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检索条件"任意字段=5th International Conference on Distributed Computing and Internet Technologies"

共 3958 条记录，以下是91-100 订阅

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A Framework for Developing IoT and Edge computing-Based Smart Transportation Applications 5th

A Framework for Developing IoT and Edge Computing-Based Sm...

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5th international conference on computing and Network Communications, CoCoNet 2023

作者： Mitra, Poojarini Rehena, Zeenat Mukherjee, Nandini Techno Main Salt Lake West Bengal Kolkata India Aliah University West Bengal Kolkata India Jadavpur University West Bengal Kolkata India

ISBN: (纸本)9789819745395

Transportation is one of the main sectors responsible for negative environmental impacts. Integrating emerging technologies can help provide real-time, resilient, and intelligent solutions that are necessary for decarbonizing road transport. this paper presents a novel framework that combines the internet of things (IoT), Edge computing, and Cloud computing to deliver sustainable and efficient transportation solutions. the proposed framework facilitates the development of smart transportation applications that envision an efficient way of reducing emissions, optimizing traffic flow, and improving overall transportation efficiency by leveraging the huge storage and computational power of Cloud computing and the real-time data processing capabilities of Edge computing. In addition, the virtual sensor is employed by the framework in order to reduce the adaptability, interoperability, and heterogeneity constraints in the IoT environment. this paper examines the shortcomings of current systems, highlights the essential elements of the framework, and assesses the framework’s effectiveness in providing effective and efficient smart transportation services. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud computing Edge computing Environmental sustainability internet of things Smart transportation system Virtual sensors

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Intrusion Detection at the Edge computing: A Deep Learning Approach Using the UNSW-NB15 Dataset 14

Intrusion Detection at the Edge Computing: A Deep Learning A...

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14th IEEE international conference on Communication Systems and Network technologies, CSNT 2025

作者： Kumar, Vipin Kumar, Vivek Bhadauria, Abhay Pratap Singh Dixit, Jay Kumar, Amit Haridwar India Department of Computer Engineering & Applications GLA University UP Mathura India

ISBN: (纸本)9798331531935

Edge computing has transformed technology by enabling seamless connections between IoT devices, but it also introduces significant security challenges. EC is crucial for providing minimal latency processing and reducing the load on centralized servers, ensuring timely and scalable intrusion detection for IoT environments. the findings underscore the potential of combining edge computing, IoT, and deep learning to address evolving security challenges in distributed systems. To mitigate these risks, efficient models for detecting malicious activities are crucial. this study investigates the application of edge computing, internet of things (IoT), and deep learning to improve the performance of Intrusion Detection Systems (IDS). By leveraging the UNSW-NB15 dataset, the research assesses the capability of deep learning models to identify and mitigate cyber threats effectively. the results demonstrate better performance, showing their suitability for real-time security applications. these findings highlight the potential of intelligent intrusion detection systems powered by robust datasets and deep learning for addressing evolving security threats in edge computing environments. © 2025 IEEE.

关键词： Edge computing

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Highly Available internet Border Systems Survey and Reference Model 5

Highly Available Internet Border Systems Survey and Referenc...

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5th international conference on computing and Informatics (IEEE ICCI)

作者： Minton, J. A. Laughlin, Dan UALR Comp & Informat Sci Little Rock AR 72204 USA Brooks Sports Inc CISSP Seattle WA USA

ISBN: (纸本)9781665499736;9781665499729

the exponential growth of organizations connecting to the internet increases the demand and expectations for technology professionals to provide highly available (HA), adaptable, always-on internet and network connectivity services to the enterprise. the rapid adoption of prevailing technologies and initiatives such as cloud-based workloads, Artificial Intelligence (AI), Machine Learning (ML), and digital transformation are fueling the growth. Organizations rely upon hardware, software, processes, and people, which form internet border systems. internet border systems provide internet connectivity and access to external network services and resources. Despite the enterprise's increased connectivity demands, a standards-based model, blueprint, or reference architecture for designing and deploying HA internet border systems does not exist. this paper proposes creating a standards-based, modular, and reproducible HA internet border system model. the internet border model will provide a frame of reference and enable always-on, automated, resilient, and self-recovering internet border connectivity services for enterprise networks. the reference model will assist technology professionals in planning, designing, creating, and deploying HA internet border systems for enterprise networks.

关键词： cloud highly available always-on architecture routing

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Development of Design Patterns with Adaptive User Interface for Cloud Native Microservice Architecture Using Deep Learning With IoT 5

Development of Design Patterns with Adaptive User Interface ...

