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检索条件"任意字段=14th International Conference on Parallel and Distributed Computing Systems"

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Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning 44

Communication-Efficient Training Workload Balancing for Dece...

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44th IEEE international conference on distributed computing systems (ICDCS)

作者： Mohammadabadi, Seyed Mahmoud Sajjadi Yang, Lei Yan, Feng Zhang, Junshan Univ Nevada Dept Comp Sci & Engn Reno NV 89557 USA Univ Houston Dept Comp Sci Houston TX 77204 USA Univ Calif Davis Dept Elect & Comp Engn Davis CA USA

ISBN: (纸本)9798350386066;9798350386059

Decentralized Multi-agent Learning (DML) enables collaborative model training while preserving data privacy. However, inherent heterogeneity in agents' resources (computation, communication, and task size) may lead to substantial variations in training time. this heterogeneity creates a bottleneck, lengthening the overall training time due to straggler effects and potentially wasting spare resources of faster agents. To minimize training time in heterogeneous environments, we present a Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning (ComDML), which balances the workload among agents through a decentralized approach. Leveraging local-loss split training, ComDML enables parallel updates, where slower agents offload part of their workload to faster agents. To minimize the overall training time, ComDML optimizes the workload balancing by jointly considering the communication and computation capacities of agents, which hinges upon integer programming. A dynamic decentralized pairing scheduler is developed to efficiently pair agents and determine optimal offloading amounts. We prove that in ComDML, both slower and faster agents' models converge, for convex and non-convex functions. Furthermore, extensive experimental results on popular datasets (CIFAR-10, CIFAR-100, and CINIC-10) and their non-I.I.D. variants, with large models such as ResNet-56 and ResNet-110, demonstrate that ComDML can significantly reduce the overall training time while maintaining model accuracy, compared to state-of-the-art methods. ComDML demonstrates robustness in heterogeneous environments, and privacy measures can be seamlessly integrated for enhanced data protection.

关键词： decentralized multi-agent learning federated learning edge computing heterogeneous agents workload balancing communication-efficient training

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A Fast Belief Propagation-Based distributed Gauss-Newton Method for Power System State Estimation 8

A Fast Belief Propagation-Based Distributed Gauss-Newton Met...

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8th international conference on Cloud computing and Big Data Analytics (ICCCBDA)

作者： Guo, Peng Shi, Danni Wang, Xuan Shi, Xinghua State Grid Smart Grid Res Inst Co Ltd State Grid Lab Grid Adv Comp & Applicat Beijing 102209 Peoples R China State Grid Smart Grid Res Inst Co Ltd Zhejiang 310007 Peoples R China

ISBN: (纸本)9781665455336

State estimation is the foundation for a variety of online power system applications in energy management systems, and the stability of power systems is directly impacted by the speed with which current system states can be obtained through state estimation. this paper proposed a fast Gaussian-Newton state estimation method for power systems based on parallel belief propagation, which implements the Gaussian belief process via multi-core and multi-thread parallel computation to achieve efficient state estimation. Simulation findings on numerous IEEE-standard power systems show that the suggested technique outperforms the traditional algorithm.

关键词： Gauss-Newton state estimation factor graphs belief propagation parallel computing

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Security threat detection performance analysis of a distributed architecture WSN 19

Security threat detection performance analysis of a distribu...

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19th international conference on Future Networks and Communications, FNC 2024 / 21st international conference on Mobile systems and Pervasive computing, MobiSPC 2024 / 14th international conference on Sustainable Energy Information Technology, SEIT 2024

作者： Arreaga, Nestor X. Estrada, Rebeca Blanc, Sara Noboa, Andres Vera, Nelson ESPOL Polytechnic University Escuela Superior Politecnica del Litoral Campus Gustavo Galindo Km. 30.5 Via Perimetral Guayaquil090902 Ecuador ITACA Universitat Politecnica de Valencia Camino de Vera s/n Valencia Valencia46022 Spain

IoT technologies are becoming more and more common in our daily activities because the networks they create are capable of collecting information, monitoring and controlling remotely. However, these devices are not exempt from security attacks, as they become vulnerable entry points to data networks. the use of traditional methods to secure networks (e.g., Next Generation Firewalls (NGFW), encryption, etc.) is not recommended because the devices used in this type of network are limited in terms of computing power and storage availability (e.g., nodeMCU). In this paper, we propose to design two intrusion detection systems in embedded systems using machine learning (ML) algorithms, Artificial Neural Networks and K-means. In a distributed architecture Wireless Sensor Network scenario (WSN), we evaluate their performance in terms of connection and response times, detection accuracy and intruder detection time. Simulation results show that both models are able to find irregularities in network traffic within milliseconds. © 2024 the Authors. Published by Elsevier B.V.

关键词： Network intrusion

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Enhancing Cloud computing Security through Blockchain-Based Communication for Electronic Health Records 20

Enhancing Cloud Computing Security Through Blockchain-Based ...

