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IEEE 12th international symposium on Power Electronics for distributed Generation systems (PEDG)

作者： Cortes, Luis R. de Morais, Aniel S. Carvalho, Daniel P. Tofoli, Fernando L. Ribeiro, Laura Gomes, Adjeferson C. Univ Fed Uberlandia Dept Elect Engn Uberlandia MG Brazil Univ Fed Sao Joao del Rei Dept Elect Engn Sao Joao Del Rei Brazil Univ Estadual Santa Cruz Dept Elect Engn Ilheus BA Brazil

ISBN: (纸本)9781665404655

This work presents the application of a distributed control approach to maximize the power extraction from photovoltaic (PV) modules based on a dc-dc four-switch synchronous buck-boost converter (FSBBC). The outputs of several converters are connected to series and parallel arrays, thus allowing obtaining maximum power point tracking (MPPT) in an individual manner, regardless of the temperature and/or irradiance conditions.

关键词： distributed control FSBBC maximum power point tracking photovoltaic systems

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Research on Graph Injection Attack Method Based on Multi Objective Feature Optimization in the Electric Power Field

Research on Graph Injection Attack Method Based on Multi Obj...

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parallel Computing and distributed systems (PCDS), international symposium on

作者： Runyang Ji State Grid Nantong Power Supply Company Nantong Jiangsu

ISBN: (数字)9798350349658

ISBN: (纸本)9798350349665

In the field of electricity, in response to the problem of graph neural networks having both significant performance and poor robustness, this may lead to poor recommendation performance or affect social evaluation, posing a threat to the integrity and security of social networks. Therefore, this article proposes a graph injection attack method based on multi-objective feature optimization, which selects multiple target nodes with similar features through clustering target selection strategy and directly connects the injection nodes to the target nodes, ensuring the effective propagation of disturbance information. This operation can enable the disturbance information attached to the injection node to propagate more directly to each target node. For the generation of perturbation features, the selected target node is used to aggregate its own information and neighboring node information to generate it. In order to enhance the perturbation ability of perturbation features, a zero order random coordinate descent algorithm is applied to optimize the generated features for discrete feature maps.

关键词： Social networking (online) Perturbation methods Electricity Clustering algorithms parallel processing Robustness Graph neural networks Power systems Security Optimization

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Optimize Metadata Operations of Key-Value Store via A Flat Indexing LSM-Tree

Optimize Metadata Operations of Key-Value Store via A Flat I...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Yuchen Liu Chen Chen Shu Yin School of Information Science and Technology ShanghaiTech University China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

The effectiveness of applying key-value store mechanisms to manage metadata of file systems has been demonstrated recently. However, traditional indirect metadata indexing schemes are not in concert with key-value data structures, which could degrade the performance of a KV-embedded file system due to the overhead of hierarchical path queries. In this paper, we propose FILT (Flat Indexing LSM-Tree), a lightweight file system middleware that can solve this issue by employing flat indexing. We introduce a new range rename mechanism over LSM-tree to provide fast directory renames. FILT exploits the benefits of both flat indexing and LSM-tree structure to eliminate redundant path look-ups. Our extensive performance evaluation studies show that FILT can offer up to 2.3X performance gain compared with TableFS and 56x to ordinary cloud file systems.

关键词： Performance evaluation distributed processing Costs File systems Metadata Performance gain Data structures Middleware Indexing

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Federated Learning Based Neural Machine Translation

Federated Learning Based Neural Machine Translation

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international symposium on Advanced Computing and Communication (ISACC)

作者： Parvez Aziz Boruah Hiren Kumar Deva Sarma Shikhar Kumar Sarma Department of Information Technology Gauhati University Guwahati India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

In this paper a work on Federated Learning based Machine Translation is performed using English-Assamese Language pair. Federated Learning is the concept of machine learning where data are distributed on different system called clients/nodes. Our objective was to performe a Machine Translation training using Federated Learning Architecture and observed the performance by varying the system parameters/hyperparameters. Also two different Federated Aggregation strategies have been used for comparison. It was observed that having a higher number of clients/nodes, there is a reduce in performance score.

关键词： Training Federated learning Neural machine translation distributed databases Computer architecture Intelligent systems

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A Review of Data Placement and Replication Strategies Based on Machine Learning

A Review of Data Placement and Replication Strategies Based ...

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international Conference on parallel and distributed systems (ICPADS)

作者： Amir Najjar Riad Mokadem Jean-Marc Pierson Institut de Recherche en Informatique de Toulouse (IRIT) Université de Toulouse Toulouse France

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

The global increase in data volumes has brought forth the need for scalable distributed systems that can provide satisfactory quality of service. Data placement and replication are well known techniques that provide increased performance, improved fault tolerance and higher availability. These techniques often require threshold-based activation mechanisms that can vary due to the nature of the workload and the underlying system architecture. Hence, setting and adjusting those thresholds usually require human intervention. In this context, machine learning presents a promising facet to automatically define such thresholds to adapt to different workloads and architectures. In this paper, we study the data placement and replication strategies proposed in the literature that employ machine learning. We classify such strategies based on the machine learning method, the platform on which they are deployed, the dynamicity and the achieved objectives. We describe the approach applied by each strategy as well as possible limitations. In addition, we provide insights into metrics used to evaluate the strategies. We highlight the need to design data placement and replication strategies that respond better to modern needs for distributed systems. We also motivate the use of machine learning to achieve autonomy in distributed systems.

