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Secure, Transparent, Supply Chain Supporting Agri-Food Provenance and Sustainability 15th

Secure, Transparent, Supply Chain Supporting Agri-Food Prove...

引用

15th international conference on Ubiquitous computing and Ambient Intelligence

作者： Martin, thomas Cowderoy, Tom Rafferty, Joseph Cadden, Trevor McIvor, Ronan Brennan, Lorraine Ulster Univ Belfast Antrim North Ireland Ulster Coll Dublin Dublin Ireland

ISBN: (纸本)9783031486418;9783031486425

the protein-I project is a cross Ireland initiative that takes a food systems approach to enhancing the sustainability of protein production across the island of Ireland, as part of the protein-I project, this study aims to produce a smart agricultural supply chain solution. there is a need for the requirements of the system to be tailored for the specific use case, agriculture on the island of Ireland is different from agriculture in other parts of the world. the average size of a farm in the Republic of Ireland is 32.4 ha [8], compare this to Australia where the average is 4,331 ha [7], therefore farm practices in Australia will be different. To develop a solution that is catered to the needs of the Agri-food sector on the island of Ireland this study gathered requirements from a series of workshops and interviews with stakeholders. Several use cases were presented by the stakeholders to identify the deficiencies in the current supply chain, and to address these challenges, a custom solution has been designed and implemented.

关键词： Secure supply chains blockchain distributed ledger technology carbon calculation sustainable living smart agriculture Internet of things Industry 5.0 protein-I project

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MECHATRON - Security Analysis of 6G and 5G Networks Using Multiaccess Edge computing 15

MECHATRON - Security Analysis of 6G and 5G Networks Using Mu...

引用

15th international conference on Networks of the Future

作者： Berardi, Davide Martini, Barbara Univ Mercatorum Dept Sci & Engn Rome Italy

ISBN: (纸本)9798350377774;9798350377767

Network security is a continuously evolving procedure now present in every aspect of communications. 5G and 6G networks are examples of networks that can suffer from network security problems and become critical assets for every operation. While the security of the infrastructure is operated at lower layers of the ISO-OSI stack and dedicated protocols or by specific researches on network slicing and Service Management and Orchestration [1], services such as Multiaccess Edge computing, Virtual Network Functions, and network assets need to be secured. We propose a security tool enabled by MEC: MECHATRON, which covers the security of Assets, Services, and Continuous Monitoring through an integrated platform.

关键词： 5G mobile communication systems

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Delay-based Fidelity Monitoring of distributed Network Emulation 15

Delay-based Fidelity Monitoring of Distributed Network Emula...

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15th international conference on Communication systems and Networks (COMSNETS)

作者： ElBouanani, Houssam Barakat, Chadi Dabbous, Walid Turletti, thierry Univ Cote Azur INRIA Sophia Antipolis France

ISBN: (纸本)9781665477062

distributed Network emulators (e.g., Mininet Cluster Edition) have proven to be an attractive solution to perform extreme-scale network and systems evaluation on smaller-size testbeds and experiment platforms. they can provide contained, customisable, and scalable testing environments for researchers to evaluate their contributions and reproduce their results. the major drawback of this approach in network experimentation is the use of virtual components (hosts, network switches, etc.) that do not behave with perfect similarity to the physical components they emulate, mainly due to the concurrency in using the underlay network and computing resources. We thus present in this paper a methodology to monitor emulation fidelity by measuring the network delays of emulated packets, which relies on statistical metrics to evaluate their inaccuracy. We further dig into the possible sources of emulation inaccuracy and show how our system can detect them to avoid biased experiment results. We particularly show through a common experiment scenario how undetected network emulation errors can lead to biased results.

关键词： network emulation passive monitoring delay measurement

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distributed Ledger Based Educational Degree Authentication and Integrity System 15

Distributed Ledger Based Educational Degree Authentication a...

