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Communication Analysis for Multidimensional Parallel Training of Large-scale DNN Models 25

Communication Analysis for Multidimensional Parallel Trainin...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Lai, Zhiquan Hao, Yanqi Li, Shengwei Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China

ISBN: (纸本)9798350330014

Multidimensional parallel training has been widely applied to train large-scale deep learning models like GPT-3. the efficiency of parameter communication among training devices/processes is often the performance bottleneck of large model training. Analysis of parameter communication mode and traffic has important reference significance for the research of interconnection network design and computing task scheduling to improve the training performance. In this paper, we analyze the parametric communication modes in typical 3D parallel training (data parallelism, pipeline parallelism, and tensor parallelism), and model the traffic in different communication modes. Finally, taking GPT-3 as an example, we present the communication in its 3D parallel training. © 2023 ieee.

关键词： Deep neural networks

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Design and Evaluation of a K8s-based System for distributed Open-Source Cellular Networks 19

Design and Evaluation of a K8s-based System for Distributed ...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Palomares, Javier Coronado, Estefania Rincon, David Shuaib Siddiqui, Muhammad i2CAT Fdn Barcelona Spain Univ Politecn Catalunya UPC Dept Network Engn Barcelona Spain Univ Castilla La Mancha Albacete Spain

ISBN: (纸本)9798350333398

Virtualization in cellular networks is one of the key areas of research where technologies, infrastructure and challenges are rapidly changing as 5G system architecture demands a paradigm shift. this paper aims to study the viability and the performance of cloud-native infrastructures for hosting network functions. the selected frameworks implement both the 4G and the 5G stacks and their network functions. this work considers a variety of scenarios for enabling the deployment of a distributed and open-source cellular network: a baremetal setup, an all-docker-based setup and the proposed Kubernetes setup. Moreover, an analysis of the impact that the Radio Access Network (RAN) and the Core Network (CN) have on computational resource utilization is presented as the network conditions vary. the design proposed in this work has been validated and analyzed using the proposed prototype and testbed. this paper proposes a design to increase resource usage flexibility and performance and reduction of deployment time. the analysis of the gathered data reveals that the deployments of containerized cellular networks display better performance in terms of flexibility, low startup times, and ease of deployment while consuming the same resources as the non-containerized.

关键词： Virtualization NFV SDN distributed systems 4G 5G Performance Evaluation

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2023 ieee 4th Annual Flagship India Council international Subsections conference: Computational Intelligence and Learning systems, INDISCON 2023

2023 IEEE 4th Annual Flagship India Council International Su...

引用

4th ieee Annual Flagship India Council international Subsections conference, INDISCON 2023

ISBN: (纸本)9798350333558

the proceedings contain 172 papers. the topics discussed include: reconstruction optimization of economic operation of distribution network based on data mining algorithm;ROI segmentation for breast cancer classification : deep learning perspective;evaluation of hotspot performance in IoT enabled wireless sensor network using special intermediate nodes in the network;a university innovation and entrepreneurship information sharing platform based on data mining and classification algorithms;data governance based on full-service data analysis domain of power grid;minimum utilization of energy resource via MAC routing protocol for mobile sensor network;sentimental analysis of movie review based on naive bayes and random forest technique;parallel algorithm of high precision surface modeling based on differential geometry;maximization of achievable sum rate and improvement in outage probability in intelligent reflecting surface (IRS) driven NOMA networks;automated 20-20-20 timers using facial detection and facial recognition;enhancement of routing flexibility by a novel distributed approach for WSN;and improvement of reliable data transmission signal by space diversity technique in wireless communication.

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Optimized Deep Learning-Based Intrusion Detection and Secure, Energy-Efficient Routing in Wireless sensor Networks 4

Optimized Deep Learning-Based Intrusion Detection and Secure...

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4th ieee international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Soni, Anita Bhalerao, Sidharth Maddineni, Tejaswi Ali, Syed Manzoor Rajini, J. Khare, Shubhi Ies University Department of Computer Science and Engineering Bhopal India Gyan Ganga Institute of Technology & Sciences Dept of Cse MP Jabalpur India Southern Illinois University Carbondale United States College-St Aloysius Institute of Technology India Kongu Engineering College Department of English TN Erode India Ggits MP India

ISBN: (纸本)9798331518981

the growth of WSN and the Internet of things (IoT) has been phenomenal as a consequence of recent technical developments. the supplier of cloud services experiences maximum delay due to the enormous amount of data processing required. the IoT is made possible by fog computing, which is an unsecured computing technology that supports programs on billions of connected gadgets in an efficiently and economical way. It has the potential to address issues with Internet of things applications that need location awareness, geolocation, low latency, and movement support. When it involves fog-based WSNs, cybersecurity is of the utmost importance, and IDS (intrusion detection systems) are often built using Deep Learning (DL) models. this method's design allows applications to run on platforms that are near the network's edge, reducing service overhead. A cloud-like system that provides users with preservation, software service, and computer assets. As a new method, it encounters many problems with security and privacy due to the fact that fog gadgets are often located in areas with low levels of protection. the confidentiality of information may be jeopardized by cyberattacks such as port scanning, disruption of service, probes, and man-in-the-middle attacks. the Cuckoo optimization method has shown results that are slightly better, with a precision of 99%. In addition, the Behavior-based IDS approach has shown moderate findings with a 99% success rate. © 2024 ieee.

