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

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distributed online extraction of a fluid model for microservice applications using local tracing data 15

Distributed online extraction of a fluid model for microserv...

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15th ieee international conference on Cloud computing (ieee CLOUD) / ieee World Congress on Services (ieee SERVICES)

作者： Ruuskanen, Johan Cervin, Anton Lund Univ Dept Automat Control Lund Sweden

ISBN: (数字)9781665481373

ISBN: (纸本)9781665481373

Dynamic resource management is a difficult problem in modern microservice applications. Many proposed methods rely on the availability of an analytical performance model, often based on queueing theory. Such models can always be hand-crafted, but this takes time and requires expert knowledge. Various methods have been proposed that can automatically extract models from logs or tracing data. However, they are often intricate, requiring off-line stages and advanced algorithms for retrieving the service-time distributions. Furthermore, the resulting models can be complex and unsuitable for online evaluation. Aiming for simplicity, we in this paper introduce a general queuing network model for microservice applications that can be (i) quickly and accurately solved using a refined mean-field fluid model and (ii) completely extracted at runtime in a distributed fashion from common local tracing data at each service. The fit of the model and the prediction accuracies under system perturbations are evaluated in a cloud-based microservice application and are found to be accurate.

关键词： microservice runtime management performance modeling model extraction queuing networks fluid model

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Efficient Power Generation System Using Single Axis Solar Tracking with Weather Monitor

Efficient Power Generation System Using Single Axis Solar Tr...

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2023 international conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Ananthajothi, K. Santhosh, S. Shreyas, S. Santhosh, M. Rajalakshmi Engineering College Computer Science and Engineering Chennai India

ISBN: (纸本)9798350319200

Growing at the fastest rate among renewable energy sources is solar energy. Using a basic dual-axis solar tracker system, the project is conceived and executed. Solar tracking devices are a must for solar power plants in order to optimize solar energy production. Utilizing a switching solar panel, a dual-axis tracker tracks the sun's beams in many directions to maximize energy *** 360-degree rotation of this solar panel is possible. The light intensity was sensed at 30 degrees per degree, or 180 degrees overall, using an LDR (Light Dependent Resistor), which subsequently sent data to the microcontroller. Also, this dual-axis solar tracker project has an LCD display, humidity and temperature sensors, and a raindrop detector. © 2023 ieee.

关键词： Dual axis solar tracker LDR sensor Renewable energy Solar power

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Experimental and Theoretical Analysis of Deep Residual Time-Delay Reservoir computing Based on Clipping Algorithm 22

Experimental and Theoretical Analysis of Deep Residual Time-...

引用

22nd international conference on Optical Communications and Networks, ICOCN 2024

作者： Zhou, Changdi Li, Nianqiang School of Optoelectronic Science and Engineering Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou215006 China Soochow University Key Lab of Advanced Optical Manufacturing Technologies of Jiangsu Province Key Lab of Modern Optical Technologies of Education Ministry of China Suzhou215006 China

ISBN: (纸本)9798350367652

Photonic reservoir computing (RC), as a crucial variant of recurrent neural networks, has boasted substantial potential owing to its straightforward training processes and facile hardware integration. In this work, we introduce and validate both experimentally and numerically a novel post-processing technique, referred to as the clipping algorithm (CA), utilized on the high-performance deep residual time-delay RC (DR-TDRC). The proof-of-concept model, i.e., a four-layer DR-TDRC, comprises 960 interrelated neurons (240 neurons per layer) based on four injection-locked distributed feedback lasers. Our results demonstrate that the implementation of the CA can effectively mitigate issues associated with the redundant layers and improve the performance of deep architectures. © 2024 ieee.

关键词： distributed feedback lasers

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A Comprehensive Overview on IoT-Based Smart Stroke Rehabilitation Using the Advances of Wearable Technology 23

A Comprehensive Overview on IoT-Based Smart Stroke Rehabilit...

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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： Razfar, Najmeh Kashef, Rasha Mohammadi, Farah Ryerson University Electrical and Computer Engineering Toronto Canada

ISBN: (纸本)9781665494571

The Internet of Things (IoT) is growing fast, and with the advancement of wearable devices and sensors, a wide range of research opportunities is now available. Several machine learning and deep learning techniques were deployed to provide smart stroke rehabilitation in remote stroke treatment and assessments. Reviewing and understanding existing studies in IoT-based stroke rehabilitation and finding the gap in this field can improve rehabilitation strategy. This paper summarizes the development of smart stroke rehabilitation knowledge for remote rehabilitation and assessments of stroke survivors. We have summarised the datasets and the state-of-the-art machine learning and deep learning methods in the IoT-based smart stroke rehabilitation using wearable devices. Supervised learning is the most common technique reported for stroke rehabilitation, and the optimum model is also reported in this paper. This survey provides a novel roadmap for future research in IoT-based stroke rehabilitation and treatment. © 2021 ieee.

