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Challenges of Data Consistency in High-Concurrency Environments: Algorithms and Implementation for the Electric Power Industrial Internet Platform

Challenges of Data Consistency in High-Concurrency Environme...

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Information Science, parallel and distributed systems (ISPDS), international Conference on

作者： Zhongran Zhou Lili Wang Chunhe Song Yaowei Shen Mafeng Li Sai Liu NARI Information & Communication Technology Co.Ltd Nanjing China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information Technology Liaoning University Shenyang China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

With the rapid development of the Electric Power Industrial Internet, challenges in high-concurrency data processing have become increasingly prominent, particularly issues related to data consistency, which directly affect the stability and reliability of the system. This study addresses the distributed data consistency problems in the Electric Power Industrial Internet platform, proposing an optimized algorithmic framework designed specifically for high concurrency and dynamic environments to enhance the response speed and data processing capabilities of the power system. This paper first analyzes common data consistency challenges in high-concurrency environments within the power system, including data synchronization delays, complexity in fault recovery, and resource allocation issues. Based on these challenges, we introduce and optimize distributed data consistency algorithms, combined with load balancing and resource optimization techniques, significantly reducing communication costs and enhancing processing efficiency. Additionally, the paper designs a robust fault tolerance mechanism to ensure data integrity and consistency in the event of node failures. Through simulation experiments, we have confirmed the effectiveness of the proposed algorithms in terms of processing speed, system response time, and fault recovery, significantly optimizing the performance of the Electric Power Industrial Internet platform. This research not only enhances the robustness of the power system in facing high-concurrency data challenges but also provides important technical support and a theoretical basis for future research and applications in the Electric Power Industrial Internet.

关键词： Protocols Heuristic algorithms distributed databases Process control Power system stability Data processing Power systems

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Construction of Hierarchical Matrix on distributed Memory systems using a Task parallel Language 10

Construction of Hierarchical Matrix on Distributed Memory Sy...

引用

10th international symposium on Computing and Networking (CANDAR)

作者： Bai, Zhengyang Hiraishi, Tasuku Ida, Akihiro Yasugi, Masahiro Fukazawa, Keiichiro Kyoto Univ Grad Sch Informat Kyoto Japan Kyoto Tachibana Univ Dept Informat & Comp Sci Kyoto Japan Japan Agcy Marine Earth Sci & Technol Res Inst Value Added Informat Generat Yokohama Kanagawa Japan Kyushu Inst Technol Dept Comp Sci & Networks Iizuka Fukuoka Japan Kyoto Univ Acad Ctr Comp & Media Studies Kyoto Japan

ISBN: (纸本)9781665475327

A hierarchical matrix is an approximated form of the dense matrix that represents the N-by-N correlations of N objects. The construction of the hierarchical matrix is achieved by dividing a matrix into submatrices (partitioning), followed by calculating these submatrices' entries (filling). The matrix partitioning is divided into two sub-steps: cluster tree (CT) construction by dividing objects into clusters, hierarchically, and block cluster tree (BCT) construction by observing all cluster pairs at the same level of the cluster tree that satisfy a given admissibility condition. We can apply task parallelism to filling by treating each submatrix as a parallelization unit. In existing implementations, the partitioning is redundantly executed on every computing node, and filling is executed in parallel by assigning a set of tasks to each worker statically. However, we cannot get good load balance using such implementations because it is difficult to predict the workload of each task precisely. In this paper, we propose a new parallel implementation of the hierarchical matrix construction, where a BCT construction is executed in parallel using all workers of all computing nodes. When a worker finds a BCT leaf during BCT construction, it executes filling for the submatrix corresponding to the leaf. To get good load balance, we parallelized the BCT construction using the task parallel language Tascell, which enables easy and efficient parallelization of tree recursive algorithms by employing a dynamic load balancing strategy. In numerical experiments with 3D electric field analyses using up to 16 computing nodes each of which has 36 cores, our implementation achieved up to 1.9-fold speedups compared to an implementation using the static task assignment strategy.

