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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841-850 订阅

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A Trading Scheme of Power Blockchain Based on Identity-Based Ring Signature for Anonymity and Anti-Forgery 5

A Trading Scheme of Power Blockchain Based on Identity-Based...

引用

5th international conference on Electronics and Communication, Network and Computer Technology, ECNCT 2023

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

ISBN: (纸本)9798350328660

Privacy is important in power blockchain. For privacy of distributed power transactions, we propose a SM9-compliant anonymous transaction scheme combining identity-based cryptography and ring-signature techniques, solving the complex management problem of public key and certificate while maintaining user privacy. We prove the unforgeability and anonymity of this scheme under the stochastic prediction model, which provides a secure and trustworthy anonymous transaction mechanism in the absence of a trusted transaction center. Experiments show that compared with the RSA ring signature, the scheme in this paper is superior in terms of communication cost and resource consumption, and can provide support for distributed power transactions. © 2023 IEEE.

关键词： Blockchain

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Research on Intelligent Prediction of Blasting Vibration Based on parallel SVM in Big Data Environment 24

Research on Intelligent Prediction of Blasting Vibration Bas...

引用

9th international conference on Intelligent Information Processing, ICIIP 2024

作者： Wang, Hui Rao, Xiaokang Li, Chunhui WUHAN CITY POLYTECHNIC China Wuhan University China Rajamangala University of Technology Tawan-Ok Thailand

ISBN: (纸本)9798400718076

Blasting vibration is one of the main negative effects of blasting construction. It is influenced by many external factors and has a complex nonlinear relationship with them. How to predict and reduce the blasting vibration effect while completing the blasting construction is a long-term concern in the blasting industry. With the development of the Internet of Things and mobile devices, various types of data collection in blasting projects have become quick and varied. Many massive, multi-source, heterogeneous blasting vibrations, and geological data have been gathered. Such a large-scale data set implies potentially useful information and presents significant challenge relevant to traditional computation theories and methods as well. Based on the massive data related to blasting vibration, this paper uses Hadoop to establish a distributed computing framework, establishes a big data analysis platform to carry out massive data mining and analysis, and builds a parallel SVM blasting vibration intelligent prediction model based on the Spark parallel computing framework. The blasting vibration velocity and frequency of blasting construction of a project in southwest are selected and compared with the calculated and measured values of the traditional Sadovski’s formula to verify the intelligent blasting prediction model in the big data environment. The practice shows that blasting vibration intelligent prediction has high efficiency and higher accuracy than traditional models based on parallel SVM used in large data environment. In this paper, the parallel computing and data mining technologies of big data clusters are applied to intelligent prediction of blasting vibrations, changed the traditional random sampling and single mining analysis models, and extracted the useful information for management, decision-making and production from massive data, improved the efficiency and precision of the intelligent blasting prediction models. © 2024 Copyright held by the owner/au

关键词： Vibration analysis

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Test-and-Decode: A Partial Recovery Scheme for Verifiable Coded computing 23rd

Test-and-Decode: A Partial Recovery Scheme for Verifiable Co...

引用

23rd international conference on Algorithms and Architectures for parallel Processing (ICA3PP)

作者： Jiang, Wei Wang, Jin Li, Lingzhi Yu, Dongyang Liu, Can Soochow Univ Sch Comp Sci & Technol Suzhou Peoples R China Soochow Univ Sch Future Sci & Engn Suzhou Peoples R China

ISBN: (纸本)9789819708581;9789819708598

Coded computing has proven its efficiency in tolerating stragglers in distributed computing. Workers return the sub-computation results to the master after computing, and the master recovers the final computation result by decoding. However, the workers may provide incorrect results, which leads to wrong final result. Therefore, it is meaningful to improve the resilience of coded computing against errors. Most existing verification schemes only use the workers' fully correct computations to recover the final result, and the defective computations are not considered for decoding. In this paper, we focus on matrix multiplication and design a general Test-and-Decode (TD) scheme to recover the final result efficiently. Furthermore, we divide each sub-computation result into multiple parts and fully use the correct parts for partial recovery, which can improve the tolerance for errors in computations. Decoding is performed only when the verification result satisfies the permission, which avoids repetitive decoding. We conduct extensive simulation experiments to evaluate the probability of successful recovery of the results and the computation time of the TD scheme. We also compare the TD scheme with other verification schemes and the results show that it outperforms the current schemes in terms of efficiency in verifying and recovering computational results.

