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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30762 条记录，以下是531-540 订阅

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Assessing the Linguistic Design Quality of APIs of distributed systems and Microservices 34

Assessing the Linguistic Design Quality of APIs of Distribut...

引用

34th Annual international conference on Collaborative Advances in Software and computing, CASCON 2024

作者： Dey, Krishno Cao, Hung Palma, Francis University of New Brunswick SE+AI Research Lab Faculty of Computer Science NB Canada University of New Brunswick Analytics Everywhere Lab Faculty of Computer Science NB Canada

ISBN: (纸本)9798331504830

APIs or Application Programming Interfaces help distributed systems and microservices to expose their functionalities and serve as a means for communication among them. In contrast to a poorly designed API, a well-designed API is easy for users to understand and use. Thus, APIs with high-quality design are essential both for API providers and client developers. This paper aims to assess the linguistic design quality of APIs in distributed systems and microservices by automatically detecting good and poor design practices, commonly known as patterns and antipatterns, respectively. We rely on syntactic and semantic analyses for automatic assessment of the design quality of APIs using detection heuristics. Syntactic analysis involves analyzing the structure and syntax of the APIs, while semantic analysis involves analyzing API documentation, descriptions, and parameters. We achieved an overall accuracy of more than 93% in detecting patterns and antipatterns. Our detection results also suggest that antipatterns are prevalent in the APIs of distributed systems and microservices. Our findings will assist API developers in identifying poor design practices and improving the design quality of their APIs. © 2024 ieee.

关键词： APIs distributed systems GraphQL Linguistic Design Quality Microservices NLP REST Semantic Analysis

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QEdgeProxy: QoS-Aware Load Balancing for IoT Services in the computing Continuum 8

QEdgeProxy: QoS-Aware Load Balancing for IoT Services in the...

引用

8th ieee international conference on Edge computing and Communications, EDGE 2024

作者： Cilic, Ivan Jukanovic, Valentin Zarko, Ivana Podnar Frangoudis, Pantelis Dustdar, Schahram University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia Distributed Systems Group TU Wien Vienna Austria

ISBN: (纸本)9798350368499

While various service orchestration aspects within computing Continuum (CC) systems have been extensively addressed, including service placement, replication, and scheduling, an open challenge lies in ensuring uninterrupted data delivery from IoT devices to running service instances in this dynamic environment, while adhering to specific Quality of Service (QoS) requirements and balancing the load on service instances. To address this challenge, we introduce QEdgeProxy, an adaptive and QoS-aware load balancing framework specifically designed for routing client requests to appropriate IoT service instances in the CC. QEdgeProxy integrates naturally within Kubernetes, adapts to changes in dynamic environments, and manages to seamlessly deliver data to IoT service instances while consistently meeting QoS requirements and effectively distributing load across them. This is verified by extensive experiments over a realistic K3s cluster with instance failures and network variability, where QEdgeProxy outperforms both Kubernetes built-in mechanisms and a state-of-the-art solution, while introducing minimal computational overhead. © 2024 ieee.

关键词： Edge computing

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Refining Automation in Power Dispatching systems: A Cloud Optimization Investigation 7

Refining Automation in Power Dispatching Systems: A Cloud Op...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Zhang, Chi Zeng, Ciling Zeng, Weiwei Changsha University of Science And Technology International Institute of Technology Changsha410114 China State Grid Hunan Electric Power Company Changsha410004 China Beijing Kedong Electric Power Control System Co.Ltd. Beijing100192 China

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359299

Efficiency in power dispatch systems is critical to ensure as it depends on the optimal resource utilization and maintaining grid stability. As power systems evolve into data-intensive environments, traditional centralized computing platforms are challenged to efficiently process information. To address this, the use of distributed computing and storage technologies is developed. In addition, the integration of advanced technologies such as cloud computing, artificial intelligence, and big data analytics can further enhance the performance and scalability of power dispatching systems. This study investigates the application of cloud optimization techniques in refining automation within power dispatching systems. Specifically, it explores the integration of cloud computing technology to improve data processing algorithms and efficiency challenges in power grid systems. Through a proposed methodology that incorporates a distributed data service bus, massive data storage systems, and dynamic load balancing mechanisms, the study aims to improve system reliability, real-time responsiveness, and accuracy. In addition, the study discusses the optimization of real-time load forecasting and dispatching strategies using time series analysis, statistical methods, and emerging machine learning techniques. The effectiveness of the proposed approach is demonstrated through simulation and verification, highlighting the improved system efficiency and reliability achieved through cloud optimization in power dispatching systems. © 2024 ieee.