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

作者： Noyon, Md Shahed Islam Moradpoor, Naghmeh Maglaras, Leandros Ahmad, Jawad Univ Greenwich Sch Comp & Math Sci London England Edinburgh Napier Univ Sch Comp Engn & Built Environm Edinburgh Midlothian Scotland

ISBN: (纸本)9798350369458;9798350369441

the health sector stands as one of the most crucial and vulnerable domains, harbouring extensive personal data. Particularly, Electronic Health Records store information in electronic media where users lack control over their data. Unauthorized access to the server or record portal could lead to data manipulation across the entire database. Addressing this security concern, blockchain emerges as a potential solution, surpassing traditional systems in data storage capabilities. In the event of unauthorized access, an attacker can only manipulate a single block of data, leaving the remaining information protected. In addition, blockchain offers new opportunities and avenues for research, particularly in terms of security and scalability. the proposed system in this paper, MediRec, aims to ensure that users have complete control over their personal data by employing a decentralized database. this database securely stores and restricts access to data, allowing only the owner to share it using a secure key. MediRec facilitates patients in creating blockchain-based accounts, ensuring each individual possesses a dedicated block for storing personal data. this innovative approach enables patients to schedule appointments, and doctors can prescribe medications, with details and e -prescriptions securely stored within the patient's block. To maintain the integrity of the system, doctors can undergo verification by healthcare services, such as the National Health Service in the UK, ensuring their validation before accessing the blockchain system. this stringent validation process ensures the security and authenticity of the data stored within the blockchain. Overall, the proposed solution in this paper offers robust security and scalability in electronic data storage, providing users with control over their information through a blockchain-based system. this system presents a promising solution in preventing data breaches and safeguarding sensitive healthcare information.

关键词： Keywords DApps Ethereal'' Encryption Decentralized Health Records Smarr Contact

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SCoOL - Scalable Common Optimization Library 30

SCoOL - Scalable Common Optimization Library

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30th international conference on High Performance computing, Data, and Analytics (HiPC)

作者： Sayed, Zainul Abideen Zola, Jaroslaw Univ Buffalo Buffalo NY 14260 USA

ISBN: (纸本)9798350383225

We propose SCoOL, a programming model and its corresponding parallel runtime systems for implementing optimization problem solvers. In SCoOL, users specify what task is performed for a point in a given search space, and what global information should be maintained during the search. the resulting optimization program is then efficiently executed in a BSP-style on a shared or distributed memory computers by a parallel runtime provided with the model. In the paper, we show details of our scalable runtime for distributed memory clusters, including algorithms for work stealing and tasks rebalancing. To benchmark the platform, we implement solutions to several optimization problems and provide performance analysis for Quadratic Assignment Problem, Parent Set Assignment, and Bayesian Networks Structure Learning. Our solvers show strong scaling on a cluster with 1,280 cores, significantly outperforming the current state-of-the-art solvers in Bayesian networks learning.

关键词： parallel programming model runtime system optimization problems

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Optimization Strategies for Data Placement in Satellite Cloud-oriented distributed File systems 14

Optimization Strategies for Data Placement in Satellite Clou...

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IEEE 14th international conference on Joint Cloud computing (JCC)

作者： Zhang, Ying Wo, Tianyu Fan, Kun Ye, Tianyu Zhang, Jiwei Zhang, Junhua Feng, Xiao Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp BDB Beijing Peoples R China China Elect Technol Taiji Grp Corp Ltd Beijing Peoples R China

ISBN: (纸本)9798350328554

Forming a collaborative computing network among the deployed satellites in space can process data rapidly and reduce data transmission delay by leveraging the communication, storage, and computing capacities of the satellites. Due to the dynamics of satellite orbits, the distance between satellites varies over time, bringing new challenges to the designing of dedicated distributed file systems for collaborative satellites. Traditional distributed file systems did not consider the network topology and dynamics of satellite clouds and the limited computing resources of satellite node cores. In view of the torus network topology of satellite clouds, we design a highly available distributed metadata management mechanism for satellite clouds to ensure efficient metadata reading and reliability. On this basis, a topology-aware replica placement strategy is proposed to minimize communication costs and energy consumption for replica placement. Based on the metadata strategy and replica placement strategy mentioned above, we design and implement a distributed file system for satellite clouds. Experimental results demonstrate that our proposed placement strategy can improve the data transmission performance of the replica placement by more than double compared to the random placement strategy.

关键词： Satellite Cloud distributed File System Data Placement Optimization Strategies

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ComFaaS distributed: Edge computing with Function-as-a-Service in parallel Cloud Environments 7

ComFaaS Distributed: Edge Computing with Function-as-a-Servi...

