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Proceedings - 2021 IEEE 41st international conference on distributed computing Systems Workshops, ICDCSW 2021

Proceedings - 2021 IEEE 41st International Conference on Dis...

引用

41st IEEE international conference on distributed computing Systems Workshops, ICDCSW 2021

ISBN: (纸本)9781665449328

The proceedings contain 10 papers. The topics discussed include: QROSS: QUBO relaxation parameter optimization via learning solver surrogates;VPN-nonVPN traffic classification using deep reinforced naive bayes and fuzzy k-means clustering;personalized federated learning by structured and unstructured pruning under data heterogeneity;effect-centric networking;joint offloading and resource allocation of UAV-assisted mobile edge computing with delay constraints;backup placement in WSNs in the network management distributed setting;AI-based robust convex relaxations for supporting diverse QoS in next-generation wireless systems;dynamic DNN decomposition for lossless synergistic inference;and joint offloading and resource allocation of UAV-assisted mobile edge computing with delay constraints.

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Architecting a SDS for Microservices-based distributed Edge computing Systems 11

Architecting a SDS for Microservices-based Distributed Edge ...

引用

11th IEEE international conference on Software Defined Systems, SDS 2024

作者： Vora, Urjaswala Pennsylvania State University College of Information Sciences and Technology University Park United States

ISBN: (纸本)9798331518325

Software Defined Systems (SDS) abstract the actual hardware at different layers with software components, layers such as networking, Storage, Security, Servers, Data Centers, Clouds etc. This abstraction facilitates construction, integration / composition and management of complex systems effectively and sustainably. Microservices architecture is increasingly being used for designing and deploying large-scale application systems in both cloud-based and enterprise infrastructures where relatively small, loosely coupled microservices communicate with each other using lightweight communication protocols and abstract complex software application(s). We propose a sustainable SDS architecture to manage microservices of a distributed edge computing system which reduces dependency on any data centre / cloud infrastructure. © 2024 IEEE.

关键词： Cloud computing architecture

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The Intelligent Information Integrity Model to Ensure the Database Protection Using Blockchain in Cloud networking 2

The Intelligent Information Integrity Model to Ensure the Da...

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2nd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Raja Praveen, K.N. Rajat Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

In the era of cloud networking, database protection is a problem that is becoming more and more crucial, and blockchain technology is emerging as a potent remedy. Blockchain is a digital ledger technology that uses an immutable, distributed, and decentralized record of transactions to build a secure, transparent, and auditable data protection system. The integrity of data saved in the cloud is further ensured by using blockchain technology. By using cryptographic hashes, data stored on the blockchain can be verified for accuracy and authenticity. This means that any changes or modifications to the data will be detected and addressed. Furthermore, blockchain technology provides a permanent and immutable record of transactions, making it difficult for data to be tampered with or corrupted. In addition to its security benefits, blockchain technology also offers scalability, efficiency, and cost savings. Blockchain-based databases are much more efficient than traditional databases, as they require fewer resources and are able to process a larger volume of transactions. Furthermore, since blockchain technology is decentralized, it can work across multiple devices and networks, allowing for a more efficient and cost-effective solution. © 2023 IEEE.

关键词： Blockchain

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Virtual Try-On Application leveraging RoCE in Low-latency Edge computing Networks 24

Virtual Try-On Application leveraging RoCE in Low-latency Ed...

引用

24th international conference on Transparent Optical Networks (ICTON)

作者： Guaitolini, Michelangelo Khan, Abdul H. Le Rouzic, Emilie Paolucci, Francesco Cugini, Filippo Consorzio Nazl Interuniv Telecomunicaz CNIT Pisa Italy

ISBN: (纸本)9798350377330;9798350377323

Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. This allows low-latency applications where data collection, analytics and feedback to the user are distributed between different nodes, optimizing resource management. RoCE, originally designed for data center operations, has the potential to effectively support applications deployed on edge nodes, where limited resources are available and low latency is required. This demo shows the use of RoCE in support to an AI-based application for smart shopping, deployed at the edge.

关键词： Edge computing RDMA over Converged Ethernet Low-latency networking virtual-try on application smart shopping

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Resource-Limited Localized Adaptive Adversarial Training for Machine Learning Model 21

Resource-Limited Localized Adaptive Adversarial Training for...

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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： Rajhi, Mohammed Pissinou, Niki Florida International University School of Computing and Information Sciences MiamiFL United States Jazan University Faculty of Computer Science & Information Technology Jazan Saudi Arabia

ISBN: (纸本)9798350329223

Balancing robustness and computational efficiency in machine learning models is challenging, especially in settings with limited resources like mobile and IoT devices. This study introduces Adaptive and Localized Adversarial Training (ALAT), an optimization approach that balances these competing needs. ALAT combines generalized models with localized adversarial perturbations and adaptive data augmentation. As a result, the model strengthens its weak points without needing to explore all possible adversarial threats, saving computational effort Our data shows that ALAT-trained models perform robustly with less computational cost compared to traditional adversarial training methods. This adaptability makes ALAT suitable for various machine learning architectures and particularly valuable in resource-constrained settings requiring resilience to adversarial threats. © 2023 IEEE.

关键词： Computational efficiency

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Privacy-Preserving Federated Learning through Clustered Sampling on Fine-Tuning distributed non-iid Large Language Models 21

Privacy-Preserving Federated Learning through Clustered Samp...