关键词： Efficiency

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The Evolutionary Logic from DIKW to DIKWP, and then to Platform Economy DIKICRWPIP 25

The Evolutionary Logic from DIKW to DIKWP, and then to Platf...

引用

25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Dou, Erxiang Cheng, Ailiu Duan, Yucong Mei, Yingtian Peking University Beijing China School of Computer Science and Technology Hainan University Haikou China

ISBN: (纸本)9798350330014

DIKW can be regarded as the overall model for human social cognition and transformation of the world. In terms of improving cognitive efficiency and improving transformation accuracy, the DIKWP model is an evolution. The difference between any animal lies in its original purpose. The clearer the purpose P, the more significant the results of cognition and transformation, and the greater the progress of human society. This evolution is also reflected in the evolution of information carriers, as exemplified by the prosperity of the platform economy. The new platform economy has improved the completeness of the platform on the basis of information carrier technology, especially in terms of the three commonalities of the platform, namely fairness, dialectics, and openness. The new platform is more credible. The modern enterprise system will transition to a 'platform + company' system, which is conducive to the formation of a unified domestic and international market and emerging value. © 2023 ieee.

关键词： international trade

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Design and Implementation of a distributed Control Platform for a Smart Building Testbed 23

Design and Implementation of a Distributed Control Platform ...

引用

23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Puryear, Nathan Zaman, Mostafa Eini, Roja Abdelwahed, Sherif Virginia Commonwealth University Department of Electrical and Computer Engineering RichmondVA United States

ISBN: (纸本)9781665494571

One of the leading frontiers of the Internet of Things (IoT) era, smart building systems have made modern homes more innovative, interconnected, and autonomous. The goal of a smart home system is to enhance users' comfort, safety, and efficiency. In this paper, a smart building testbed is designed and constructed as a cyber-physical system that allows testing and validating building control algorithms, communication networks, and user interfaces. The building control unit is responsible for optimizing the performance of testbed actuators (thermal, lighting, and access systems), whereby building parameters are aggregated via a set of distributed sensors and communicated to a management system. This data is observed and analyzed by the control system to produce optimal control commands. The building communication network is developed based on the Message Queuing Telemetry Transport (MQTT) protocol, in which subscribers receive the measurement data, format it, and send it to the user-interface unit. The user interface is implemented in a Node-RED platform, where the data is visualized in real-time, and users are capable of interacting with the automation system. Experimental results demonstrate the usefulness of such a prototype for smart building monitoring and control research. © 2021 ieee.

关键词： Smart buildings Smart homes Thermal sensors Thermal management sensor systems Safety Internet of Things

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2025 ieee 5th international conference on Power, Electronics and Computer Applications, ICPECA 2025

2025 IEEE 5th International Conference on Power, Electronics...

引用

5th ieee international conference on Power, Electronics and Computer Applications, ICPECA 2025

ISBN: (纸本)9798331533694

The proceedings contain 154 papers. The topics discussed include: transient stability analysis of power system considering multiple inverter aggregation model;development of the safeguard companion for secondary safety measures of relay protection;an open interconnection system for computing power based on service mesh;securing distributed power dispatching systems: a framework for cybersecurity and 5G integration;utilizing deep belief networks for power system state estimation and anomaly detection;fire detection approach for 10kV distribution room based on spatial perception and hybrid attention mechanism;research on the application of information sharing technology in distributed photovoltaic aggregation optimization control strategy;and construction and optimization of key quality problem graph of power equipment based on association rule mining.

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Proceedings - 2023 ieee international conference on Parallel and distributed Processing with Applications, Big Data and Cloud computing, Sustainable computing and Communications, Social computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2023

Proceedings - 2023 IEEE International Conference on Parallel...

引用

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

ISBN: (纸本)9798350329223

The proceedings contain 153 papers. The topics discussed include: transaction data management optimization based on multi-partitioning in blockchain systems;semi-asynchronous federated learning optimized for NON-IID data communication based on tensor decomposition;HKTGNN: hierarchical knowledge transferable graph neural network-based supply chain risk assessment;DQR-TTS: semi-supervised text-to-speech synthesis with dynamic quantized representation;deep reinforcement learning-based network moving target defense in DPDK;iNUMAlloc: towards intelligent memory allocation for AI accelerators with NUMA;and predictive queue-based low latency congestion detection in data center networks.

