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检索条件"任意字段=17th International Conference on Distributed Computing and Intelligent Technology"

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Event-Triggered Switched Observers for Networked distributed Multi-Agent Systems via Cloud computing 6

Event-Triggered Switched Observers for Networked Distributed...

引用

6th international conference on Electronic Engineering and Informatics, EEI 2024

作者： Zhang, Chen Ren, Hongru Ma, Hui Zhou, Qi School of Automation Guangdong University of Technology Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China School of Mathematics and Statistics Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9798350353594

this paper designs event-triggered switched observers for the networked distributed multi-agent systems based on the cloud computing systems. Firstly, a novel cloud computing system architecture is designed, in which each group of agents can interact with each others through distributed cloud nodes, and each cloud node also serves as an event-triggered switched observer to observe the topologies of the systems. Secondly, event-triggered switched observers are designed, which can assist distributed agents in accurately obtaining information from the leader, even with continuous switching topologies. then, through stability analysis, we demonstrate the effectiveness of the observers. Finally, we prove the feasibility of the observers through simulation. © 2024 IEEE.

关键词： distributed cloud

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O-RIDE: Open-RAN Innovation and Deployments Exploration 25

O-RIDE: Open-RAN Innovation and Deployments Exploration

引用

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

作者： Kondepu, Koteswararao Tamma, Bheemarjuna Reddy Gudepu, Venkateswarlu Indian Institute of Technology Dharwad Dharwad India Indian Institute of Technology Hyderabad Hyderabad India

ISBN: (纸本)9798400710629

the O-RIDE tutorial aims to provide participants with a comprehensive understanding of building the Open Radio Access Network (Open-RAN) platforms, followed by a demonstration of basic use cases - Key Performance Indicator Monitoring for performance monitoring and Traffic Steering for resource management. Open-RAN disaggregates traditional RAN components, allowing for greater flexibility, vendor neutrality, and innovation in modern telecom networks. the O-RIDE tutorial will showcase the setup and integration of Open-RAN components and their application in real-world scenarios through practical demonstrations, emphasizing hands-on learning and direct application of the technology. Participants will gain an understanding of key concepts in Open-RAN architecture, the role of the RAN intelligent Controller, and practical steps to monitor network performance and dynamically manage traffic. this O-RIDE tutorial suits researchers, students, and professionals interested in next-generation wireless networks. © 2025 Copyright held by the owner/author(s).

关键词： Radio access networks

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A Comparison of distributed Tracing Tools in Serverless Applications 17

A Comparison of Distributed Tracing Tools in Serverless Appl...

引用

17th IEEE international Congress on intelligent and Service-Oriented Systems Engineering (CISOSE)

作者： Eder, Christina Winzinger, Stefan Lichtenthaeler, Robin Univ Bamberg Distributed Syst Grp Bamberg Germany

ISBN: (纸本)9798350322392

Serverless computing can favor the emergence of complex and error-prone applications. In order to gain observability in such applications, distributed tracing can be used. However, as serverless computing relies on the pay-per-use billing model, utilizing distributed tracing tools can have a noticeable impact on the resulting costs. therefore, this paper investigates the impact of distributed tracing in serverless applications by exploring and comparing the efficiency characteristics of three selected distributed tracing tools - Zipkin, OpenTelemetry, and SkyWalking. In particular, the runtime, the memory usage, and the initialization duration were examined by benchmarking AWS Lambda function invocations. In the experiments, Zipkin imposed the lowest runtime overhead with an average of 10.73 %, while SkyWalking introduced the highest overhead with an average runtime overhead of 50.67 %. OpenTelemetry added 24.19% additional runtime. Besides runtime overheads, significantly higher memory usage and initialization durations were detected for all tools. therefore, the results suggest that distributed tracing can significantly impact the efficiency of serverless applications. Nevertheless, differences could be observed concerning tracing mechanisms and use cases. this helps developers to carefully select the most suitable tracing tool considering factors such as runtime overhead, memory usage, and initialization durations.

关键词： distributed Tracing Serverless AWS Lambda Benchmarking

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Decision Making Help during Ultrasonic Inspection of Materials 17

Decision Making Help during Ultrasonic Inspection of Materia...

引用

17th international conference on INnovations in intelligent SysTems and Applications, INISTA 2023

作者： Boudhane, Lakhder Djennah, Mohamed Amine Merazi-Meksen, thouraya University of Science and Technology Houari Boumediene Instrumentation and Contrôl Dept. Usthb Algiers Algeria

ISBN: (纸本)9798350338904

Ultrasonic testing is a type of non-destructive inspection that is widely used in industry to verify the integrity of structures. According to the advancement of technology, automatic methods and algorithms are developed to assist engineers in results *** procedures and the use of robots allow the inspection of larges structures (pipelines, reactor vessels...) consequently, the amount of data to analyze become more and more large and thus too long time consuming.. that is why automating results analyzes and Artificial Intelligence (AI) are mean fields of research in this *** article describes an AI based method to ultrasonic image classification. the objective is to recognize images relatives to defective scanned zones and images corresponding to safe zones. In the first step, image characteristics to apply as inputs to a classifier have to be determined and extracted. Exploiting the Support Vector Machine (SVM) classification models, we classified these images first by implementing the low-level features and then the high-level features. © 2023 IEEE.