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作者： Yun, Sheng Bhuiyan, Zakirul Alam Sadi, Md. Taufiq Al Hasib Su, Shen Fordham University Department of Computer and Information Sciences New York10458 United States North South University Department of Electrical & Computer Engineering Dhaka Bangladesh Guangzhou University Cyberspace Institute of Advanced Technology Guangzhou China

ISBN: (纸本)9798350329223

Recently, Large Language Models (LLMs) have been a phenomenal trend in the Artificial intelligence field. However, training and fine-tuning can be challenging because of privacy concerns and limited computing resources. Federated Learning (FL) has emerged as a novel machine learning framework offering privacy protection. The challenges in applying FL to real-world applications include dealing with heterogeneous data, poor client updates, and client selection. This paper introduces Privacy-preserving Federated Learning through Clustered Sampling on LLMs (FCLM), a framework that clusters models by their distribution similarity. It helps the model group similar models to improve text data heterogeneity handling and privacy concerns in distributed machine-learning environments. The FCLM framework is implemented and evaluated using popular Language models and text data. The framework shows a robust performance over the heterogeneous text data, which can further extend to the use of more complex LLMs. © 2023 IEEE.

关键词： Privacy-preserving techniques

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Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser Network 30

Misaligned Over-The-Air Computation of Multi-Sensor Data wit...

引用

30th international conference on Mobile computing and networking, ACM MobiCom 2024

作者： Du, Mingjun Zheng, Sihui Zhang, Xiao-Ping Dong, Yuhan Shenzhen Key Laboratory of Ubiquitous Data Enabling Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (纸本)9798400704895

In data driven deep learning, distributed sensing and joint computing bring heavy load for computing and communication. To face the challenge, over-the-air computation (OAC) has been proposed for multi-sensor data aggregation, which enables the server to receive a desired function of massive sensing data during communication. However, the strict synchronization and accurate channel estimation constraints in OAC are hard to be satisfied in practice, leading to time and channel-gain misalignment. The paper formulates the misalignment problem as a non-blind image deblurring problem. At the receiver side, we first use the Wiener filter to deblur, followed by a U-Net network designed for further denoising. Our method is capable to exploit the inherent correlations in the signal data via learning, thus outperforms traditional methods in term of accuracy. Our code is available at https://***/auto-Dog/MOAC_deep. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Channel estimation

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

引用

25th international conference on distributed computing and networking, ICDCN 2024

ISBN: (纸本)9798400716737

The proceedings contain 63 papers. The topics discussed include: post quantum communication over the internet infrastructure;efficient and resilient edge computing: algorithms, techniques and research opportunities;self-stabilizing byzantine multivalued consensus;a further study on weak byzantine gathering of mobile agents;distributed uniform partitioning of a region using opaque ASYNC luminous mobile robots;space and move-optimal arbitrary pattern formation on a rectangular grid by robot swarms;maximal independent set via mobile agents;collision-free linear time mutual visibility for asynchronous fat robots;arbitrary pattern formation on a continuous circle by oblivious robot swarm;sublinear message bounds of authenticated implicit byzantine agreement;and LightKey: lightweight and secure key agreement protocol for effective communication in internet of vehicles.

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SpDISTAL: Compiling distributed Sparse Tensor Computations

SpDISTAL: Compiling Distributed Sparse Tensor Computations

引用

international conference for High Performance computing, networking, Storage and Analysis (HPC)

作者： Yadav, Rohan Aiken, Alex Kjolstad, Fredrik Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781665454445

We introduce SpDISTAL, a compiler for sparse tensor algebra that targets distributed systems. SpDISTAL combines separate descriptions of tensor algebra expressions, sparse data structures, data distribution, and computation distribution. Thus, it enables distributed execution of sparse tensor algebra expressions with a wide variety of sparse data structures and data distributions. SpDISTAL is implemented as a C++ library that targets a distributed task-based runtime system and can generate code for nodes with both multi-core CPUs and multiple GPUs. SpDISTAL generates distributed code that achieves performance competitive with hand-written distributed functions for specific sparse tensor algebra expressions and that outperforms general interpretation-based systems by one to two orders of magnitude. © 2022 IEEE.

关键词： Computer Science Programming Parallel Programming

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An Efficient Data Integrity Verification Scheme For distributed Fog computing Architecture 18

An Efficient Data Integrity Verification Scheme For Distribu...

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18th international conference on Wireless and Mobile computing, networking and Communications (WiMob)

作者： Sellami, Youssef Imine, Youcef Gallais, Antoine Univ Polytech Hauts de France Valenciennes LAMIH UMR CNRS 8201 Valenciennes France

ISBN: (数字)9781665469753

ISBN: (纸本)9781665469753

Fog computing is a promising computing paradigm that provides computing services close to end-users at edge of the network. Therefore, it supports large-scale, geographically distributed and latency-sensitive applications. However, due to its untrusty nature, numerous security challenges must be overcome. The integrity verification of the data in fog computing context is one of the main challenges to tackle. Indeed, most of existing solutions consider a centralized data storage context, and usually rely on a trusted third party to check data integrity. However, these approaches are not suitable for fog computing architecture, since the data is stored in a dynamic and a completely distributed manner. Motivated by these challenges, we propose in this paper, a new efficient public verification scheme that protects the integrity of the data in fog computing architecture. Our scheme secures data integrity and authenticity based on the short integer solution SIS problem and the identity-based signatures. In addition, it allows to efficiently verify the integrity of data, even when it is separately shared on multiple servers. This verification can be performed by any end-user on the architecture, and without relying on any trusted third party. Finally, we show through extensive simulation that our solution is highly effective and outperforms existing solutions.

关键词： Data integrity Fog computing Security Lattice-based cryptography distributed networks

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