引用

7th international conference on Information and Computer Technologies, ICICT 2024

作者： Lee, Jaden Jinu Nava, Judah Lee, Hanku Minnesota State University Moorhead Computer Science And Information Systems MoorheadMN United States

ISBN: (纸本)9798350385625

Function-as-a-Service (FaaS) has emerged as a revolutionary service platform, abstracting the complexities of hardware, operating systems, and web hosting services. this allows developers to focus solely on implementing their service applications, making FaaS an ideal platform for the scalable manipulation of large data sets. Traditionally deployed on the cloud, FaaS now faces a new frontier: the network edge. Leveraging the edge offers several potential benefits, including reduced latency and improved resource utilization, making it a promising approach for efficient FaaS deployment. As the daily volume and complexity of data we handle continues to grow, adopting a parallel computing paradigm has become increasingly important to ensure fast and efficient execution of computational tasks. Addressing this need, ComFaaS distributed embarks on a comprehensive comparison of the capabilities of parallelized edge and cloud environments for FaaS deployment. Utilizing benchmark programs meticulously crafted to simulate event-triggered scenarios, ComFaaS distributed aims to provide valuable insights into the performance and potential of FaaS at the edge, paving the way for a future where parallel computing empowers the efficient and scalable processing of ever-growing data volumes. © 2024 IEEE.

关键词： Edge computing

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TAPS: A Performance Evaluation Suite for Task-based Execution Frameworks 20

TAPS: A Performance Evaluation Suite for Task-based Executio...

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20th IEEE international conference on E-Science (E-Science)

作者： Pauloski, J. Gregory Hayot-Sasson, Valerie Gonthier, Maxime Hudson, Nathaniel Pan, Haochen Zhou, Sicheng Foster, Ian Chard, Kyle Univ Chicago Dept Comp Sci Chicago IL 60637 USA Argonne Natl Lab Data Sci & Learning Div Lemont IL 60439 USA

ISBN: (纸本)9798350365627;9798350365610

Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a computational goal and abstract the parallel and distributed execution of those tasks on arbitrary hardware. Research into these task executors has accelerated as computational sciences increasingly need to take advantage of parallel compute and/or heterogeneous hardware. However, the lack of evaluation standards makes it challenging to compare and contrast novel systems against existing implementations. Here, we introduce TAPS, the Task Performance Suite, to support continued research in distributed task executor frameworks. TAPS provides (1) a unified, modular interface for writing and evaluating applications using arbitrary execution frameworks and data management systems and (2) an initial set of reference synthetic and real-world science applications. We discuss how the design of TAPS supports the reliable evaluation of frameworks and demonstrate TAPS through a survey of benchmarks using the provided reference applications.

关键词： Performance Evaluation parallel computing Open-Source Python Workflows

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Unit Test Framework for distributed Unit Manager (DUMGR) of 5G RAN 14

Unit Test Framework for Distributed Unit Manager (DUMGR) of ...

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

作者： Suman, Madhumati Patil, Rajendrakumar Kotoju, Rajesh Coep Technological University Department of Electronics & Telecommunication Engineering Pune India Parallel Wireless India Pvt. Ltd Banglore India

ISBN: (纸本)9798350335095

the three main parts of 5G wireless systems, commonly referred to as 5G New Radio technology, are user equipment, access side, and core side. the Open Radio Access Network (O-RAN) is designed to enable the Next Generation-RAN, which is a crucial component for providing wireless connectivity through a radio link between devices and the core network. the Radio Unit, Centralised Unit, and distributed Unit make up the *** project focuses on developing a Unit Test Framework for DU MGR (DU Manager) and creating stubs or simulators that can replace the actual implementation of a component during testing using C language. For instance, we have developed CU stub, RLC stub, MAC stub, DUOAM stub and F1U stub to simulate the behavior of the components that DU MGR interacts with. By using these stubs, we aimed to validate the functionality of DU MGR, which is our Device under Test (DUT). We verified the cell bring-up, UE attach call flows of 5G and negative scenarios possible through writing test *** project has used the "VS Code"editor to write code in the C language. Also, we used Jenkins CI/CD to develop and run tests for our code. the "MobaXterm"application was used to execute and repeat testing suites and to verify logs for debugging purposes. © 2023 IEEE.

关键词： C (programming language)

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Uncertainty Estimation in Multi-Agent distributed Learning for AI-Enabled Edge Devices 14

Uncertainty Estimation in Multi-Agent Distributed Learning f...

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14th international conference on Cloud computing and Services Science, CLOSER 2024

作者： Radchenko, Gleb Fill, Victoria Andrea Silicon Austria Labs Sandgasse 34 Graz8010 Austria FH Joanneum Alte Poststraße 149 Graz8020 Austria

ISBN: (纸本)9789897587016

Edge IoT devices, once seen as low-power units with limited processing, have evolved with introduction of FPGAs and AI accelerators, significantly boosting their computational power for edge AI. this leads to new challenges in optimizing AI for energy and network resource constraints in edge computing. Our study examines methods for distributed data processing with AI-enabled edge devices to improve collaborative learning. We focus on the challenge of assessing confidence in learning outcomes amid data variability faced by agents. To address this issue, we investigate the application of Bayesian neural networks, proposing a novel approach to manage uncertainty in distributed learning environments. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Edge computing

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