关键词： Deep learning Smart cities Wearable computers Supervised learning Stroke (medical condition) sensor systems Internet of Things

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IOT and Artificial Intelligence based Smart Agriculture System Using Node MCU 2

IOT and Artificial Intelligence based Smart Agriculture Syst...

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2nd ieee international conference on Trends in Quantum computing and Emerging Business Technologies, TQCEBT 2024

作者： Dhandapani, Padmapriya Kg College of Arts and Science Department of Computer Technology Saravanampatti Coimbatore641 035 India

ISBN: (纸本)9798350384277

Rural action on the cultivate requires exertion for occurrence, planting, keeping up, and collecting crops requires assets such as cash, time, vitality, and work. An counterfeit insights group created a framework that can distinguish plant infections. This analysts utilized a strategy called exchange learning to instruct the AI to recognize edit illnesses and creepy crawly *** has been affected by innovation in numerous ways, which has changed cultivating hones over time. A second obstacle to arrival will be the approximately 4% additional land under construction on the world by 2055, when the population is predicted to rise from 8.0 billion to 9.9 billion. Farming is the essential industry that makes occupations in a expansive number of countries around the world. Agriculturists will in this manner require to utilize less assets with more prominent exertion. In arrange to bolster an additional two billion individuals, nourishment yield would require to rise by 60%, concurring to the same appraise. [1]In today's world, Farming needs to keep up with innovative headway's as well. IoT is fundamental to cleverly cultivating. Web of Things (IoT) sensors grant the vital information approximately cultivate lands. The capacity to screen horticulture utilizing remote sensor systems and collect information from a few sensors that are scattered over diverse regions and transmitted through remote convention is the fundamental advantage of the Web of Things. The IoT stage that supports keen farming is called NodeMCU. In addition to the temperature, wetness, and mugginess sensors, it contains a DC engine. The degree of stickiness and moisture is started to be graded by this framework. © 2024 ieee.

关键词： sensor nodes

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Determine the Number of distributed Big Data Storage Replicas 26

Determine the Number of Distributed Big Data Storage Replica...

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26th international conference on Soft computing and Measurements, SCM 2023

作者： Tatarnikova, Tatyana M. Arkhiptsev, Evgeny D. Saint Petersburg Electrotechnical University LETI Department of Information Systems St. Petersburg Russia

ISBN: (纸本)9798350322484

The problem of distributed storage of big data on clusters is discussed. Known methods of distributed storage are considered: fragmentation and replication. Replication schemes are considered that allow accelerating access to data: peer-to-peer and master-slave. It is shown that replication leads to data inconsistency, which in practice is a compromise formulated in the CAP theorem: out of three properties-data consistency and availability, their partition resistance -no more than two properties can be provided. A model for determining the required number of nodes in a cluster and the number of replicas based on the queuing theory is proposed. In terms of solving the fragmentation problem, a recurrent procedure and a method for choosing the optimal cluster structure are proposed. As part of solving the replication problem, a model for choosing the number of replicas in the event of a 'write-write' conflict in the 'master-slave' scheme is proposed. © 2023 ieee.

关键词： Big data

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Intelligent Sampling: A Novel Approach to Optimize Workload Scheduling in Large-Scale Heterogeneous computing Continuum 17

Intelligent Sampling: A Novel Approach to Optimize Workload ...

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17th ieee international Congress on Intelligent and Service-Oriented systems Engineering (CISOSE)

作者： Pujol, Victor Casamayor Morichetta, Andrea Nastic, Stefan TU Wien Distributed Syst Grp Vienna Austria

ISBN: (纸本)9798350322392

Scheduling workloads on large-scale infrastructures, such as in the Edge-Cloud continuum is a challenging task. Usually, the scheduling algorithm considers only a limited sample of the infrastructure nodes, typically obtained through random sampling. The sampling reduces the number of nodes, which need to be evaluated in the scheduling pipeline, making the scheduling process more saleable. Unfortunately, current sampling approaches become largely inefficient when the infrastructure is heterogeneous and specific, scarce node characteristics are required to successfully execute a workload. computing continuum infrastructures are heterogeneous, hence, we need to re-think the sampling process to keep it viable at scale while also being able to identify and leverage the heterogeneity of the Edge-Cloud continuum resources. In this article, we present Intelligent Sampling - a novel technique for improving sampling in large-scale and heterogeneous infrastructures. We develop a model for any heterogeneous infrastructure. Based on this model, we provide a method to sample the infrastructure nodes more accurately, considering the specific task at hand. Finally, we leverage the Alibaba PAI dataset to show that our approach is 2.5x times more accurate compared with other state-of-the-art sampling mechanisms while retaining comparable performance and scalability.

