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IMFOCA-IOV: Intelligent Moth Flame Optimization based Clustering Algorithm for internet of Vehicle 14

IMFOCA-IOV: Intelligent Moth Flame Optimization based Cluste...

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14th international conference on computing Communication and Networking technologies, ICCCNT 2023

作者： Rani, Preeti Sharma, Rohit SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Electronics & Communication Engineering Delhi-NCR Campus Delhi-Meerut Road Uttar Pradesh Ghaziabad India

ISBN: (纸本)9798350335095

Intelligent transportation systems (ITS) are receiving much attention today because of their significant effect on transportation safety, efficiency, and convenience. the Vehicle ad hoc networks (VANETs) in the ITS network are enhanced through the internet of Vehicles (IOV), a continuation of the internet of things (IoT). In the IOV paradigm, the network's topology is extremely dynamic, and data is transmitted using 5G cellular communication. this work proposes an intelligent moth flame optimization-based clustering algorithm (IMFOCA) for the IOVs (IMFOCA-IOV). the IMFOCA-IOV algorithm provides maximum coverage for the IOV node with minimum cluster heads (CHs) required for routing. Simulation results are delivered to confirm that the IMFOCA-IOV algorithm can decrease the power consumption of IOV. the proposed IMFOCA-IOV algorithm performed better than CACONET, GWOCNET CLPSO, and MOPSO algorithms regarding the number of clusters and transmission range. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Service Migration Algorithm for distributed Edge computing in 5G/6G Networks 23rd

Service Migration Algorithm for Distributed Edge Computing i...

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23rd international conference on Next Generation Wired/Wireless Networks and Systems (NEW2AN) / 16th conference on internet of things and Smart Spaces (RuSMART)

作者： Kuznetsov, Konstantin Kuzmina, Ekaterina Lapteva, Tatiana Volkov, Artem Muthanna, Ammar Aziz, Ahmed St Petersburg State Univ Telecommun Dept Telecommun Networks & Data Transmiss St Petersburg Russia

ISBN: (纸本)9783031609930;9783031609947

In recent years, the volumes of information processed and transmitted over the network are rapidly increasing, while the demand for speed and quality of transmitted data is also increasing. As a result, there is a need to use edge computing, which allows reducing network response time and more efficiently using bandwidth, as well as significantly improving the performance of the data transmission system. Article describes the application of edge computing in the form of transferring processes to an edge computing cluster, and presents the results of research on existing migration processes, full transfer time and downtime, identifying the optimal migration process for further implementation of the service migration automation algorithm. the following empirical research methods were used in the work: comparative evaluation method and experiment. the work considers the transfer of computational processes to an edge computing cluster;a comparative analysis of methods for automated service migration is carried out;an optimal migration strategy is identified;an algorithm for automating service migration is developed. Solutions related to automation of migration are excellent for use in the field of internet of things. they contribute to improving application performance and reducing response time. Automatic service migration allows increasing process efficiency and reducing system maintenance costs."

关键词： kubernetes K8s virtualization service migration edge computing

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Research on Multi-level Trust Mechanism of internet of things 23

Research on Multi-level Trust Mechanism of Internet of Thing...

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8th international conference on Cyber Security and Information Engineering, ICCSIE 2023

作者： Zhu, Yun Xu, Wenxiang Jiangsu University of Science and Technology China

ISBN: (纸本)9798400708800

With 5G, the internet of things and other technologies becoming popular, cloud edge end integration gradually replaced centralized cloud computing has become the current development trend. However, due to the complex network environment, the security of massive and diverse terminal devices has become a challenge, and the traditional iot trust mechanism has been unable to apply to the cloud-side architecture. As a decentralized distributed ledger technology, blockchain has the characteristics of data immutable, unfalsifiable, traceable and jointly maintained by many aspects, etc. Integrating blockchain into the cloud-side architecture can enable data interaction between multiple participants with mutual trust, which can ensure data integrity and security. this paper proposes to integrate blockchain into the cloud edge architecture of the internet of things to solve the trust problem, and the edge node and the cloud node jointly maintain the blockchain environment, and adopt the fragmentation idea to form a temporary dynamic "community"to improve the throughput of trust evidence of the blockchain and thus improve the overall security of the internet of things system. An improved algorithm for detecting abnormal trust information based on Apriori is designed and deployed on cloud nodes. Experiments show that the improved detection algorithm can improve the detection efficiency and reduce the calculation consumption. © 2023 ACM.