关键词： hierarchical matrix dynamic load balancing task parallel language Tascell

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Development of a Collaborative Design Platform Based on Bim (Building Information Modeling) and Cloud Computing

Development of a Collaborative Design Platform Based on Bim ...

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Electronics, Energy systems and Power Engineering (EESPE), IEEE international Conference on

作者： Zekun Chang Shandong Vocational College of Industry Zibo China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This study proposes a collaborative design platform based on BIM and cloud computing, combined with an innovative real-time synchronization algorithm, to solve the problems of delay, data consistency and synchronization conflict in cloud collaborative design. The proposed real-time synchronization algorithm is based on a distributed computing model. By introducing a distributed lock and timestamp mechanism, it effectively guarantees the data consistency and real-time performance in large-scale collaborative design, and can reduce data conflicts and improve collaborative efficiency when multiple design teams operate in parallel. In order to verify the effectiveness of the platform, this study conducted experiments in multiple architectural design projects, and the platform runs in mainstream cloud computing environments (such as AWS and Azure). The experimental results show that the collaborative design platform based on the innovative algorithm has significant advantages over traditional collaborative design tools in terms of synchronization delay, data transmission speed and number of concurrent users. When multiple design teams collaborate, the design cycle of the platform is shortened by 15 %, the overall work efficiency is improved by more than 20 %, and it can maintain stability and low response time in a high concurrent user environment. In addition, the platform's real-time rendering and version control mechanism also significantly improve the design quality and accuracy.

关键词： Cloud computing Visualization Computational modeling Buildings Collaboration distributed databases Real-time systems Delays Synchronization Security

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An Approach to Dynamic Satellite Service Substitution in Satellite Constellations

An Approach to Dynamic Satellite Service Substitution in Sat...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Yucheng Tao Haopeng Chen Zihong Lin Chang Liu Shengyang Liu Fei Han School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Institute of Spaceflight Control Technology Shanghai China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

With the continuous emergence of large-scale low-Earth orbit satellite constellations and the service-oriented functionality of satellites, we have designed a dynamic service substitution approach to enhance space-based missions’ reliability and completion rate. Based on our formal description model for satellite services, this approach generates one-to-one direct substitution or one-to-many composite substitution schemes when satellite service failures are detected, enabling task migration between satellites through real-time monitoring of satellite status. Additionally, when it is impossible to generate service substitution schemes that strictly meet function and resource requirements, this approach produces suboptimal solutions with relaxed constraints. These solutions are evaluated using our proposed evaluation model. Testing the prototype system demonstrated that our dynamic service substitution approach improves satellite missions’ reliability and completion rate compared to existing methods.

关键词： Satellite constellations distributed processing Satellites Evaluation models Prototypes Reliability engineering Real-time systems Orbits Testing

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Efficient Multi-Processor Scheduling in Increasingly Realistic Models (Brief Summary)

Efficient Multi-Processor Scheduling in Increasingly Realist...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Pál András Papp Georg Anegg Aikaterini Karanasiou Albert-Jan N. Yzelman Computing Systems Lab Huawei Zurich Research Center Zurich Switzerland

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

We study the problem of efficiently scheduling a computational DAG on multiple processors. While previous works have mostly studied this problem in rather simple models, we instead consider the well-established BSP model, and extend it with non-uniform memory access (NUMA) effects. This results in a notably more realistic model that captures communication costs, synchronization costs, and the hierarchical structure of modern computing architectures. We develop a range of algorithms to minimize the scheduling cost in this more complex setting: several initialization heuristics, a hill-climbing local search, and different approaches to solve the problem as an Integer Linear Program (ILP). We analyze our scheduling algorithms on a diverse set of real-world computational DAGs to show that they outperforms both academic and practical baselines: without NUMA effects, our scheduler finds solutions of 44%-51% smaller cost on average, and with NUMA effects, it achieves up to a factor 3× improvement. Finally, we develop a multilevel scheduling algorithm for the special case when the problem is dominated by very high communication costs.