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

作者： Suneela, Mathe Srilatha, Dande Venkateswara Rao, K. Asha Priyadarshini, M. Reddy, Byreddy Sudhakara Pedapudi, Ramya Vignan’s Lara Institute of Technology & Science Vadlamudi AP Guntur India AP Guntur522508 India

ISBN: (纸本)9798350370249

In today's digital era, traditional methods of academic certificate validation are plagued by inefficiencies and vulnerabilities to fraudulent activities. To combat these challenges, integrating blockchain technology presents a promising solution. Originally designed for cryptocurrencies such as Bitcoin, blockchain offers a decentralized ledger system characterized by transparency, cryptographic security, and immutability. this research endeavors to explore the utilization of blockchain for the validation of student certificates. Our proposed system aims to develop a robust platform for issuing, storing, and verifying certificates, leveraging blockchain's distributed consensus and cryptographic features to ensure integrity and authenticity. Additionally, the system will incorporate user-friendly interfaces, seamless integration with existing educational systems, and advanced security measures to enhance user experience and trust in the validation process. this innovative approach grants individuals’ greater control over their credentials while mitigating risks of fraud and manipulation, thus revolutionizing the landscape of academic certificate validation in the digital age. ©2024 IEEE.

关键词： distributed ledger

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12th international Workshop on Load Testing and Benchmarking of Software systems: LTB'24 Chairs' Welcome 15

12th International Workshop on Load Testing and Benchmarking...

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15th ACM/SPEC international conference on Performance Engineering (ICPE)

作者： Fokaefs, Marios Oliveira, Filipe Ezzati-Jivan, Naser York Univ Toronto ON Canada Redis Lisbon Portugal Brock Univ St Catharines ON Canada

ISBN: (纸本)9798400704451

It is our great pleasure to welcome you to the twelfth edition of the international Workshop on Load Testing and Benchmarking of Software systems - LTB 2024, (https://***/). this one-day workshop brings together software testing and software performance researchers, practitioners, and tool developers to discuss the challenges and opportunities of conducting research on load testing and benchmarking software systems, including theory, applications, and experiences. LTB 2024 includes 2 keynote talks, 4 research papers, and 2 industry presentations. the topics cover performance of serverless computing, performance and load testing, performance-driven culture, workload generation, workload tracing, benchmarking, and performance verification.

关键词： benchmarking performance and load testing performance of serverless computing performance verification performance-driven culture workload generation workload tracing

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Federated Ensemble for Lung Pneumonia Detection 15

Federated Ensemble for Lung Pneumonia Detection

引用

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

作者： Sharma, Vishwash Challa, VenkataHemant Kumar Reddy Pranavi, Pasupuleti Singh, Tripty Nair, Rekha R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Alliance University Alliance School of Advanced Computing Department of Computer Science and Enginnering Bengaluru India

ISBN: (纸本)9798350370249

In the realm of medical imaging, the detection of lung pneumonia through automated methods has garnered significant attention due to its potential to augment diagnostic processes. this study proposes a novel approach, termed Federated CNN Ensemble, aiming to enhance the accuracy and robustness of pneumonia detection from chest X -ray images through federated learning and ensemble techniques. the proposed method leverages convolutional neural networks trained locally at distributed medical institutions, thereby preserving data privacy and security while harnessing collectiveintelligence. By aggregating the learned models through an ensemble strategy, our approach achieves superior performance in pneumonia detection compared to standalone CNN models. this research contributes to the advancement of automated medical diagnosis systems, offering a promising avenue for scalable and collaborative disease detection in healthcare settings. © 2024 IEEE.

关键词： DeepLearning Ensemble models Federated Learning

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distributed Large Memory and Message Passing Interface in Cloud Environment using OpenStack Cloud Platform 15

Distributed Large Memory and Message Passing Interface in Cl...

引用

15th international conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Deshmukh, Pranjali P. Prof. Ram Meghe Institute of Technology & Research Badnera Amravati India

ISBN: (纸本)9798331300579

distributed large memory offers the use of large virtual memory by using remote memory distributed over nodes in a cluster. the message passing interface (MPI) plays important role in DLM. MPI-based DLM manages the large virtual memory over the cluster using MPI batch queuing system. In distributed memory system message MPI is important parallel programming. As the number of virtual machines increases MPI and shared memory parallel programming combined to perform efficient communication in virtual machines [1,2]. Various tasks communicate with each other by sharing memory on the different disk through shared memory distributed computing. If various tasks are trying to access same the same memory location for reading and writing purpose, sometimes it may cause deadlock. In this case synchronization mechanism should handle such situation to keep the integrity of the data [2]. MapReduce and Hadoop are having inbuilt functions to handle distributed shared memory mechanism. the distributed computing with MPI can process thousands of parallel processes in cloud environment. © Grenze Scientific Society, 2024.