关键词： Blockchain

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Innovative Solutions and Applications of 5G Smart Factory for Chip Packaging 19

Innovative Solutions and Applications of 5G Smart Factory fo...

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

作者： Li, Cheng Lu, Na Li, Yang Wei, Yao Jin, Ning China Telecom Corp Ltd Beijing Peoples R China

ISBN: (纸本)9798350333398

High-quality communication network is the cornerstone of enterprise digital transformation. Conventional 5G capacity has limited uplink bandwidth and uncertain jitter. this paper presents a standalone 5G industry construction scheme for digital transformation of Outsourced Semiconductor Assembly and Testing (OSAT) with on-premise design for wafer grind, dicing and other specific application scenarios. We use uplink enhancement, Dual Fed and Selective Receiving (DFSR), 5G Local Area Network (LAN) and other 5G advanced technologies to form a networking scheme including the wireless, transmission network and core network. through simulations, we demonstrate that the latency is less than 20ms which can meet the requirements of 99.99% of packets. Notably, we provide a fundamental paradigm to increase the performance of the 5G enhancement network for other semiconductor foundries.

关键词： Industrial internet latency 5G advanced wireless communication prototypes fabrication

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Anomaly Detection in Battery Charging Systems: A Deep Sequence Model Approach 21

Anomaly Detection in Battery Charging Systems: A Deep Sequen...

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21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zheng, Li Ding, Donghui Li, Zhao Gao, Jun Xiao, Jie Chen, Hongyang Dustdar, Schahram Zhang, Ji The Key Laboratory of High Confidence Software Technologies Ministry of Education China Peking University School of Computer Science Beijing China Hangzhou Yugu Technology Hangzhou China East China Normal University Shanghai China Zhejiang Lab Hangzhou China Technical University of Vienna Austria University of Southern Queensland Toowoomba Australia

ISBN: (纸本)9798350329223

While the popularity of electric vehicles brings great convenience to our lives, battery charging also leads to an increase in accidents, resulting in personal injuries and economic losses. the methods currently embedded in charging hardware mainly focus on the short-term state of the battery and fail to leverage historical information effectively. the development of the Industrial internet of things (IIoT) enables data collection from sensors on industrial devices, which can be analyzed using deep learning methods to support sophisticated analysis. this paper proposes an intelligent and secure battery charging system in the IIoT that establishes an interaction between battery charging devices and cloud-based algorithms. A novel anomaly detection method is introduced to deal with anomalous charging sequences by making good use of historical data. We evaluate our system using real-life data from 4,940 batteries in electric vehicles, and our experiments achieve satisfactory results in detecting anomalies in battery charging. © 2023 IEEE.

关键词： Charging (batteries)

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Social IoT Security and Privacy 6

Social IoT Security and Privacy

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6th international conference on Advanced computing and Communication technologies for High Performance Applications (ACCthPA)

作者： Maniveena Kalaiselvi Noorul Islam Ctr Higher Educ Dept Comp Sci & Engn Kanyakumari India RMK Coll Engn & Technol Dept Comp Sci & Engn Gummidipoondi India Anna Univ Chennai Tamil Nadu India