关键词： computing continuum Intelligent sampling Workloads scheduling Heterogeneous infrastructure model

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distributed Reinforcement Learning Framework for Collaborative Energy Management in Connected Hybrid Electric Vehicle Ecosystems

Distributed Reinforcement Learning Framework for Collaborati...

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2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Kumar, P. Lokesh Jayanthi, Muthuswamy Singh, Jay Gupta, Manish Bobba, Phaneendra Babu Albawi, Ali Shubhra Mlr Institute of Technology Department of CSE-AI&ML Telangana Hyderabad India New Horizon College of Engineering Department of Electronics and Communication Engineering Bangalore India Gl Bajaj Institute of Technology and Management Dept. of Eee U.P Gr. Noida India Lovely Professional University Phagwara India Griet Department of Eee Bachupally Telangana Hyderabad India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India

ISBN: (纸本)9798331527495

The technical parameters of HEV energy management systems increase in interaction with connected and dynamic environments, therefore demanding superior control algorithms. This work proposes an asynchronous RL paradigm for energy management in driving HEV ecosystems. The framework uses distributed RL agents with each agent responsible for local policy optimization for energy control of individual electric vehicle and with sharing information through V2V and V2I mechanisms. A general optimization layer superposes local data to coordinate personal interests with global objectives, for example, the general level of emissions and traffic density. The proposed method is capable of effectively mitigating the periodic decision making issue through using high accuracy RL algorithms for instance the MAPPO alongside low latency communication. OpenPowertrainLib and SUMO are utilized for traffic modelling integrating stochastic traffic characteristics and renewable energy inputs as well as complicated vehicle dynamics. Research findings establish the efficiency in terms of energy savings and emissions compared to single optimized energy management solutions as well as improved traffic flow. The research puts emphasis on distributed RL frameworks in developing intelligent transportation systems that positively impact scalability and sustain ability of connected HEV networks. This study sets the ground for potential future developments in co-energy management and its incorporation into smart cities. © 2025 ieee.

关键词： Hybrid vehicles

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Adaptive Control and Optimization Techniques for Microgrid Energy Management 4

Adaptive Control and Optimization Techniques for Microgrid E...

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4th international conference on Advances in Electrical, computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Sahu, Vishnu Kumar Singh, Mahesh Tiwari, Shruti Ralhan, Shimpy Shri Shankaracharya Technical Campus Department of Ee Chhattisgarh Bhilai India Shri Shankaracharya Technical Campus Department of Eee Chhattisgarh Bhilai India

ISBN: (纸本)9798350343670

In the era marked by rapid advancements in "green energy"and storage technologies, microgrids integrated with distributed generation principles emerge as a promising avenue for efficient power management. DC microgrids have attracted significant interest among researchers and engineers owing to the escalating adoption of renewable energy sources coupled with energy storage systems, improved utilization of DC power electronics devices, and the additional benefits of mitigating harmonics and synchronization challenges. A crucial aspect necessitates the establishment of an efficient, optimized, and dependable control system for the integrated infrastructure. This article introduces a versatile and adaptable control system for microgrid resources, aimed at fulfilling the local households' electricity demand while addressing economic considerations. The proposed approach adopts a decentralized control structure, deploying controllers in each household, leveraging open-source optimizers and cost-effective hardware. To mitigate the likelihood of failure, the authors developed a redundant solution, incorporating redundant communication channels and hot standby control devices. A comprehensive validation process was conducted via simulations on a sample microgrid encompassing diverse methods of generation and storage, ensuring robustness and reliability. © 2024 ieee.

关键词： DC microgrids distributed energy generation Green energy microgrids

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IoT based Smart Assistance for Visually Impaired using Raspberry Pi 2

IoT based Smart Assistance for Visually Impaired using Raspb...

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2nd international conference on Automation, computing and Renewable systems, ICACRS 2023

作者： Rambabu, Kalathiripi Dubey, Sanjay Arjun, Dindigala Sathwik, Jennarapu Swastik, Kodi Department of Electronics and Communication Engineering B V Raju Institute of Technology Narsapur Medak502313 India

ISBN: (纸本)9798350340235

With the help of a revolutionary smart eyeglass prototype introduced in this system, visually impaired people will receive crucial support in identifying people and spotting obstacles in their environment. The prototype makes use of cutting-edge technology, such as face recognition and distance detection characteristics, to provide a thorough and simple user interaction. The Raspberry Pi 4 B serves as the prototype's primary processing unit, and it is supplemented by a Raspberry Pi 4 camera, an ultrasonic sensor for measuring distance, a 5V power supply, and a special set of glasses. These elements work together to create a seamless system that gives those who are blind or visually impaired better perception and navigational skills. Smart eyewear uses cutting-edge technology to identify individuals using face recognition features precisely. © 2023 ieee.

关键词： Pi Camera Raspberry Pi Ultrasonic sensor

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