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iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobile and Static End Devices

iSFA: Intelligent SF Allocation Approach for LoRa-Based Mobi...

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IEEE Conference on Wireless Communications and Networking

作者： Anakhi Hazarika Nikumani Choudhury Dept. of Electrical & Electronics Engineering India Dept. of Computer Science & Information Systems India

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

LoRaWAN (Long Range Wide Area Network) is a low-power, wide-area wireless communication protocol designed specifically for the Internet of Things (IoT) and machine-to-machine (M2M) applications that enable long-range, bidirectional communication between low-power devices. Lo-RaWAN employs Adaptive Data Rate (ADR) technology to dynamically adjust the data rate for each device based on its signal quality and distance from the gateway. ADR enables improved network performance, extends device battery life, and simplifies network management, making LoRaWAN suitable for various IoT deployments. However, the end devices' inefficient utilization of radio resources (e.g., spreading factor and transmission power) significantly degrades network performance, device battery life, and adaptability to changing network conditions. Machine Learning (ML) algorithms analyze and optimize the real-time network conditions to enhance network performance. This work aims to develop an ML-based approach that adaptively selects the most suitable Spreading Factor (SF) for end devices (ED). Two independent ML algorithms such as K-means and Reinforcement Learning (RL) have been applied to EDs and Gateways, respectively, to dynamically allocate SF for both static and mobile EDs. Through simulations, the performance of the proposed mechanism is analyzed in terms of packet success rate, convergence time, energy consumption, latency, and throughput.

关键词： Performance evaluation Wireless communication Wide area networks Machine learning algorithms Reinforcement learning Logic gates Throughput

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Enhancing 6G-Satellite Network Integration with Artificial Intelligence: A Future Communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

引用

22nd International Learning and Technology Conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial Intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 IEEE.

关键词： Satellite communication systems

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Dynamic Topology Optimization for Efficient and Decentralised Federated Learning

Dynamic Topology Optimization for Efficient and Decentralise...

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Menegatti, Danilo Giuseppi, Alessandro Poli, Cecilia Pietrabissa, Antonio Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy Istituto Superiore di Sanità National Centre for Innovative Technologies in Public Health Department Rome Italy

ISBN: (纸本)9798350362480

Topology optimization in decentralised federated learning settings enables the design of policies aimed at minimizing the number of communication rounds needed to reach algorithmic convergence. Given a federation of autonomous agents, finding the optimal topology which guarantees that the underlying graph is connected is still an open issue. This paper proposes a novel energy-aware topology optimization algorithm with the goal to derive an optimal topology which maximizes the algebraic connectivity of the corresponding graph in presence of energy and communication constraints. The effectiveness of the proposed approach is validated in the context of a consensus-based federated learning algorithm over an e-Health scenario. © 2024 IEEE.

关键词： Federated learning

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Challenges and Solutions for Practical Implementation of Process Bus Based Substation Protection and Automation System

Challenges and Solutions for Practical Implementation of Pro...

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2023 IEEE Asia Meeting on Environment and Electrical engineering, EEE-AM 2023

作者： Soetomo, Kevin Hamamatsu, Koichi Thuan, Dinh Huu Linh, Nguyen Manh Quang, Lai Vu Okai, Makoto Power Grid System Solutions Toshiba Energy Systems & Solutions Corporation Engineering Dept. Kawasaki Japan Technical Department Ho Chi Minh City Viet Nam Ltd. Engineering Dept. Hanoi Viet Nam Ltd. Sales & Engineering Division Hanoi Viet Nam Toshiba Energy Systems & Solutions Corporation Protection and Control Dept. Fuchu Japan

ISBN: (纸本)9798350381061

The protection and control system in substations has undergone significant evolution since the era of hardwired systems. In recent years, the increasing trend of digital transformation (DX) across various fields, including protection and automation systems, has led to the promotion of IEC 61850 process bus-based digital substations. However, recent analysis and evaluation have revealed numerous challenges in various aspects, such as technical issues, system performance, test methods, maintenance, and economic considerations. Moreover, many of these challenges lie outside the scope of international standards like IEC 61850 and IEC 61869. As a result, the worldwide implementation of digital substations has been hindered. This paper aims to describe the issues encountered during the implementation of process bus technology and propose solutions that focus on optimizing system configuration based on our experience in implementing digital substation projects and developing MU and IED. Addressing these issues is crucial to fully unlocking the potential of digital substations. One of the most promising advantages is the availability of digital data collected from substation equipment. By utilizing this data, overall power system operational efficiency can be enhanced, and equipment management can be optimized. Predictive maintenance can be implemented, enabling the early detection of potential equipment failures, minimizing unplanned outages, and reducing the need for emergency repairs, which contribute to unnecessary carbon emissions and equipment downtime. Ultimately, digital substations empower end-users to reduce greenhouse gas emissions, improve energy efficiency, and seamlessly integrate power systems, thereby supporting the carbon-neutral initiative and facilitating the transition towards a sustainable energy future. © 2023 IEEE.

