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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

共 34266 条记录，以下是821-830 订阅

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A Mobile Network Experience Quality Evaluation Model Based on Network Security 2

A Mobile Network Experience Quality Evaluation Model Based o...

引用

2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Zhang, Xiaolu Shen, Wuqiang Cui, Lei Guangdong Power Grid Guangdong Guangzhou China

ISBN: (纸本)9798350382952

In order to seize more users and market share, network operators and service providers must continuously improve their service level and quality to meet the increasing demands of customers. Therefore, the quality of user experience has become a focus of their attention. This article first defines and extracts feature parameters including video correlation, end-to-end network packet loss damage, and end-to-end network delay damage. Among them, video related feature parameters are used to measure the impact of video encoding damage and video content on user experience quality. Then, based on end-to-end communication of streaming media services on mobile networks, this article establishes an end-to-end simulation business platform for mobile network streaming media. Subsequently, this article designed and organized the subjective testing of user experience quality based on the characteristics of mobile network streaming services. Finally, this article establishes an end-to-end user experience quality evaluation model for mobile networks based on quality evaluation methods using different feature parameter subsets. The results indicate that the multi and multi feature parameters involved in this article only require packet header parsing of network data packets, without involving video decoding, and have the characteristic of low computational complexity. © 2024 IEEE.

关键词： Quality control

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Empirical Study on the Relationship Between Renewable Energy Electricity Consumption and Carbon Emission Based on Genetic Algorithm 13th

Empirical Study on the Relationship Between Renewable Energy...

引用

13th international conference on Frontier computing, FC 2023

作者： Su, Yun Zhang, Kai Liu, Shu Shi, Shanshan Wang, Zhaohui State Grid Shanghai Electric Power Company Shanghai200120 China

ISBN: (纸本)9789819995370

Renewable energy is the main energy in China. It has great development potential, but it also brings severe challenges to the operation and management of power system. Firstly, this paper combs the distributed robust optimization theory, specifically including the characteristics and applicable conditions of the distributed robust optimization model, classifies them according to the different methods of fuzzy set construction of uncertain parameters, and analyzes the advantages and disadvantages of each method of fuzzy set construction, laying a theoretical foundation for the subsequent construction of the distributed robust optimization scheduling model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Genetic algorithms

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Improvement of Task Scheduling with Energy Efficiency including Fault Tolerant with Resilient computing System in parallel and distributed Communication Network 2

Improvement of Task Scheduling with Energy Efficiency includ...

引用

2nd international conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Kumar, Vijay Madhuri, P. Yamini, R. Sravani, Palla Muthukumar, K. Graphic Era Hill University Department of Physics Dehradun India Hyderabad501401 India Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu Kattankulathur603203 India Raghu Engineering College Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam531162 India Sri Krishna College of Engineering and Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350325799

In parallel and distributed communication networks, task scheduling is essential for attaining the best system performance. Innovative ways that may intelligently distribute computing resources while minimizing energy consumption and maintaining system resilience are required due to the rising need for energy efficiency and fault tolerance. This system, offers a unique approach to job scheduling in parallel and distributed communication networks that integrate genetic algorithms (GA) and machine learning (ML).Using ML approaches, proposed method analyses historical task execution data to discover patterns that may be applied to task execution time prediction in various computing systems. As a result, this can assign tasks to resources effectively, maximize resource usage, and cut down on execution time as a whole. In addition, using predefined objectives like energy efficiency and fault tolerance, GA is used to find the best task-resource assignments. This applies resilient computing approaches to the job scheduling procedure to overcome problems with fault tolerance. This prevents the execution of crucial operations from being hampered by system faults or resource shortages by utilizing fault detection and recovery technologies. This system can adapt dynamically to shifting network conditions through the combination of ML, GA, and resilient computing, which raises the entire system's reliability and availability. © 2023 IEEE.

关键词： Machine learning

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CoupHM: Task Scheduling Using Gradient Based Optimization for Human-Machine computing Systems 28

CoupHM: Task Scheduling Using Gradient Based Optimization fo...