关键词： distributed processing Costs Program processors Scheduling algorithms Computational modeling Heuristic algorithms Conferences

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Diverse Recommendations With Maximum Entropy Neighbor Selection and Graph Contrast Learning

Diverse Recommendations With Maximum Entropy Neighbor Select...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Jinhao Zhou Pinghua Chen Yunhua Chen Honghong Zhou School of Computer Science and Technology Guangdong University of Technology Guangzhou China Guangdong Science & Technology Innovation Monitoring and Research Center Guangzhou China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

It has become a great challenge to balance accuracy and diversity in recommendation systems. Graph Neural Networks (GNNs), while powerful, can lead to node representation homogeneity and information redundancy due to the indiscriminate aggregation of neighbor information. Therefore we propose a novel method that integrates maximum entropy neighbor selection with graph contrast learning to enhance the diversity of recommendations. The method introduces a strategy for neighbor selection based on maximum entropy to ensure a diverse subset of neighbors is chosen during the aggregation phase. A layer attention mechanism is implemented to address the over-smoothing issue, directing greater focus on higher-order neighbors. Furthermore, a loss re-weighting technique is applied to emphasize the learning of long-tail items. The overarching objective is to significantly improve recommendation diversity while maintaining system accuracy, underpinned by graph contrast learning method. Experimental results on the Beauty and MIND-small datasets demonstrate significant enhancements in the accuracy and diversity metrics of the proposed method. In particular, regarding the Recall@300 metric, a substantial improvement of up to 30.56% is observed. Conversely, the method experiences a mere 4.63% reduction in accuracy compared to the optimal baseline. This indicates that the proposed method markedly amplifies the diversity of recommendations without significantly compromising recommendation accuracy.

关键词： Measurement Learning systems distributed processing Accuracy Attention mechanisms Heavily-tailed distribution Redundancy Entropy Graph neural networks Recommender systems

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Low-bit CUTLASS GEMM Template Auto-tuning using Neural Network

Low-bit CUTLASS GEMM Template Auto-tuning using Neural Netwo...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Hong Guo Nianhui Guo Christoph Meinel Haojin Yang Hasso Plattner Institute University of Potsdam Potsdam Germany

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Optimizing General Matrix Multiplication (GEMM) on GPU platforms has become increasingly important due to the scaling demands of modern deep neural network research. While substantial progress has been made in accelerating high-precision GEMM, optimizing lower-bit GEMM remains an open problem. The CUTLASS library offers highly optimized low-bit GEMM based on tensor cores, but performance varies significantly with tile and pipeline settings across different GPUs. We introduce a novel auto-tuning framework for low-bit CUTLASS GEMM that employs a neural network model to predict optimal GEMM template parameters for target GPUs. This model was trained on a synthetic dataset featuring various matrix sizes from different Ampere GPUs and evaluated on these GPUs. In the test dataset, our method achieved an accuracy of up to 92.9%. Real-time evaluations of low-bit data types on the A100 GPU demonstrated speedups of up to 2.03× for GEMM and 1.44× for the linear layer compared to the default templates.

关键词： distributed processing Accuracy Tensors Pipelines Graphics processing units Predictive models Real-time systems Libraries Optimization Synthetic data

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parallel Electromagnetic Transient Simulation Method for MMC-based SST Based on Diakoptics

Parallel Electromagnetic Transient Simulation Method for MMC...