ISBN: (纸本)9798350398441

the internet of things (IoT) is a network of physically connected, online-connected, globally distributed things. Given that most smart gadgets are carried by people, we may take advantage of their owners' social connections to prevent interception by unauthorized users, which is consistent with the Social internet of things (SIoT) concept. SIoT combines social networks and IoT to enable communication between devices and people as well as information sharing. this convergence has enhanced both perspectives and given rise to new ecologies. Indeed, the inherent weaknesses of SIoT devices, combined with limited resources and heterogeneous technology, as well as the absence of particularly developed IoT protocols, provide ideal platform for the spread of specialised cyber attacks. the security of social IoT is a big concern since linked devices can lead to large amounts of personal data being gathered and retained by organizations. To ensure security, it is vital for firms to take mechanisms such as encryption, authentication, authorization, and access control to secure data and ensure privacy. Furthermore, businesses should adopt security rules and standards to ensure that data is handled securely. this can include routine software upgrades as well as the installation of firewalls and secure networks. this paper provides an overview of the privacy issues and requirements that SIoT currently confronts.

关键词： internet of things SIoT security challenges privacy cyber threats

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Federated Learning Based Secured Computational Offloading in Cyber-Physical IoST Systems 5th

Federated Learning Based Secured Computational Offloading in...

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5th international conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R)

作者： Gaba, Shivani Buddhiraja, Ishan Kumar, Vimal Makkar, Aaisha Bennett Univ Sch Comp Sci Engn & Technol Greater Noida UP India Univ Derby Dept Comp & Math Coll Sci & Engn Derby England

ISBN: (纸本)9783031235986;9783031235993

In the past years, there has been fast growth in various applications which generates penetrating and personal information dependent on the internet of things (IoT). the Softwarization of a network may improvise its inclusive flexibility. the software-enabled proficiency has made it functional for mobile devices, wireless, and telecommunication networks through the progression of technologies like software-defined network (SDN), and mobile edge networks. the applications of cyber-physical systems have also increased with the rise of cyber-physical internet of softwarized things (IoST) systems. To maintain the quality among users, managing the applications for latency of cyber-physical system (CPS) is mandatory. though edge computing and cloud computing have performed well in achieving latency-aware resource allocation, sometimes it fails to do secure computation offloading in cyber-physical IoST systems. this paper presents a novel federated scheme based on deep learning for fast computation offloading. Secondly, we develop a federated learning framework that allows cyber physical IoST systems to build a model in a privacy-preserving way.

关键词： internet of softwarized things (IoST) Cyber physical systems (CPS) Federated learning Offloading

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Enhancing Smart Agriculture Scenarios with Low-code, Pattern-oriented functionalities for Cloud/Edge collaboration 19

Enhancing Smart Agriculture Scenarios with Low-code, Pattern...

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19th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2023

作者： Fatouros, Georgios Kousiouris, George Lohier, theophile Makridis, Georgios Polyviou, Ariana Soldatos, John Kyriazis, Dimosthenis University of Piraeus Dept. of Digital Systems Piraeus Greece Innov-Acts Ltd Nicosia Cyprus Harokopio University Dept. of Informatics and Telematics Athens Greece CybeleTech Montrouge France University of Nicosia Dept. of Management Nicosia Cyprus

ISBN: (纸本)9798350346497

the integration of cloud computing and internet of things (IoT) technologies has brought significant advancements in the agriculture domain. However, the implementation of such systems often requires significant time and resources, making it challenging for smart agriculture providers to offer optimized yet affordable services for small and medium-sized farmers at scale. Low-code development platforms can be a viable solution to address these challenges, enabling non-experts to adapt or enhance existing applications with minimal coding. this paper presents a low-code approach to enhance smart agriculture scenarios with pattern-oriented functionality blocks for cloud/edge collaboration. It highlights the usage of a pattern collection for redesigning the implementation of smart agriculture applications that can enhance the data collection process as well as real-time decision-making and efficient resource management in the continuum. the effectiveness of the presented approach is demonstrated through the implementation of a case study in smart agriculture greenhouses. Evaluation results show that this approach can significantly reduce the time and effort required to deploy smart agriculture applications and provide data resilience. © 2023 IEEE.

关键词： internet of things

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Energy Efficiency of IoT-Edge computing in Smart Grid Using Deep Reinforcement Learning 5

Energy Efficiency of IoT-Edge Computing in Smart Grid Using ...

