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检索条件"任意字段=22nd International Conference on Distributed Computing Systems"

共 2924 条记录，以下是41-50 订阅

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Retrieval-Augmented Generation Powered by a Multi-agent System to Assisted the Operation of Industries 22nd

Retrieval-Augmented Generation Powered by a Multi-agent Syst...

引用

22nd international conference on Practical Applications of Agents and Multi-Agent systems, PAAMS 2024

作者： Oliveira, Francisco Gomes, Luis Vale, Zita GECAD – Research Group on Intelligent Engineering and Computing for Advancement Innovation and Development Polytechnic of Porto Porto Portugal LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

ISBN: (纸本)9783031704147

The introduction of large language models in recent years transformed the use of artificial intelligence in our daily life, making it available to common users and allowing them to interact with natural language processing machines. However, the common and general knowledge of large language models is not reliable when it comes to the quality of the response and its veracity. The proposed work integrates the use of retrieval-augmented generation with large language models with a multi-agent system framework to enable the creation of trees of knowledge where multiple agents have domain specific knowledge. The proposed agent-based solution was tested in a realistic case study where multiple knowledge domains are distributed amongst six different agents. The case study evaluates the capacity of agents to delegate questions according to its topics and the capacity of correctly replying to questions. The results are promising, demonstrating the ability of large language models to assess and process information that wasn’t used in its training process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Natural language processing systems

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TrustMesh: A Blockchain-Enabled Trusted distributed computing Framework for Open Heterogeneous IoT Environments

TrustMesh: A Blockchain-Enabled Trusted Distributed Computin...

引用

Working IEEE/IFIP conference on Software Architecture

作者： Murtaza Rangwala Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory School of Computing and Information Systems The University of Melbourne Australia

ISBN: (数字)9798331520908

ISBN: (纸本)9798331520915

The rapid evolution of Internet of Things (IoT) environments has created an urgent need for secure and trust-worthy distributed computing systems, particularly when dealing with heterogeneous devices and applications where centralized trust cannot be assumed. This paper proposes TrustMesh, a novel blockchain-enabled framework that addresses these challenges through a unique three-layer architecture combining permissioned blockchain technology with a novel multi-phase Practical Byzantine Fault Tolerance (PBFT) consensus protocol. The key innovation lies in TrustMesh’s ability to support non-deterministic scheduling algorithms while maintaining Byzantine fault tolerance, features traditionally considered mutually exclusive in blockchain systems. The framework supports a sophisticated resource management approach that enables flexible scheduling decisions while preserving the security guarantees of blockchain-based verification. Our experimental evaluation using a real-world cold chain monitoring scenario demonstrates that TrustMesh successfully maintains Byzantine fault tolerance with fault detection latencies under 150 milliseconds, while maintaining consistent framework overhead across varying computational workloads even with network scaling. These results establish TrustMesh’s effectiveness in balancing security, performance, and flexibility requirements in trustless IoT environments, advancing the state-of-the-art in secure distributed computing frameworks.

关键词： Fault tolerance Trusted computing Technological innovation Software architecture Scheduling algorithms Fault tolerant systems Trustless services Internet of Things Security Resource management

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Proceedings of the 1996 22nd international conference for the Resource Management & Performance Evaluation of Enterprise computing systems, CMG. Part 1 (of 2)

Proceedings of the 1996 22nd International Conference for th...

引用

Proceedings of the 1996 22nd international conference for the Resource Management & Performance Evaluation of Enterprise computing systems, CMG. Part 1 (of 2)

The papers submitted to the 22nd international conference for the Resource Management and Performance Evaluation of Enterprise computing systems are presented. The main issues and items considered at the conference include performance monitoring and capacity planning, resource allocation management, Internet payment systems, 32-bit application performance, simulation models, Client/Server systems, LAN/WAN networks, workload CPU, transaction routing, tape performance tools, Sysplex, Web service, benchmarking, hybrid tape subsystems, parallel applications, distributed computers, database allocation, analytical modeling.

关键词： Computer systems

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Benchmarking Large Language Models for Multi-agent systems: A Comparative Analysis of AutoGen, CrewAI, and TaskWeaver 22nd

Benchmarking Large Language Models for Multi-agent Systems: ...

引用

22nd international conference on Practical Applications of Agents and Multi-Agent systems, PAAMS 2024

作者： Barbarroxa, Rafael Gomes, Luis Vale, Zita GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4249-015 Portugal

ISBN: (纸本)9783031704147

This paper presents the benchmarking of three multi-agent systems powered by large language models. The paper presents a comparative analysis of AutoGen, CrewAI, and TaskWeaver. Nowadays, large language models have emerged as powerful tools able to assist users in various areas. The integration of large language models into multi-agent systems increases their potential for collaborative problem-solving. This study focuses on a case study involving a machine learning code generation task which is used to evaluate the framework’s performance. To assess the performance of the solutions, it is requested to create energy forecasting models using the same dataset as the base. After producing the code, a new dataset is used to test the model performance using the root mean square error. The three solutions were able to provide results using multiple large language models. The best result was achieved by TaskWeaver using GPT-3.5, with an error of 25.04. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Multi agent systems

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Network Anomaly Detection in distributed Edge computing Infrastructure

Network Anomaly Detection in Distributed Edge Computing Infr...