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High-Performance and Low-Cost distributed Acoustic sensor with Phase Noise Compensation

High-Performance and Low-Cost Distributed Acoustic Sensor wi...

引用

2024 Asia Communications and Photonics conference, ACP 2024 and international conference on Information Photonics and Optical Communications, IPOC 2024

作者： Xiao, Zhengyuan Pan, Yichen Chen, Jiageng Ji, Jiazhen Li, Zhengwen He, Zuyuan State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China

Without any specialized receivers for extracting phase noise, we demonstrate a distributed acoustic sensor with phase noise compensation. 50 km sensing range is achieved using 100 kHz linewidth laser in EDFA free expe... 详细信息

ISBN: (纸本)9798350379266

关键词： Acoustic devices

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distributed Brute-Force Password Recovery with a Partitioned Quantum Grover’s Algorithm 2

Distributed Brute-Force Password Recovery with a Partitioned...

引用

2nd international conference on Computational Intelligence and Network systems, CINS 2024

作者： Bounceur, Ahcene University of Sharjah College of Computing and Informatics Sharjah United Arab Emirates

ISBN: (纸本)9798331504106

In the booming field of quantum computing, Grover’s Algorithm emerges as a pivotal quantum search algorithm, theoretically capable of outperforming classical brute-force search methods by exploiting the principles of superposition and quantum parallelism. However, the practical application of Grover’s Algorithm to crack complex passwords is limited by the nascent stage of quantum technology, which is currently challenged by limitations in qubit count and coherence times. This paper proposes a novel distributed quantum computing framework that aims to circumvent these limitations by partitioning the search space for a complex password among an array of quantum processors. Each processor executes Grover’s Algorithm on a fraction of the total search space, thereby reducing the complexity and quantum resource requirements for each individual computation. The partial results are then transmitted to a central classical computer, which synthesizes them into the final password. This distributed approach not only makes the task feasible for (with) present-day quantum systems but also presents a scalable model that could adapt to the rapid advancements in quantum technologies. By dissecting the complexity of the quantum brute-force problem into smaller, more manageable units, this method holds the potential to significantly reduce the time complexity of password recovery processes and thus presents a profound progress (implications) for the fields of cryptography and cybersecurity. ©2024 ieee.

关键词： Quantum computers

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Demystifying deep learning in predictive monitoring for cloud-native SLOs 16

Demystifying deep learning in predictive monitoring for clou...

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ieee 16th international conference on Cloud computing (ieee CLOUD)

作者： Morichetta, Andrea Pujol, Victor Casamayor Nastic, Stefan Pusztai, Thomas Raith, Philipp Dustdar, Schahram Vij, Deepak Xiong, Ying Zhang, Zhaobo TU Wien Distributed Syst Grp Vienna Austria Futurewei Technol Inc Santa Clara CA USA

ISBN: (纸本)9798350304817

The complexity inherent in managing cloud computing systems calls for novel solutions that can effectively enforce high-level Service Level Objectives (SLOs) promptly. Unfortunately, most of the current SLO management solutions rely on reactive approaches, i.e., correcting SLO violations only after they have occurred. Further, the few methods that explore predictive techniques to prevent SLO violations focus solely on forecasting low-level system metrics, such as CPU and Memory utilization. Although valid in some cases, these metrics do not necessarily provide clear and actionable insights into application behavior. This paper presents a novel approach that directly predicts high-level SLOs using low-level system metrics. We target this goal by training and optimizing two state-of-the-art neural network models, a Short-Term Long Memory LSTM-, and a Transformer-based model. Our models provide actionable insights into application behavior by establishing proper connections between the evolution of low-level workload-related metrics and the high-level SLOs. We demonstrate our approach to selecting and preparing the data. We show in practice how to optimize LSTM and Transformer by targeting efficiency as a high-level SLO metric and performing a comparative analysis. We show how these models behave when the input workloads come from different distributions. Consequently, we demonstrate their ability to generalize in heterogeneous systems. Finally, we operationalize our two models by integrating them into the Polaris framework we have been developing to enable a performance-driven SLO-native approach to Cloud computing.

关键词： workload prediction neural networks cloud LSTM Transformers

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