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

作者： Cherukuri, Bangar Raju Germantown MD United States

ISBN: (纸本)9798350383522

the development of design patterns with adaptive user interfaces using deep learning provides an innovative solution to address the demands of modern software systems. the design patterns play an essential role in obtaining scalability and reliability in the systems. the various challenges in the architectural designs and automatic decision-making techniques are attained through the aid of Adam optimization techniques integrated with the internet of things. through the process of integration with an adaptive user interface, the changing user needs are monitored by the system. the deep learning techniques help to automatically adapt and optimize itself without any external parameters. this helps to analyze the user interactions and to promote system efficiency with an enhanced performance ratio. the generation of constant streams of data is obtained through the internet of things. the real-time decisions are adopted by analyzing the user behaviour. the Adam optimization techniques are well-known for the training of neural networks. this helps to maintain and adopt fine-tuning of the system and maintaining optimum performance. thus the integration of deep learning with cloud-native microstructure architecture provides self-optimizing networks for each user in the dynamic nature of the IoT data in real-time environments. © 2024 IEEE.

关键词： Adam algorithm Adaptive user interface Decision-making Deep learning Design patterns internet of things Software systems

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the IoT in Security Architecture, Challenges, and Solutions 5th

The IoT in Security Architecture, Challenges, and Solutions

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5th international conference on Optical and Wireless technologies (OWT)

作者： Punia, Anita Tiwari, Manish Verma, Sourabh Singh Manipal Univ Jaipur Dept Comp & Commun Engn Jaipur Rajasthan India Manipal Univ Jaipur Dept Elect & Commun Engn Jaipur Rajasthan India

ISBN: (纸本)9789811916458;9789811916441

the internet of things (IoT) is a forerunner to the smart world, as it uses ubiquitous computers and networking to simplify and supply other services, such as easy monitoring of many phenomena in our environment. Environmental and everyday goods referred to as things, objects, or machines, are improving with computing and communication technologies in the internet of things. An IoT architecture may provide a variety of solutions for various industries, but its primary goal is to establish a functioning, scalable, flexible, maintainable, and cost-effective IoT ecosystem. this paper analyses the challenges of security and their solutions and presents well-defined security architecture as confidentiality of the privacy and security of the user, which could result in its wider mass acceptance.

关键词： internet of things Privacy Confidentiality Security Challenges

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FOGSAFE: IoT enabled V2V communication system for enhanced visibility and safety in low visibility conditions 1st

FOGSAFE: IoT enabled V2V communication system for enhanced v...

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1st international conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Ishita Izna Sharma, Kapil Department of Information Technology Delhi Technological University Delhi India

ISBN: (纸本)9781032874036

the development of the internet of things (IoT) idea in the form of internet of Vehicles (IoV) has provided a solution to all of the challenges associated with operating a vehicle. the full potential of IoV creates a distributed network of automobiles that cooperate with diverse vehicular systems, addressing numerous issues related to traffic monitoring and road safety measures. Due to their high latency and responsiveness delays, current technologies such as Vehicular Cloud computing, Vehicle Ad hoc Networks (VANET), and Mobile Cloud computing are not optimal. Vehicle Fog computing (VFC), a potential paradigm that combines fog computing and vehicle networks, offers VANETSs an efficient but different approach. Particle swarm optimization (PSO) algorithm is used to route the path optimization which leads to the most efficient routing paths being the best ones in the VANET. VFC boasts several advantages including very high throughput, consuming very little energy, and maintaining energy efficiency, with this hybrid model of Ada Boost and Random Forest Algorithm we get an impressive accuracy of 99.928%. © 2025 the Author(s).

关键词： Fog computing

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EdgeShield: Hybrid Real-Time Attack Detection in IOTA Tangle via Edge Devices 15

EdgeShield: Hybrid Real-Time Attack Detection in IOTA Tangle...

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15th international conference on computing Communication and Networking technologies, ICCCNT 2024

作者： Arunodhai, V. Susan, Leena P. Kannimoola, Jinesh M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Applications Amritapuri India

