conference on Smart Technologies and Systems for Next Generation computing, ICSTSN 2024

作者： Poongodi, K. Mithuna, S. Rajkumar, S. K. S. Rangasamy College of Technology Computer Science and Engineering Tiruchengode637 215 India

ISBN: (纸本)9798350391565

The rapid expansion of Wireless Sensor Networks (WSNs) has made them a critical component in various applications, from environmental monitoring to military surveillance. However, their inherent vulnerabilities make them prime targets for distributed Denial of Service (DDoS) attacks, that have the potential to significantly impair data integrity and network performance. This paper presents an advanced approach for DDoS detection in WSNs using an optimized Bidirectional Long Short-Term Memory (Bi-LSTM) network. The proposed method leverages the strengths of Bi-LSTM in capturing temporal dependencies and patterns within network traffic data, providing a robust mechanism for identifying anomalous activities indicative of DDoS attacks. To enhance the detection accuracy and efficiency, introduce a novel optimization technique that fine-tunes the BiLSTM parameters, balancing the trade-offs between detection performance and computational overhead. Extensive simulations demonstrate that our optimized Bi-LSTM model significantly outperforms traditional machine learning approaches and standard LSTM configurations. The results underline the potential of this approach in fortifying WSNs against sophisticated DDoS threats, ensuring reliable and secure network operations. © 2024 IEEE.

关键词： Denial-of-service attack

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Search Engine for QnA using distributed Inverted Index System 3

Search Engine for QnA using Distributed Inverted Index Syste...

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3rd international conference for Innovation in technology, INOCON 2024

作者： Dey, Snehasis Moharana, Bhimasen De, Utpal Chandra Samant, Tapaswini Behera, Trupti Mayee Banerjee, Shobhan College of Engineering Electronics & Telecommunication Engineering Bhubaneswar India Lovely Professional University Department of Computer Science & Engineering Punjab India Kalinga Institute of Industrial Technology School of Computer Applications Bhubaneswar India Kalinga Institute of Industrial Technology School of Electronics Engineering Bhubaneswar India Birla Institute of Technology and Science Department of Engineering Technology Pilani India

ISBN: (纸本)9798350381931

The internet along with its global uses has also evolved as a platform where various people can pose their questions on certain sites and get them answered by others from the same domain. Certain sites like Quora, Reddit, Yahoo Answers, etc. are sites enabling people to enhance their range over the net to find solutions to various issues or answers to various questions. But this leads to redundancy in data & hence increased memory consumption where different users can pose the same question in different ways. The same thing stands for the answers posted by different users for the same question in various ways. In this paper, we have worked on a search engine system for Question & Answers where given a question, we can find similar questions with the same semantic meaning using Elastic Search which uses an inverted index system & looks at various aspects of the formulated problem statement. © 2024 IEEE.

关键词： Search engines

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