关键词： Fog computing

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Enhanced Cyberattack Detection in Wireless sensor Networks Using Gradient Boosting Decision Tree 4

Enhanced Cyberattack Detection in Wireless Sensor Networks U...

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4th ieee international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Mohandas, R. Pavithra, A. Vinothkumar, E.S. Amarnath Prabhakaran, A. Gupta, Sumit Kumar Malik, Neeru Chennai Institute of Technology Department of Electronics & Communication Engineering Chennai India Department of Information Technology Trichy India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Thiruvallur India Nandha Engineering College Department of Biomedical Engineering Erode India St. Wilfred's P.G College Department of Physics Jaipur India Pimpri Chinchwad University Department of Engineering and Technology Pune India

ISBN: (纸本)9798350352931

Wireless sensor Networks (WSNs) are essential to the Internet of things despite their power constraints. As sensor deployment has increased, so have security risks, requiring effective attack detection and prevention solutions. Machine Learning (ML) might build strong systems that detect cyber threats in real time. Data preparation, feature extraction, and model training are used to improve WSN security in this research. Preprocessing included data purification, conversion, standardisation, and splitting. Principal Component Analysis (PCA) reduced dimensionality, preserved variance, and improved computing speed. Model training uses Gradient Boosting Decision Trees (GBDT), notable for its classification accuracy in complex datasets. Averaging 93.11 % accuracy, the GBDT model outperformed the BiLSTM and DCNN models. this high accuracy shows GBDT's capacity to identify and mitigate WSN-based IoT security threats. the findings show that machine learning, particularly GBDT, can efficiently identify WSN intrusions to improve IoT network security and resilience. this study establishes complete cybersecurity safeguards for the IoT ecosystem, enabling more secure and robust applications. © 2024 ieee.

关键词： Cyber attacks

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(POSTER) SmartTwins: Secure and Auditable DLT-based Digital Twins for the WoT 18

(POSTER) SmartTwins: Secure and Auditable DLT-based Digital ...

引用

18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Pittaras, Iakovos Polyzos, George C. Athens Univ Econ & Business Sch Informat Sci & Technol Dept Informat Mobile Multimedia Lab Athens Greece

ISBN: (纸本)9781665495127

Digital Twins and the Internet of things (IoT) are two of the most prominent recent concepts and technologies. the IoT supports many applications that merge the physical with the cyber world. this highlights the need for improved security. Here, we argue that digital twins can help in securing and strengthening the IoT by using them for interacting with the actual IoT devices. While most digital twins implementations are centralized, we propose to integrate distributed Ledger Technologies (DLTs) and digital twins into the IoT to realize decentralized, secure, available, flexible, and auditable blockchain-based IoT services for IoT devices that follow the W3C Web of things (WoT) standards. In this work, we present the design of SmartTwin, a blockchain-based digital twin framework for which we provide two different implementations using two different blockchains, we present the design trade-offs, and we discuss future research and development directions.

关键词： Digital Twins distributed Ledger Technologies Internet of things Sensing Actuation Blockchain Ethereum Hyperledger Fabric Auditability Availability

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PSO-CHS Routing Protocol for Energy Consumption Enhancement in Wireless sensor Networks 4

PSO-CHS Routing Protocol for Energy Consumption Enhancement ...

引用

4th ieee international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Fakhri, Israa Sabri Marhoon, Haydar Abdulameer Hussein, Mohsin Hasan College of Computer Science and Information Technology University of Kerbala Department of Computer Science Karbala Iraq Scientific Research Center Al-Ayen University Department of Computer Science Information and Communication Technology Research Group Thi-Qar Iraq

ISBN: (纸本)9798350352931

A region's Wireless sensor networks consist of sensors distributed over a region that collect and send environmental data to a central station. It measures humidity and temperature. the formation is based on many key ideas, including the routing system that optimizes data flow to the base station. Routing introduces limits and obstacles to better results. One challenge is choosing the cluster head, who aggregates data from nearby sensors and sends it to the base station. Many methods are used to choose the cluster head. Instead of GSTEB, DCBRP, and ETSRP, which are laborious and time-consuming, modern cluster head identification methods use artificial intelligence. this study selects the cluster head quickly and accurately using PSO-CHS (particle swarm optimization-Cluster Head Selection Routing Protocol). It improves execution time by 84.1%, delay matrix by 44.3%, and energy matrix by 80.4% over previous protocols. PSO-CHS design promotes energy efficiency, network durability, and packet loss reduction. © 2024 ieee.