关键词： Coded computing distributed computing Matrix Multiplication Partial Recovery

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Deconstructing Alibaba Cloud's Preemptible Instance Pricing 23

Deconstructing Alibaba Cloud's Preemptible Instance Pricing

引用

32nd international Symposium on High-Performance parallel and distributed computing (HPDC) part of the ACM Federated computing Research conference (FCRC)

作者： Davidow, Danielle Movsowitz Ben-Yehuda, Orna Agmon Dunkelmen, Orr Tel Aviv Univ Dept Ind Engn Tel Aviv Israel Univ Haifa Caesarea Rothschild Inst Interdisciplinary Applic Haifa Israel Univ Haifa Dept Comp Sci Haifa Israel

ISBN: (纸本)9798400701559

Alibaba Cloud's preemptible instances are IaaS instances sold using an auction, similar to the spot instances offered by Amazon Web Services (AWS). Clients purchase them by bidding. The instances are terminated when supply is insufficient, or when the client's bid is lower than the "market price"- which Alibaba Cloud publishes ever so often. We collected Alibaba Cloud's preemptible price traces from November 2018 to July 2021. This work analyzes the traces, and shows evidence that they experienced sharp lateral behavioral changes over time. We characterize the traces before and after these events. Our analysis highlights features in the traces that seem to be artificially engineered by an underlying pricing mechanism. Since engineered features may abruptly change, they are particularly interesting to clients planning their bidding strategy, or scholars who study them (e.g., to design new pricing mechanisms on the basis of real-life data).

关键词： Cloud computing Auctions Alibaba Cloud Traces

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Tokenized Intelligence: Redefine Network Optimization in Softwarized Networks 10

Tokenized Intelligence: Redefine Network Optimization in Sof...

引用

10th international conference on Network Softwarization (NetSoft)

作者： Zanardo, Enrico Martini, Barbara Bellisario, Denise Univ Mercatorum Rome Italy

ISBN: (纸本)9798350369588;9798350369595

Tokenized Intelligence (TI) aims to enhance network performance by combining machine learning and blockchain-based tokenomics in software-defined networks (5G/6G). This paper examines the potential for incentivizing decentralized edge computing through economic rewards, which can facilitate the efficient training of AI models. TI enables the coordination of a decentralized network of nodes, which allows for collaborative sharing of resources and decreases the expenses linked to centralized cloud-based solutions. TI is utilized to design customized logical networks that effectively optimize the use of computing, storage, and networking resources within a common physical infrastructure. This framework, which is decentralized and distributed, speeds up data analysis and reduces delays. It also provides economic rewards for edge nodes that participate in model training activities. The core of TI lies in its ability to improve network slicing strategies, such as best effort, high availability, and low latency, while also incentivizing edge nodes based on their contributions to the training process of the machine learning model. This economic incentive mechanism guarantees the efficient allocation of resources according to the specific needs of machine learning applications, thereby enhancing overall network performance.

关键词： AI/ML softwarized networks 5G 6G blockchain DLT parallel Computation

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Point cloud objective recognition method combining SHOT features and ESF features 12

Point cloud objective recognition method combining SHOT feat...

引用

12th international conference on Cyber-Enabled distributed computing and Knowledge Discovery (CyberC)

作者： Ding, Junfeng Chen, Hao Zhou, Jian Wu, Deyong Chen, Xuan Wang, Lei State Grid Jiangsu Elect Power Co Ltd Nanjing 211102 Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing 210023 Peoples R China State Grid Jiangsu Elect Power Co Ltd Extra High Voltage Branch Co Nanjing 211102 Peoples R China

ISBN: (纸本)9798350331547

During the process of obtaining a point cloud, various problems, such as noise, occlusion, and incompleteness, will affect the recognition accuracy of the object. This paper proposes a point cloud 3D object recognition method combining SHOT features and ESF features to identify the objects in complex point cloud scenes accurately. The model is recognized based on the template matching method. According to the corresponding group and Hough voting method, we can determine the matching key points and the global features are calculated based on the rotation invariance characteristic of point clouds. The experiments show that the proposed method is, on average, 15% more accurate than traditional feature descriptor based on identification methods, and our approach also presents better robustness to noise.

关键词： SHOT Hough voting ESF template matching point cloud

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Advancing Droop Control Dynamics for Equilibrium in Decentralized Microgrids: A Strategy for Enhanced Power Distribution

Advancing Droop Control Dynamics for Equilibrium in Decentra...