引用

IEEE 28th international conference on parallel and distributed Systems (IEEE ICPADS)

作者： Wang, Hui Ren, Zhuoli Yu, Zhiwen Zhang, Yao Liu, Jiaqi Cui, Heilei Northwestern Polytech Univ Sch Comp Sci Xian Peoples R China

ISBN: (纸本)9781665473156

We witnessed great advancement in Artificial Intelligence (AI) powered technologies in recent years, and yet, when applied to certain high-stake contexts, such as medical diagnosis, automatic driving and criminal justice, they are not qualified. This matter can be greatly settled by Human-Machine computing (HMC), which is an effective computing paradigm that couples the expertise and demonstration abilities of humans with the high-performance computing power of machines. This work studies an optimal task scheduling problem for HMC systems, where various tasks are decomposed and dispatched to humans and AI-enabled machines to provide significantly better benefits compared to either type of computing resources in isolation. However, designing such optimal task scheduling is challenging because of the stochastic hybrid features of machines, as well as various human professional abilities. Considering the Quality of Service (QoS) and the heterogeneity of human-machine computing resources, we propose CoupHM, a feasible task scheduler using gradient based optimization for HMC systems. In particular, we firstly present the underlying architecture of HMC system and details of the task-driven workload model. On that basis, we then formulate the objective optimization problem to be solved and describe the composition of the CoupHM scheduler. Finally, the performance of our solution is evaluated by the simulation experiments, and the results indicate that the proposed scheduler has preferable performance both in balancing resources and guaranteeing QoS, which can serve as guidelines for future research on HMC systems.

关键词： Human-machine computing Task scheduling Gradient based optimization Quality of service

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A distributed Feature Extraction Method Based on MapReduce 2

A Distributed Feature Extraction Method Based on MapReduce

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2nd IEEE international conference on Control, Electronics and Computer Technology, ICCECT 2024

作者： Wang, Yongchang Hu, Hongqiang Liu, Xuning College of Future Information Technology Shijiazhuang University Shijiazhuang China

ISBN: (纸本)9798350380958

For data with complex dimensions, Kernel Principal Component Analysis (KPCA) is a common method of feature extraction, it has a better generalization performance. However, it often face with significant difficulties in computation on large datasets. Therefore, we developed a parallel KPCA algorithm based on MapReduce (MRKPCA) in this paper, it's a parallel computing method which can run in a cluster. We apply our algorithm to an experiment of datasets of face recognition, the experimental results show that our algorithm can scale well and has better timeliness for some specific problems which require a lot of computation, and it can significantly reduce computation time. © 2024 IEEE.

关键词： MapReduce

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Intelligent Detection and Automatic Repair of Cement Pole Defects Based on Deep Reinforcement Learning 2

Intelligent Detection and Automatic Repair of Cement Pole De...

引用

2nd international conference on distributed computing and Optimization Techniques, ICDCOT 2024

作者： Hong, Wenming Huang, Yongxiang Li, Junyi Guo, Wei State Grid Zhejiang Electric Power Material Branch Zhejiang Hangzhou China

ISBN: (纸本)9798350382952

Cement poles are an important part of building construction, and their quality problems directly affect the success of the entire project. In order to solve this problem, this paper adopts deep reinforcement learning technology and uses network analysis technology to build a model for cement pole detection and repair. The model includes front-end acquisition terminal equipment, as well as functional modules such as sensor arrays and embedded microprocessors, which perform operations such as data processing, positioning calculation and artificial neural network fusion in real time. Through this system, the location of steel bar defects during construction is identified, surface stress and strain are measured, and the mechanism of crack formation is studied. Through deep learning methods, cement poles are tested and optimized to improve their quality and durability. Test results show that the deep reinforcement learning algorithm requires more interactive samples in real environments to achieve higher accuracy, with an accuracy rate of over 94%;the scalability can reach up to 0.85. This model can not only effectively improve the quality control capabilities of cement poles, but also has high practicability and operability, and can provide strong technical support and guidance for the building construction industry. © 2024 IEEE.

关键词： Poles

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parallel Software for Million-scale Exact Kernel Regression 23

Parallel Software for Million-scale Exact Kernel Regression

引用

37th ACM international conference on Supercomputing (ACM ICS)

作者： Chen, Yu Skon, Lucca McCombs, James R. Liu, Zhenming Stathopoulos, Andreas William & Mary Williamsburg VA 23185 USA Indiana Univ Bloomington IN USA