关键词： Particle swarm optimization (PSO)

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Real-Time Indoor Target Tracking Using IoT and Wireless sensor Networks 4

Real-Time Indoor Target Tracking Using IoT and Wireless Sens...

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4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Katakwar, Sachin R. Jajulwar, Kapil K. Tadas, Surekha M. Tech Communication Engineering G H Raisoni College of Engineering Nagpur India G H Raisoni College of Engineering Department of Electronics and Telecommunication Engineering Nagpur India

ISBN: (纸本)9798331523923

Indoor target tracking presents significant challenges across various fields such as security surveillance, industrial automation, and healthcare. this research paper outlines the design and implementation of a reliable direction monitoring system aimed at achieving accurate indoor target tracking using IoT and wireless sensor networks. By utilizing advanced sensor technologies and sophisticated data processing algorithms, the proposed system enables real-time monitoring and precise localization of targets within indoor spaces. the combination of IoT devices and wireless sensor networks facilitates effective data collection, analysis, and visualization, thereby improving the overall performance of the monitoring system. the results indicate that the developed system is effective in accurately tracking and localizing targets, fulfilling the essential requirement for efficient indoor direction monitoring solutions. the paper concludes with a discussion on the practical implications and potential applications of this system, emphasizing its importance in enhancing indoor target localization across diverse sectors. © 2025 ieee.

关键词： Indoor positioning systems

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An Orderly Regulation Method of Grid Energy Storage Capacity Under distributed New Energy Access 4

An Orderly Regulation Method of Grid Energy Storage Capacity...

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4th international conference on Energy Engineering and Power systems, EEPS 2024

作者： Xiong, Xiaocui Chen, Songling Zhang, Xiaoming Zhang, Mingnian State Grid Huanggang Electric Power Supply Company Hubei Huanggang438000 China

ISBN: (纸本)9798350366914

the method of regulating energy storage capacity in the power grid mainly uses the normal distribution to generate the optimal solution for ordered regulation, which is easily affected by the convergence speed of energy storage load, resulting in poor regulation of energy storage capacity. therefore, it is necessary to consider distributed new energy access and design a new method for orderly regulation of energy storage capacity in the power grid. We have designed a decision-making process for the orderly regulation of energy storage in the power grid and considered the integration of distributed new energy to generate an orderly regulation strategy for energy storage in the power grid, thereby achieving disorderly regulation of energy storage in the power grid. the experimental results show that the electricity shortage rate, leveling cost, and excess electricity index are low, while the renewable energy capacity index is high. this proves that the designed orderly regulation method for power grid energy storage capacity has a good regulation effect and certain economic value, which helps to improve the comprehensive energy storage efficiency of the power grid and reduce power supply and distribution losses. © 2024 ieee.

关键词： Charge storage

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Solar Irradiance Forecasting Utilizing distributed and Federated Learning 25

Solar Irradiance Forecasting Utilizing Distributed and Feder...

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作者： Zhang, Hao Yan, Ke College of Information Engineering China Jiliang University Hangzhou China China Jiliang University National University of Singapore Singapore

ISBN: (纸本)9798350330014

Photovoltaic energy generation and prediction are crucial for the integration between solar plants and smart grid. Accurate solar radiation prediction is one of the most important research topics for solar energy generation. Existing deep learning methods require sufficient data for training for achieving the desired results. In traditional deep learning modeling, the data sets required for model training usually come from various data in different regions and organizations, and it is difficult to ensure data security and privacy protection. Federated learning can effectively utilize the data optimization model while ensuring data security and privacy, but there is still the risk of privacy leakage by analyzing the parameters uploaded by the client. To effectively utilize data optimization models while ensuring data security and privacy, we propose a method based on a federated learning framework and N-BEATS to achieve interpretable time series prediction of solar irradiance. the model builds the N-BEATS model on the solar irradiance datasets of multiple institutions in a distributed method, does not share local data to protect institutional data privacy, the concept of differential privacy (DP) is introduced, Gaussian noise is added to the parameters of the client before the server-side aggregation processing, the model parameters of each distributed node are collected through TCP communication for federated average, and the parameters are returned to each distributed node. the experimental results show that compared with other deep learning models, the model has better prediction accuracy under the premise of ensuring data security and privacy. © 2023 ieee.

关键词： Solar radiation

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