关键词： Energy efficiency

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controlled Dropout for Uncertainty Estimation

Controlled Dropout for Uncertainty Estimation

引用

2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Hasan, Mehedi Hossain, Ibrahim Rahman, Ashikur Nahavandi, Saeid Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3220 Australia Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350337020

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art performance for many applications, they still provide unreliable point predictions, which lack information about uncertainty estimates. Among various methods to enable neural networks to estimate uncertainty, Monte Carlo (MC) dropout has gained much popularity in a short period due to its simplicity. In this study, we present a new version of the traditional dropout layer where we are able to fix the number of dropout configurations. As such, each layer can take and apply the new dropout layer in the MC method to quantify the uncertainty associated with NN predictions. We conduct experiments on both toy and realistic datasets and compare the results with the MC method using the traditional dropout layer. Performance analysis utilizing uncertainty evaluation metrics corroborates that our dropout layer offers better performance in most cases. © 2023 IEEE.

关键词： dropout Monte Carlo dropout neural network Uncertainty estimation

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Multi-objective optimization for cloud provisioning: A case study in large-scale microservice notification applications 9

Multi-objective optimization for cloud provisioning: A case ...

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9th International Conference on Future Internet of Things and Cloud, FiCloud 2022

作者： Vrbaski, Mira Bolic, Miodrag Majumdar, Shikharesh University of Ottawa School of Electrical Engineering and Computer Science Ottawa Canada Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

An approach to optimizing a large-scale microservice deployment for a critical notification system is presented. This paper addresses optimization for three objectives: cloud service cost, cloud resource utilization of CPU, RAM and storage, and meeting the system notification deadlines. To the best of our knowledge, this is the first work dealing with multi-objective optimization for microservice notification applications where the notification load is variable and depends on other priorly executed microservice in request processes. Furthermore, best of our knowledge, this is the first work that is based on multi-objective optimization, analyzing and proposing a Pareto front and optimal list from preselected VM candidates. First, the paper formulates multi-objective optimization problems for microservice-based large-scale notification system applications and provides the mathematical deployment model. Then, based on the expected workload and required multi-objective criteria, the paper proposes a set of algorithms that provide the Pareto front optimal solution for preselecting a Cloud Service provider's VM type. In the end, the paper presents a case study that demonstrates the use of the proposed technique. © 2022 IEEE.

关键词： Multiobjective optimization

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Reliable Data Storage and Sharing using Block chain Technology and Two Fish Encryption 4

Reliable Data Storage and Sharing using Block chain Technolo...

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4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Sivanantham, S. Sakthivel, M. Krishnamoorthy, V. Balakrishna, N. Akshaya, V. Sree Vidyanikethan Engineering College Dept. of Computer Science and Systems Engineering Andhra Pradesh Tirupati India Sree Vidyanikethan Engineering College Dept. of Computer Science and Engineering Andhra Pradesh Tirupati India Bannari Amman Institute of Technology Dept. of Computer Science and Engineering Tamilnadu Sathyamangalam India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Digital data that has been certified by a respected institution is valuable and can be saved or transmitted over the internet. However, the issues are ensuring the security and reliability of stored and shared data, as well as ensuring a secure, transparent, and fair data sharing process. As a result, The schemas for data production, storage, and sharing is suggested. A group signature scheme in the data production schema for a collection of respected organisations that provide similar services is used. A member of the group develops precious digital data from RD (raw data) provided by a DO (data owner) and then provides a certification based on the encipher of that data. The system saves the data's access address in the database after data owner uploading his or her data to the system in the data storage schema. Before submitting a data sharing proposal to the DO, every person on the system might validate the quality of shared data. The data sharing mechanism is carried out via a smart contract to incentivize honesty. The schemas assure the security properties of data storage and exchange, which include confidentiality, integrity, privacy, and non-repudiation. © 2022 IEEE.

关键词： Fish

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Underwater and In-Air IPT-CPT Wireless Power Transfer Performance Comparison: A Simulation Study

Underwater and In-Air IPT-CPT Wireless Power Transfer Perfor...