关键词： Cloud platforms

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IoTinuum: the IoT computing Continuum 20

IoTinuum: The IoT Computing Continuum

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20th Annual international conference on distributed computing in Smart Sensor systems and the Internet of things (DCOSS-IoT)

作者： Kamienski, Carlos Zyrianoff, Ivan Bittencourt, Luiz Fernando Di Felice, Marco Fed Univ ABC Santo Andre SP Brazil Univ Bologna Bologna Italy Univ Estadual Campinas Campinas SP Brazil

ISBN: (纸本)9798350369458;9798350369441

IoT smart applications must deal with the inherently distributed nature of IoT infrastructures that may vary among different deployments. For example, in urban environments, some deployments may require distributed edge nodes to support the sensors and actuators, while others may skip this processing stage and go directly to the cloud. We propose the concept of an IoT computing Continuum, or IoTinuum, with multiple computing stages spread over the distributed IoT infrastructure. We present the modeling and implementation of two urban use cases for a 6-stage IoTinuum: smart drone delivery and smart structural monitoring. In our experience, the IoTinuum improves the understanding of function placement in application development and reveals important performance tradeoffs.

关键词： edge computing fog computing IoT smart applications

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Enhancing Security in VANETs using distributed computing: A Review 15

Enhancing Security in VANETs using Distributed Computing: A ...

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15th IEEE Annual computing and Communication Workshop and conference, CCWC 2025

作者： Pavuluri, Vamsi Krishna Borah, Abinash Paranjothi, Anirudh Khan, Mohammad S. Oklahoma State University Department of Computer Science StillwaterOK United States East Tennessee State University Department of Computing Johnson CityTN United States

ISBN: (纸本)9798331507695

Vehicular Ad-Hoc Networks (VANETs) are a cornerstone of intelligent transportation systems, enabling vehicles to communicate with each other and roadside infrastructure to enhance traffic safety and efficiency. Securing VANETs remains a critical challenge due to the dynamic and decentralized nature of vehicular communications. this paper reviews and analyzes various distributed technologies-blockchain, fog computing, and federated learning-deployed for enhancing VANET security. Each technology's efficacy in addressing some of the security issues is assessed, revealing its strengths in improving data integrity and trustworthiness. However, challenges such as scalability limitations, high computational overheads, and susceptibility to single point of failure persist. Future research directions are proposed to bolster fault tolerance, load balancing, and scalability, aiming to advance the resilience and efficiency of distributed VANET security solutions. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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DyRAM: Dynamic Data Allocation and Resource Management in distributed Machine Learning systems 15

DyRAM: Dynamic Data Allocation and Resource Management in Di...

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15th Ubiquitous computing Electronics and Mobile Communication conference

作者： Tiwari, Vaibhavi thakkar, Rahul Wang, Jiayin Montclair State Univ Sch Comp Montclair NJ 07043 USA

ISBN: (纸本)9798331540913;9798331540906

the rapid evolution of digital technologies and the pervasive nature of data connectivity have significantly expanded the scope of decentralized machine learning tasks. At the forefront of this shift is distributed machine learning, which leverages distributed data while promoting privacy and efficiency. Built on the principles of cloud computing, distributed machine learning decomposes complex computational tasks into smaller components processed concurrently across interconnected nodes, optimizing resource utilization and scalability. the global cloud computing market, integral to the advancement of distributed machine learning, is projected to grow substantially, reaching USD 2,495.2 billion by 2032. Central to this study is the Cloud-Based Ratio Proportion Data Distribution Algorithm (CB-RPDDA), an innovative solution to traditional data distribution inefficiencies. CB-RPDDA reallocates data based on the processing speeds of individual machines, ensuring optimal resource utilization and effective workload distribution. this method introduces a new perspective on dataset division among worker nodes, enhancing load balancing and performance. By integrating CB-RPDDA with distributed machine learning frameworks, we improve the efficiency of decentralized learning processes, ensuring efficient data distribution across nodes while maintaining data security and privacy. Our findings demonstrate the potential of combining CB-RPDDA with distributed machine learning to offer scalable, efficient, and secure machine learning solutions, driving significant advancements in the field.

关键词： distributed Machine Learning Resource Management Data Distribution

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