ISBN: (纸本)9798350370249

the internet of things (IoT) revolutionizes technology interaction by enabling seamless connectivity and automation, but it introduces significant security challenges. A distributed ledger technology (DLT) called IOTA Tangle, a utilizing a Directed Acyclic Graph (DAG), enables secure and feeless transactions among IoT devices. Despite its advantages, the IOTA Tangle faces threats such as replay attacks and double spending, which highlight vulnerabilities in distributed ledger technologies. To address these security concerns, we initially developed EdgeGuard, a rule-based system for spam detection within the IOTA ecosystem. However, its reliance on predetermined rulesets limited its adaptability. We have now enhanced our approach with EdgeShield, incorporating a neural network for superior threat *** enhances adaptability over EdgeGuard in threat detection for the IOTA Tangle by integrating machine learning. EdgeShield analyzes network packets to identify threats, leveraging machine learning to adapt to evolving risks. Trained using the MQTTSet dataset, it detects network-based threats such as denial-of-service (DoS) attacks and packet flooding. Tested with simulated IoT data, EdgeShield demonstrates effectiveness across various domains, particularly in healthcare IoT. Its decentralized processing on edge devices like the Raspberry Pi 4 enables immediate network traffic analysis, reducing reliance on centralized servers and improving system resilience. Additionally, real-time alerts empower administrators to proactively secure IoT deployments and maintain transaction integrity within the IOTA Tangle. this paper traces our research evolution from EdgeGuard to EdgeShield, highlighting advancements and demonstrating the enhanced security of IoT transactions on the IOTA Tangle. © 2024 IEEE.

关键词： and Decentralised Security Measures distributed Ledger Edge computing Edge Devices internet of things (IoT) IOTA Tangle Machine Learning Network Packet Analysis Real-Time Security

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ICDCN 2025 - Proceedings of the 26th international conference on distributed computing and Networking

ICDCN 2025 - Proceedings of the 26th International Conferenc...

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26th international conference on distributed computing and Networking, ICDCN 2025

ISBN: (纸本)9798400710629

the proceedings contain 63 papers. the topics discussed include: a cognitive resource aware orchestration of network services for 5G and beyond;multi-stream TSN gate control scheduling in the presence of clock synchronization;on-demand multi-node partial charging scheme using multiple wireless charging vehicles in WRSN;renting servers for multi-parameter jobs in the cloud;advanced method for flow frequency estimation and top-k heavy hitters detection in SDN leveraging programmable switch;mixing entanglement swapping and hop-by-hop transmission on heterogeneous quantum networks;federated learning-enabled network incident anomaly detection optimization for drone swarms;and deterministic collision-free exploration of unknown anonymous graphs.

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On the Robustness of Widely Linear Processing for FBMC-OQAM system with Short Prototype Filter 20

On the Robustness of Widely Linear Processing for FBMC-OQAM ...

引用

2024 international conference on Wireless and Mobile computing Networking and Communications

作者： Fhima, Hayfa Shaiek, Hmaied Bouallegue, Ridha Carthage Univ InnovCOM Lab SupCom Tunis Tunisia CNAM CEDRIC ILAETITIA Lab Paris France

ISBN: (纸本)9798350387452;9798350387445

In this paper, we study the impact of the prototype filter length on FBMC-OQAM equalization. this waveform is still considered as a promising candidate for beyond 5G and Narrow Band internet of things systems thanks to the well localized prototype filter providing high spectral efficiency, low side-lobes radiations and better robustness to users asynchronism, when compared to OFDM. As far as the prototype filter length gets shorter, the Inter-Carrier-Interferences level increases. In this context, we will demonstrate how the FBMC-OQAM prototype filter length impacts the performances of linear and widely linear processing. this work confirms the outstanding capability of widely linear processing in mitigating interference effects for non second order circular signals.

关键词： Widely Linear Processing FBMC-OQAM Short Filter Narrow Band internet of things

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Weather Prediction from Historical Data using Big Data technologies 5

Weather Prediction from Historical Data using Big Data Techn...

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5th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Choudha, Shaurya Singh, Aniruddh Kumar, Aman Gouthaman, P. School of Computing College of Engineering and Technology Department of Networking and Communications SRM Institute of Science and Technology Kattankulathur603203 India

ISBN: (纸本)9798331518097

Weather forecasting is an important function in a variety of activities such as agriculture, environment monitoring, and disaster management among others. Today with the development of technology, vast amounts of meteorological data are able to be collected and analyzed with the intention of improving prediction accuracy. the purpose of this work is to analyze the contribution of Big Data frameworks such as, Hadoop, MapReduce and Apache Spark in effective weather prediction processes. In a distributed system, historical weather data, satellite images and sensor readings are kept and manipulated through the HDFS storage. For effective data manipulation, MapReduce and Spark are used along with Hive and Pig for searching large datasets. Predictive analytics are performed using machine learning algorithms included in the MLlib package of Spark. these results are presented using the Tableau application, which shows the speed and accuracy of this Big Data approach in comparison to classical ones. the proposed work ends with a look into the prospects of Big Data in the field of weather forecasting and relevant problems in this area. © 2024 IEEE.

关键词： MapReduce

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