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2023 IEEE International Conference on Environment and Electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Shafiei, Sadjad Yazdi, Seyed Saeid Heidari Kermani, Mostafa Saukhimov, Almaz Hekmati, Arsalan Bagheri, Mehdi Nazarbayev University Dept. of Electrical and Computer Engineering Astana Kazakhstan Sapienza University of Rome Dept. of Electrical Engineering Rome Italy Almaty University of Power Engineering and Telecommunications Dept. of Electrical Systems and Networks Almaty Kazakhstan Revterra Company HoustonTXTX77004 United States

ISBN: (纸本)9798350347432

In this study, an inductive-capacitive coupling wireless power transmission (IC-UWPT) system in the seawater environment is discussed. It is revealed that the conductive characteristic of seawater medium will change the eddy current flow as compared to the air medium, and in higher frequency ranges, will increase power dissipation and affect the total efficiency and ultimately the system's performance. A new equivalent circuit is provided to precisely model the seawater WPT, where the eddy current losses are referred to as an additional term coil's parameter in the circuit model. Using Ansys Electronics, simulation studies are carried out in both air and water environment. The eddy current and electrostatic solutions are adopted for IPT and CPT system analysis. Moreover, Ansys Simplorer is utilized to couple the proposed IPT-CPT combined system. The simulation results validate the introduced model for the underwater IPT -CPT system and its performance. © 2023 IEEE.

关键词： Energy transfer

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A Review on Improvement in Detection of Cyberattacks Using Artificial Intelligence for the Grid Applications 11

A Review on Improvement in Detection of Cyberattacks Using A...

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11th IEEE Open Conference of Electrical, Electronic and Information Sciences, eStream 2024

作者： Vilkelyte, Zivile Wojciechowski, Jerzy Bojarczak, Piotr Fallah, Saad El Kharbach, Jaouad Jamil, Mohammed Ouazzani Vanagas, Jonas Vilnius TECH Dept. Electrical Engineering Vilnius Lithuania Casimir Pulaski University of Radom Dept. Control Systems and Electronics Radom Poland Fez Morocco Université Sidi Mohamed Ben Abdellah Faculté des Sciences Dhar El Mahraz Laboratoire de Physique de Solide Fez Morocco Vilnius TECH Vilnius Dept. Electrical Engineering Lithuania

ISBN: (纸本)9798350352412

The integration of artificial intelligence and machine learning technologies into critical infrastructures, such as smart grids, has raised significant concerns regarding cybersecurity. This paper explores the dual role of artificial intelligence and machine learning in both enhancing and challenging cybersecurity within smart grid systems. By analysing the current stateof-the-art research and technology, the utilisation of artificial intelligence and machine learning to fortify cybersecurity defences while addressing potential vulnerabilities. The the emergence of cyber threats targeting Internet-of-Things-based smart grids is highlighted and solutions to mitigate these risks are proposed. Through a comprehensive review of literature, the efficacy of artificial intelligence driven cybersecurity measures in detecting and preventing cyberattacks are evaluated. Additionally, challenges associated with implementing these solutions in smart grid environments, such as data complexity and computational requirements are taken into account. The findings underscore the critical importance of ongoing research and innovation to ensure the resilience of smart grid cybersecurity. © 2024 IEEE.

关键词： Smart power grids

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Privacy-Preserving Attribute-Based Access control with Non-Monotonic Access Structure 7

Privacy-Preserving Attribute-Based Access Control with Non-M...

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7th Cyber Security in Networking Conference, CSNet 2023

作者： Ashouri-Talouki, Maede Kahani, Nafiseh Barati, Masoud University of Isfahan Dept. of Information Technology Iran Carleton University Systems and Computer Engineering Canada School of Information Technology Carleton University Canada

ISBN: (纸本)9798350342871

Attribute-Based Encryption (ABE) with non-monotonic access policies provides fine-grained access control for widespread applications like Cloud-assisted HealthIoT systems. In this context, multi-authority ABE with untrusted authorities eliminates the need for a trusted authority, but ensuring user's identity and attributes-set privacy against these authorities remains a significant challenge. This paper proposes a new, efficient multi-authority ABE approach that preserves user's identity privacy and attributes-set privacy, and is secure against collusion attack. Also, the proposed approach provides non-monotonic access policies, which supports positive and negative constraints using NOT operation as well as AND and OR operations. © 2023 IEEE.

关键词： Access control

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