引用

Consumer Communications and Networking conference, CCNC IEEE

作者： William Marfo Enrique A. Rico Deepak K. Tosh Shirley V. Moore Department of Computer Science University of Texas at El Paso El Paso USA

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

As networks continue to grow in complexity and scale, detecting anomalies has become increasingly challenging, particularly in diverse and geographically dispersed environments. Traditional approaches often struggle with managing the computational burden associated with analyzing large-scale network traffic to identify anomalies. This paper introduces a distributed edge computing framework that integrates federated learning with Apache Spark and Kubernetes to address these challenges. We hypothesize that our approach, which enables collaborative model training across distributed nodes, significantly enhances the detection accuracy of network anomalies across different network types. We show that by leveraging distributed computing and containerization technologies, our framework not only improves scalability and fault tolerance but also achieves superior detection performance compared to state-of-the-art methods. Extensive experiments on the UNSW-NB15 and ROAD datasets validate the effectiveness of our approach, demonstrating statistically significant improvements in detection accuracy and training efficiency over baseline models, as confirmed by MannWhitney U and Kolmogorov-Smirnov tests $(p<0.05)$ .

关键词： Training Fault tolerance Accuracy Federated learning Roads Scalability Computational modeling Fault tolerant systems Anomaly detection Edge computing

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Proceedings - DMS 2016: 22nd international conference on distributed Multimedia systems

Proceedings - DMS 2016: 22nd International Conference on Dis...

引用

22nd international conference on distributed Multimedia systems, DMS 2016

ISBN: (纸本)1891706403

The proceedings contain 29 papers. The topics discussed include: recommender systems and social networks: an application in cultural heritage;a toolkit for knot diagram sketching, encoding and re-generation;visualizing student engagement in e-learning environment;supporting mobile development project-based learning by software project and product measures;towards formal multimodal analysis of emotions for affective computing;a toolkit for knot diagram sketching, encoding and re-generation;is e-learning ready for big data? and how big data would be useful to e-learning? recommender systems and social networks: an application in cultural heritage;scaffolding version control into the computer science curriculum;and supporting mobile development project-based learning by software project and product measures.

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Towards Implementation of Privacy-Preserving Federated Learning Aggregation Using Multi-key Homomorphic Encryption

Towards Implementation of Privacy-Preserving Federated Lear...

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25th international conference on Internet computing and IoT, ICOMP 2024, and 22nd international conference on Embedded systems, Cyber-physical systems, and Applications, ESCS 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

作者： Boudko, Svetlana Norwegian Computing Center Oslo Norway

ISBN: (纸本)9783031859229

Federated Learning is a machine learning approach where a model is trained across multiple decentralized edge devices. Since the data are not uploaded to a server, this approach is particularly useful for data protection and efficient computation. Further, it can be combined with privacy-preserving technologies, e.g., homomorphic encryption for enhanced data protection. Considering all these elements, a practical solution will require an efficient multikey homomorphic encryption as well as an effective integration of federated model aggregation and multikey generation processes. The paper studies the related work for homomorphic encryption in the context of federated learning and outlines the rationale behind practical design of secure federated learning. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： distributed computer systems

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Proceedings of the 1996 22nd international conference for the Resource Management & Performance Evaluation of Enterprise computing systems, CMG. Part 2 (of 2)

Proceedings of the 1996 22nd International Conference for th...

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Proceedings of the 1996 22nd international conference for the Resource Management & Performance Evaluation of Enterprise computing systems, CMG. Part 2 (of 2)

The proceedings contains 56 papers. Topics discussed include distributed network management, client server systems, data sharing, capacity planning, information technology service management, benchmarking, parallel computer performance, object oriented method to performance management, enterprise resource management, software engineering, world wide web sites, CMOS technology, UNIX performance management, multibreading processors.

关键词： Information technology

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Proceedings - 2020 IEEE 22nd international conference on High Performance computing and Communications, IEEE 18th international conference on Smart City and IEEE 6th international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

Proceedings - 2020 IEEE 22nd International Conference on Hig...

引用

22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

ISBN: (纸本)9781728176499

The proceedings contain 183 papers. The topics discussed include: design of direct read from sparse segments in MPI-IO;descriptive and predictive analysis of aggregating functions in serverless clouds: the case of video streaming;a proactive uncertainty driven model for data synopses management in pervasive applications;on-line traffic scheduling optimization in IEEE 802.1Qch based time-sensitive networks;multi-layer and heterogeneous resource management in SDN-based space-terrestrial integrated networks;structure preserved graph reordering for fast graph processing without the pain;an efficient approach to vectorize the hybrid breadth-first search;a novel developer portrait model based on Bert-capsule network;job placement strategy with opportunistic resource sharing for distributed deep learning clusters;and batched pattern-aware cache management strategy for astronomical time series sub-images retrieval.

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Balancing computing and Networking in Autonomous Edge Clouds

Balancing Computing and Networking in Autonomous Edge Clouds

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Consumer Communications and Networking conference, CCNC IEEE

作者： Shinnosuke Masuda Tsuyoshi Hasegawa Kazuyuki Shudo Kenjiro Cho Kyoto University IIJ

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

In the ever-changing environment of edge cloud systems, it is necessary to allocate diverse cloud resources in an efficient manner, at the same time, reducing energy consumption. A simple distributed resource allocation model is proposed in a previous study that utilizes a pseudo cost function of resource load, and it is shown that a convex function allows energy saving by pooling idle edge servers. In this paper, we extend this cost model beyond simple load, and present a method to balance computation and communication by merging multiple constraints into the cost function. We show trade-offs among soft constraints along with energy saving effects by simulation, using specific scenarios with computational and communication constraints. Our simulation results show that the combination of a convex function with a polynomial penalty function works well for balancing energy saving and other soft constraints.

关键词： Computational modeling Simulation Energy conservation Cost function Convex functions Polynomials Resource management Servers Load modeling Edge computing

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