关键词： Nondestructive examination

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Assessment and Integration of Relational Databases, Big Data, and Cloud computing in Financial Institutions: Performance Comparison 18

Assessment and Integration of Relational Databases, Big Data...

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18th international conference on Innovations in intelligent Systems and Applications (INISTA)

作者： Ionescu, Sergiu-Alexandru Radu, Andreea-Oana Univ Econ Studies Dept Econ Informat & Cybernet Bucharest 010374 Romania

ISBN: (纸本)9798350368130

Adept data management, as well as analysis, hold an increasing significant role in fast progressing filed of financial modeling. this paper is based on major elements such as relational databases, big data and cloud computing, each of them is presented from a perspective concerning financial modeling. the proposed solution is based on our investigation into the usability of each technology, optimal contexts for their application, and the methods for effectively interconnecting them. Each element is described in terms of operational efficiency, integration and overall performance, with machine learning techniques as means of assessment. Besides the thorough presentation of these technologies, the paper includes an analysis of their implementation so as to improve financial modeling of financial institutions. the interconnectivity and the correct utilization of the application of this technologies may prove of utmost importance because of relational databases, big data, and cloud computing, which represent major data-driven elements for the business environment.

关键词： Data Management Technologies Artificial Intelligence Decision Support Cloud computing Hadoop Spark

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Intent-based Management for the distributed computing Continuum 17

Intent-based Management for the Distributed Computing Contin...

引用

17th IEEE international Congress on intelligent and Service-Oriented Systems Engineering (CISOSE)

作者： Morichetta, Andrea Spring, Nikolaus Raith, Philipp Dustdar, Schahram TU Wien Distributed Syst Grp Vienna Austria

ISBN: (纸本)9798350322392

Managing digital and connected systems has become increasingly challenging in the past decade due to their scale and complexity. A new perspective is required to manage these systems, considering the infrastructure and components from edge to cloud, i.e., in the distributed computing continuum. Serverless computing offers improved scalability and cost efficiency, but balancing and coordinating serverless systems remain complex. Intent-based systems, popular in networking, can provide a solution by translating stakeholder inputs into actions that meet Service Level Objectives (SLOs). their application in the computing continuum can be highly beneficial, but it has yet to be deeply explored. To bridge this gap, we propose a methodology for deploying an intent-based system for the computing continuum. We implement an architectural framework leveraging the serverless paradigm. Furthermore, we focus on defining and implementing the main components for translating the management requirements into actions executed by serverless functions inspired by a threelayer model. through a Proof of Concept (PoC) deployed in Amazon's AWS cloud and detailed simulations, we showcase how such an approach can resolve conflicts in a complex system, i.e., balancing efficiency and availability. Our work aims to contribute to effectively managing the computing continuum and highlight the potential of intent-based systems in this domain. the experiments' results show our framework's ability to make appropriate scaling decisions, fulfilling both objectives.

关键词： computing continuum intents PoC serverless SLO

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Self-Optimizing distributed Cloud computing with Dynamic Neural Resource Allocation and Fault-Tolerant Multi-Agent Systems 4

Self-Optimizing Distributed Cloud Computing with Dynamic Neu...

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4th international conference on Ubiquitous computing and intelligent Information Systems, ICUIS 2024

作者： Tripura, N. Divya, P. Chaganti, Koushik Reddy Rao, Kota Venkateswara Rajyalakshmi, P. Naresh, P. Vignan Institute of Technology And Science Dept of Mba Hyderabad India University of the Cumberlands Dept. of Computer and Information Systems KY United States Andhra Loyola Institute of Engineering and Technology Dept of Cse Vijayawada India Tkr College of Engineering and Technology Dept of Cse Hyderabad India Dayananda Sagar University Dept of Cse Bangalore India