引用

2024 international conference on Advances in computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Islam, Riadul Kabir, Shaharier Hossain, Md Imran Hannan, Nasif Islam, Md Ashikul Shufian, Abu Lamar University Dept. of Electrical Engineering TX United States American International University-Bangladesh Dept. of Eee Dhaka Bangladesh Eastern University Dept.of Eee Dhaka Bangladesh

ISBN: (纸本)9798350350289

Variations in feeder impedances among distributed Generators (DGs) within a microgrid lead to inaccuracies in reactive power distribution. Additionally, significant fluctuations in load and diverse droop characteristics among DGs cause fluctuations in the inverter's voltage and frequency, thereby impacting both reactive and active power sharing. The generalized droop control strategy struggles to efficiently distribute both reactive and active power loads among the distributed generators. This paper introduces a decentralized enhanced droop-based control method aimed at improving the equitable distribution of both active and reactive power within an isolated micro grid utilizing inverters. The research then proceeds into enhancing droop control to achieve better optimization and incorporating additional mechanisms to distribute voltage, power, and frequency more effectively among different energy sources. A microgrid consisting of three DGs and three loads is simulated using the MATLAB/Simulink environment, and the proposed control strategy is validated through this simulation. The outcomes offer valuable understanding on addressing challenges related to voltage, power, and frequency imbalances, thereby improving the stability of Microgrids (MGs), and ensuring dependable operation of decentralized energy systems. © 2024 IEEE.

关键词： Reactive power

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Research on collaborative planning model of main distribution network frame structure and distributed power generation 3

Research on collaborative planning model of main distributio...

引用

2023 3rd international conference on Electrical, Electronics, and computing Technology, EECT 2023

作者： Ren, Xiaofeng Wang, Dong Gao, Hailong Yang, Pei Li, Jinghao State Grid XuZhou Power Supply Company Xuzhou221000 China State Grid Smart Grid Research Institute CO. LTD. Beijing102200 China Nanjing Institute of Technology Nanjing211167 China

The electric power industry is going through a relatively large transformation period of energy development, and new electric power equipment such as distributed power supply has emerged as the times require. However, there is often a problem of insufficient coordination between the grid frame and distributed power in the main distribution network. This paper starts with the two main stakeholders, namely, the distributed generation operator and the distribution system operator, to build a two-level collaborative planning model for the main distribution network. With the help of particle swarm optimization algorithm and genetic algorithm with improved constraint factors, the model is solved. In the optimization process, two different scenarios are set, including and not including the distributed generation output, for comparative analysis, the comprehensive cost of the collaborative planning model with distributed generation output is less than that of the collaborative planning model with traditional generation output. The results show that the model in this paper can not only optimize the overall line, but also reduce the excessive investment of the main distribution network, which is more in line with the future development of my country's power industry, can improve the profits of related enterprises, and achieve a win-win effect. © Published under licence by IOP Publishing Ltd.

关键词： distributed power generation

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2024 3rd international conference on Smart grid and Green Energy

2024 3rd International Conference on Smart Grid and Green En...

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2024 3rd international conference on Smart grid and Green Energy, ICSGGE 2024

The proceedings contain 39 papers. The topics discussed include: a composite control method of PWM and phase shift for a three-level DC-DC converter;two-stage stochastic planning for distribution networks considering uncertainties of electric vehicles and distributed generators;study on phase-locked out-of-step fault characteristic analysis and protection of VSPSU;optimal scheduling of virtual power plants considering integrated demand response;construction of small size and high output triboelectric nanogenerator by multi-layer stacking and charge excitation;low-delay low-voltage load aggregator demand response communication transmission architecture based on 5G edge computing;analysis of hierarchical optimization control technology of distribution network with mobile energy storage;and identification of hidden danger discharges in transmission lines based on multi-scale convolutional neural network.

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Emotionally Aware Edtech: A Deep Learning Perspective

Emotionally Aware Edtech: A Deep Learning Perspective

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international conference on parallel distributed and grid computing (PDGC)

作者： Mehak Goel Akshat Mittal Mitu Sehgal Sorabh Gupta Rashmi Makkar Department of Computer Science & Engineering (AI & DS) Panipat Institute of Engineering and Technology Panipat India Department of Information Technology Panipat Institute of Engineering and Technology Panipat India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Speech emotion recognition in affective computing is an area that is growing quickly. It has implications for how people and computers interact, how mental health is diagnosed, and how customer service is handled. To correctly pick up on emotions in real time, deep learning is used in this study. Our model looks at vocal pitch, tone, and cadence along with complicated neural network designs to accurately classify emotions. The method was taught with a variety of emotional expressions. It's strong and can work with a wide range of speakers and settings. Many tests show that the model is more accurate and can process emotions faster than most other ways. Deep learning can make automatic systems smarter about emotions, which can make them more caring and flexible, as this study shows

关键词： Deep learning Emotion recognition Affective computing Computational modeling Customer services Neural networks Speech recognition Mental health grid computing Real-time systems

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