ISBN: (纸本)9798400700569

We present the design and the implementation of a kernel principal component regression software that handles training datasets with a million or more observations. Kernel regressions are nonlinear and interpretable models that have wide downstream applications, and are shown to have a close connection to deep learning. Nevertheless, the exact regression of large-scale kernel models using currently available software has been notoriously difficult because it is both compute and memory intensive and it requires extensive tuning of hyperparameters. While in computational science distributed computing and iterative methods have been a mainstay of large scale software, they have not been widely adopted in kernel learning. Our software leverages existing high performance computing (HPC) techniques and develops new ones that address cross-cutting constraints between HPC and learning algorithms. It integrates three major components: (a) a state-of-the-art parallel eigenvalue iterative solver, (b) a block matrix-vector multiplication routine that employs both multi-threading and distributed memory parallelism and can be performed on-the-fly under limited memory, and (c) a software pipeline consisting of Python front-ends that control the HPC backbone and the hyperparameter optimization through a boosting optimizer. We perform feasibility studies by running the entire ImageNet dataset and a large asset pricing dataset.

关键词： kernel principal component regression SVD parallel algorithm classification machine learning software tools boosting

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Reliability Dynamic Perception-based Power Line Communication Hierarchical Networking Method 4

Reliability Dynamic Perception-based Power Line Communicatio...

引用

4th international conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Shi, Zhan Li, Bo Wu, Zhentian Wang, Xiuzhu Guangdong Power Grid Co. Ltd. Power Dispatching Control Center Communication Management Department Guangdong China Guangdong Electric Power Communication Technology Co. Ltd. Science Innovation Department Guangdong China

ISBN: (纸本)9798350337181

With the large-scale access of distributed photovoltaic, controllable load, and energy storage devices to the low-voltage distribution network, the requirements for the transmission quality and processing efficiency of power line communication data are rapidly increasing. However, large access of high proportion power electronic components will introduce color noise, which will have a great impact on the channel environment of power line communication. This paper first constructs a multi-layer hierarchical power line communication networking architecture. Then, a reliability dynamic perception-based optimal subcarrier selection method is proposed to meet the high-speed transmission requirements of renewable power system services. The simulation results show that the algorithm has excellent performance in probability of selecting the optimal subcarrier versus iteration and data transmission efficiency. © 2023 IEEE.

关键词： Memory architecture

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A Cross-Chain Transaction Model for Power Blockchain Based on Hash-Locking Mechanism 3

A Cross-Chain Transaction Model for Power Blockchain Based o...

引用

3rd international conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Li, Jinzhong Duan, Xiangjun Qiu, Wangjie Cao, Panan Wang, Zhen Li, Yunshuo State Grid Corporation of China State Grid Anhui Electric Power Research Institute Hefei China State Grid Corporation of China China Electric Power Research Institute Beijing China Beihang University Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing China

ISBN: (纸本)9798350318180

Blockchain is a closed island in the traditional power transaction platform and cannot freely trade with others, which limits the flexibility and autonomy of the distributed power trading market. Aiming at the problems of network isolation and interoperability among different power blockchains, we proposed a general and compatible power cross-chain trading protocol based on hash time locking technology, where the transaction power and price are locked by hash time to realize cross-chain exchanges of different assets. A flexible and specialized smart contract framework is designed, which can be easily adapted and extended according to specific needs, promoting the flexibility and freedom of the distributed power market. And the experimental shows that the transaction processing capability is significantly better than that of the relays technology when dealing with multiple concurrency problems. © 2023 IEEE.

关键词： cross-chain distributed power trading hash-locking smart contracts

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Stability Analysis of Circulating Current in Multi-parallel grid-Connected Inverter System 2

Stability Analysis of Circulating Current in Multi-Parallel ...

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2nd IEEE international Power Electronics and Application Symposium, PEAS 2023

作者： Li, Mingliang Ruan, Xinbo Shi, Mingming Zheng, Xian College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Electric Power Research Institute of State Grid Jiangsu Electric Power Co Ltd. Nanjing China

ISBN: (纸本)9798350313765

Multi-parallel grid-connected inverter system is increasingly applied in distributed power generation systems. Due to the existence of grid impedance, the output current of the grid-connected inverter cannot be fed to the grid totally, and a part of it will circulate to other inverters connected in parallel under weak grid. And the stability of circulating current also affects the safety and reliability of the system. Also, the large circulating current will bring more power loss to system. This paper uses the average model of the grid-connected inverter to establish the Norton equivalent circuit of the multi-parallel grid-connected inverter system. On this basis, the generation mechanism of the circulating current is explained by the current separateness, and the relationship between the stability of the circulating current and the injected grid current is indicated. Finally, the accuracy of the proposed theory is verified by simulation. © 2023 IEEE.

关键词： circulating current current separateness grid-connected inverter weak grid

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