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5th IEEE international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2023

作者： Bin Dahari, Ahmad Fikri Asuhaimi, Fauzun Abdullah Bin Jafri, Muhammad Akmal Mohd Hatta, Mohd Khairil Universiti Sains Islam Malaysia Department of Electronic Engineering Nilai Malaysia Project Delivery and Technology Petronas Group Technical Solution Kuala Lumpur Malaysia

ISBN: (纸本)9798350304152

Smart grids have attracted more and more attention due to the characteristic of itself that provide much more interactive solution comparing from the conventional grid, such as enabling demand side management (DSM) and demand response and so on. In smart grid, Wide Area Networks (WAN) is a part of the largest communication network that provides communication to the energy generation domains such as solar panels. internet-of-thing (IoT) can be adopted to provide communication in WAN. However, IoT may suffer in term of quality of services as well as energy efficiency because of how far the data must transmit since WAN cover the largest area. therefore IoT-Edge computing can be adopted to process the data nearer to the sources of data generation before transmitting into the cloud services. Energy efficiency in IoT is critical especially when smart grid is considered. Specifically, when a fault occurs in a grid, the sensors and the technologies in the areas affected by the fault will be isolated and have the shortage of power supply. In this paper, we proposed power control method to curb the problem state before. To find the best action, deep reinforcement learning (DRL) is adopted. DRL has the ability to learn make decision in a dynamic environment through a combination of deep learning and reinforcement learning techniques. Simulation results show that with the proposed method, the energy efficiency manage to elevate. © 2023 IEEE.

关键词： Energy efficiency

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English Speech Recognition using Convolution Neural Networks and IoT 5

English Speech Recognition using Convolution Neural Networks...

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5th IEEE international conference on computing, Power, and Communication technologies, IC2PCT 2024

作者： Vijayakumari, R. Bannatti, Akshay Ashok Maranan, Ramya Kaur, Jaspreet Kamatchi, S. Department of Research and Innovation Saveetha School of Engineering Simats Krishna University Machilipatnam Chennai Kanchipuram India Simats India Gulzar Group of Institutions India Simats Krishna University Saveetha School of Engineering Machilipatnam Chennai TAMIL NADU Kanchipuram India

ISBN: (纸本)9798350383522

the middle era of speech popularity makes it viable for machines and those to communicate effectively and seamlessly. the demand for particular and dependable voice popularity structures is rising as internet of things (IoT) applications are expanding quick. the use of convolutional neural networks (CNNs) to enhance speech recognition performance, especially for the linguistic English language, is presented in detail in this summary. the complex phonetics and phonology of the English language, in addition to its numerous accents, dialects, and regional editions, are all covered within the field of linguistics. For efficient human-pc interplay in a whole lot of IoT contexts, including smart houses, healthcare systems, and voice-controlled gadgets, accurate linguistic English speech reputation is crucial. For quite a few pc imaginative and prescient and audio processing obligations, convolutional neural networks (CNNs) have turn out to be effective deep mastering fashions. In this paper, we explore the use of CNNs in IoT contexts for linguistic English voice popularity. the collection of speech data, preprocessing, function extraction, model schooling, and reputation are the primary components of the recommended system. To ensure robustness and generality, we use huge-scale datasets of English speech to train the CNN fashions. Backpropagation and stochastic gradient descent are used to educate the version whilst optimizing the parameters to lessen the popularity blunders. this summary's end emphasizes the significance of unique English speech popularity in IoT programs. We can improve the effectiveness of speech popularity systems for the linguistic English language via using convolutional neural networks. By allowing greater intuitive and herbal interactions via speech commands and voice-managed devices, the suggested approach creates new opportunities for seamless human-gadget engagement in IoT environments. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Audio analysis Convolutional Neural Networks (CNNs) Deep Learning internet of things (IoT) IoT applications IoT devices Language processing Linguistic English language Machine learning Natural Language Processing (NLP) Neural network models Speech recognition Speech-to-text Voice recognition

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