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IEEE international symposium on Power Electronics for distributed Generation systems (PEDG)

作者： Yiming Yang Jin Xu Zirun Li Keyou Wang Guojie Li Pan Wu Department of Electrical Engineering Shanghai Jiao Tong University Shanghai China

With the rapid development of renewable energy generation and the distribution network, the dc network has become a hotspot in research and engineering. In the dc network, the power electronic transformer (PET, also known as solid-state transformer, SST) is the crucial interface device. To achieve better characteristics, the SST based on modular-multilevel-converter (MMC) is proposed. The cascade modulization and high switch efficiency of MMC-SST bring challenges to its electromagnetic (EMT) simulation. The numerous submodules increase the order of the node admittance matrix, requiring more computation resources; the high switch frequency requires a smaller time step, decreasing the calculation speed. To deal with these problems, this paper proposes a parallel EMT simulation method based on the diakoptics. This method achieves parallelized calculation at the system level and submodule level by tearing the whole system into subsystems and applying the compact EMTP method. The proposed method is verified in MATLAB and an FPGA-based real-time simulation platform.

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A Fault Tolerance Mechanism for UAV-Assisted Vehicular Network in Disaster Rescue

A Fault Tolerance Mechanism for UAV-Assisted Vehicular Netwo...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Kaiqi Zhang Jing Zhao Rui Chen Dalian University of Technology Dalian China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Data sharing among ground rescue vehicles is essential for safe and efficient operations in disaster-stricken areas. When disasters disrupt communication infrastructure, unmanned aerial vehicles (UAVs) can be deployed to facilitate data sharing among vehicles. However, maintaining reliable inter-vehicle communication is challenging due to potential UAV and link failures. To enhance communication reliability, we propose a fault tolerance mechanism for UAV-assisted vehicular networks. We introduce the novel concept of K-fault tolerance, which marks the first study of fault tolerance in this context. Moreover, we develop a UAV deployment algorithm that minimizes UAV requirements, controlling costs while maintaining K-fault tolerance. Furthermore, we propose a fault tolerance topology control algorithm (FTTCA) that adjusts deployed UAV communication ranges to further reduce costs while ensuring K-fault tolerance, supported by corresponding theorem proofs. Extensive simulations validate the effectiveness of our proposed UAV deployment algorithm and FTTCA and demonstrate the superiority of our fault tolerance mechanism in managing UAV and link failures.

关键词： Fault tolerance distributed processing Costs Network topology Disasters Simulation Fault tolerant systems Autonomous aerial vehicles Topology

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MTRP: A High-Performance Cost-Efficient Buffering Scheme for Multi-Tenant Cloud Services

MTRP: A High-Performance Cost-Efficient Buffering Scheme for...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Zekai Zhu Peiquan Jin Guorui Huang Xiaoliang Wang Yigui Yuan University of Science and Technology of China Hefei China Unit 31002 the Chinese People’s Liberation Army Beijing China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Multi-tenancy is a crucial criterion for cloud service providers since it enables them to share resources among tenants, thus reducing costs. As all tenants share the same buffer space in the cloud server, a tenant’s overall performance will be affected by other tenants. Thus, developing an efficient buffering scheme to ensure tenant isolation becomes an urgent need. Aiming to solve this problem, this paper proposes a novel buffering scheme for managing the shared buffer in a multi-tenant cloud database. We first present an SLA (Service Level Agreement)-based model to quantify the buffering performance of each tenant. Then, we propose MTRP (Multi-Tenant Replacement Policy) for multi-tenant scenarios. The novelty of MTRP lies in three aspects: (1) it partitions the buffer into logical zones to implement tenant isolation. Each zone manages the pages one tenant uses, but the zone space can be dynamically adjusted by buffer replacements; (2) it proposes a two-step replacement algorithm, including global replacement and local replacement, which can improve space efficiency and reduce the SLA cost; (3) it adopts a reinforcement learning model to select the most appropriate zone for page replacement. The experimental results on various multi-tenant workloads show that MTRP achieves a higher hit ratio and lower SLA costs than LRU, LFU, LRU-2, and LeCaR.

关键词： distributed processing Costs databases Heuristic algorithms Reinforcement learning Minimization Partitioning algorithms Servers History Service level agreements

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