ISBN: (纸本)9798331529635

the exponential growth of distributed cloud systems necessitates an intelligent form of workload management that ensures optimum performance, scalability, and reliability. Traditional approaches based on static or heuristic resource allocation and fault-tolerance mechanisms cannot capture the dynamic nature of modern workloads and heterogeneous infrastructures. Drawing from this source of inspiration, this work develops a holistic framework integrating machine learning models that facilitate self-optimizing distributed cloud computing for dynamic workload management. three components are significant in the proposed framework: (1) DNRA;this uses a hybrid GNN and RL architecture for real-time resource allocation, offering up to 25% improvement in resource utilization and a 30% reduction in task latency. (2) Workload-Aware Transfer Learning Scheduler (WATLS), leveraging transfer learning to predict workload dynamics across heterogeneous nodes, achieving 20% higher task throughput and 15% energy savings through proactive scheduling. (3) Multi-Agent Predictive Fault-Tolerant System (MAP-FTS), combining multi-agent systems with predictive fault detection to preemptively redistribute tasks and schedule maintenance, reducing system downtime by 50% and enhancing fault detection accuracy to 90%. the framework integrates novel methodologies towards answering the main challenges of resource allocation, workload prediction, and fault tolerance. the amount of progress achieved through cumulative contributions includes improvement in system reliability and scalability up to 5x their nodes and respective scalable energy efficiency without any degradation of performance. this work paves the pathway for an adaptive and intelligent next generation of distributed cloud systems. © 2024 IEEE.

关键词： distributed cloud

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Self-supervised Learning for Fine-grained Ethnicity Classification under Limited Labeled Data 17

Self-supervised Learning for Fine-grained Ethnicity Classifi...

引用

17th IEEE international conference on Automatic Face and Gesture Recognition, FG 2023

作者： Li, Kunyan Zhang, Jie Shan, Shiguang Institute of Computing Technology Cas Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Institute of Intelligent Computing Technology Cas Suzhou China

ISBN: (纸本)9798350345445

Human faces are always determined by genes and other external causes, such as geographical environment, which makes it possible for us to predict ethnicity according to the faces. However, it remains a challenging task due to the tiny differences in faces for various ethnicities, which is hard for human beings to tell, especially for ethnicities on the same continent, e.g., East Asia. Although some strongly-supervised methods have demonstrated their feasibility in this task, they cease to be effective when suffering from data-hungry issues in practice. this paper proposes a novel self-supervised model with a polynomial stacked attention mechanism to well excavate distinctions across different nations under limited labeled data. And we also construct a new ethnicity dataset named Cupid which observably extends the scale and categories of ethnic data compared to the existing datasets. Extensive experiments confirm that our method achieves the state-of-the-art results on both the Asian Face dataset and our proposed Cupid dataset. © 2023 IEEE.

关键词： Supervised learning

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DyPSS: Dynamic Priority Signalling System for Emergency Vehicles using Fog and YOLOv8 17

DyPSS: Dynamic Priority Signalling System for Emergency Vehi...

引用

17th international conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Kakde, Anuj Nath, Shubha Brata Ghosh, Soumya K. Indian Institute of Technology Department of Computer Science and Engineering Kharagpur India Indian Institute of Information Technology Department of Computer Science and Engineering Guwahati India

ISBN: (纸本)9798331531195

Efficient navigation of emergency response vehicles (ERVs) through urban congestion is crucial to life-saving efforts, yet traditional traffic systems often slow down their swift passage. In this work, we introduce Dynamic Priority Signalling System (DyPSS), an intelligent, multi-layered traffic management solution designed to minimize ERV delays by creating "green corridors"at traffic signals. Using technologies like fog computing, cloud computing, global positioning system and deep learning, DyPSS adjusts traffic lights instantly to clear congestion as an ERV approaches. Simulation testing was conducted using SUMO and it demonstrated DyPSS's potential to significantly reduce ERV travel time in dense urban settings with minimal disruption to general traffic flow. this system could drastically improve emergency response by reducing delays and helping responders reach their destinations faster, potentially saving more lives. © 2025 IEEE.

关键词： Emergency vehicles

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Optimal Dispersion in Triangular Grids: Achieving Efficiency Without Prior Knowledge 21st

Optimal Dispersion in Triangular Grids: Achieving Efficiency...

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21st international conference on distributed computing and intelligent technology

作者： Pandit, Himani Pandit, Supantha Dhirubhai Ambani Inst Informat & Commun Technol Gandhinagar Gujarat India

ISBN: (纸本)9783031814037;9783031814044

In the dispersion problem, a group of k <= n mobile robots, initially placed on the vertices of an anonymous graph G with n vertices, must redistribute themselves so that each vertex hosts no more than one robot. We address this challenge on an anonymous triangular grid graph, where each vertex can connect to up to six adjacent vertices. We propose a distributed deterministic algorithm that achieves dispersion on an unoriented triangular grid graph in O(root n) time, where n is the number of vertices. Each robot requires O(log n) bits of memory. the time complexity of our algorithm and the memory usage per robot are optimal. this work builds on previous studies by Kshemkalyani et al. [WALCOM 2020 [17]] and Banerjee et al. [ALGOWIN 2024 [3]]. Importantly, our algorithm terminates without requiring prior knowledge of n and resolves a question posed by Banerjee et al. [ALGOWIN 2024 [3]].

关键词： distributed algorithms Mobile robots Dispersion Triangular grid Deterministic algorithms

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