关键词： Fault tolerance Costs Fault tolerant systems Taxonomy distributed databases Quality of service Reinforcement learning Time factors Unsupervised learning Tuning

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Data Communication Algorithm of HPDB parallel Database System Based on Computer Network

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international Journal of High Speed Electronics and systems 2025年第2期34卷

作者： Ma, Zhiqiang School of Information Engineering Henan Agricultural Vocational College Henan Zhengzhou451450 China

High-Performance Database (HPDB) is designed to meet the demands of today's modern data-driven world, as massive volumes of information need to be accessed and analyzed with minimal latency. A pivotal aspect of their operation lies in efficient data communication among nodes in a computer network, which is essential for parallel database systems. HPDBs may involve distributed architectures and parallel database systems to store and process data across multiple nodes or servers in a network. Hence, an algorithm called Hybridized Partitioning Strategy (HPS)-based Communication (C) for achieving HPDB has been proposed to facilitate data transmission and coordination across a computer network using the Message Passing Interface (MPI) protocol. The proposed HPS-C-HPDB technique includes partitioning and distributing data, query routing, and load balancing strategies to achieve high-performance levels. The (HPS) combines hash and range partitioning methods for effective processing and retrieval to balance data distribution, reduce communication overhead in parallel databases, and improve the system's performance. In parallel database systems, query routing effectively routes requests into the optimal nodes or partitions based on the query's conditions and the data's placement and guarantees efficient data processing and retrieval. The proposed scheme is evaluated using various performance metrics like throughput, response time, speedup, and communication overhead analysis. © 2025 World Scientific Publishing Company.

关键词： Search engines

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Data Center Isolated parallel Ring Bus Differential Protection Scheme 12

Data Center Isolated Parallel Ring Bus Differential Protecti...

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IEEE 12th international symposium on Power Electronics for distributed Generation systems (PEDG)

作者： Jiang, Taosha Qi, Lisa Zhang, Yuzhi Suryanarayana, Harish Alzamli, Mohammed Handlin, Harry Colombi, Silvio ABB Inc US Res Ctr Raleigh NC 27606 USA ABB Inc Electrificat Distribut Solut Glendale Hts IL USA ABB Ltd Electrificat Smart Power Quartino Switzerland

ISBN: (纸本)9781665404655

UPSs are used in data centers and other critical power applications for power conditioning and back-up. In addition, to ensure reliability of the data center, a redundant architecture is needed. This increases capital expenses and decreases the utilization rate. One approach is to use the isolated parallel ring bus (IPRB) architecture with static UPS. This features load sharing with active and reactive power transferred through choke inductors to the ring bus. This architecture maximizes the utilization rate while maintaining the reliability of the system. The protection scheme in this IPRB is critical to guarantee the operation in case of any fault. In this paper, the differential protection scheme of the IPRB is explained with simulation and field-testing results. The differential protection can effectively identify and isolate faults to ensure uninterrupted service to the load.

关键词： data center fault protection differential protection

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An architecture interface and offload model for low-overhead, near-data, distributed accelerators 55

An architecture interface and offload model for low-overhead...

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55th Annual IEEE/ACM international symposium on Microarchitecture (MICRO)

作者： Baskaran, Saambhavi Kandemir, Mahmut Taylan Sampson, Jack Penn State Univ University Pk PA 16802 USA

ISBN: (数字)9781665462723

ISBN: (纸本)9781665462723

The performance and energy costs of coordinating and performing data movement have led to proposals adding compute units and/or specialized access units to the memory hierarchy. However, current on-chip offload models are restricted to fixed compute and access pattern types, which limits software-driven optimizations and the applicability of such an offload interface to heterogeneous accelerator resources. This paper presents a computation offload interface for multi-core systems augmented with distributed on-chip accelerators. With energy-efficiency as the primary goal, we define mechanisms to identify offload partitioning, create a low-overhead execution model to sequence these fine-grained operations, and evaluate a set of workloads to identify the complexity needed to achieve distributed near-data execution. We demonstrate that our model and interface, combining features of dataflow in parallel with near-data processing engines, can be profitably applied to memory hierarchies augmented with either specialized compute substrates or lightweight near-memory cores. We differentiate the benefits stemming from each of elevating data access semantics, near-data computation, inter-accelerator coordination, and compute/access logic specialization. Experimental results indicate a geometric mean (energy efficiency improvement;speedup;data movement reduction) of (3.3;1.59;2.4)x, (2.46;1.43;3.5)x and (1.46;1.65;1.48)x compared to an out-of-order processor, monolithic accelerator with centralized accesses and monolithic accelerator with decentralized accesses, respectively. Evaluating both lightweight core and CGRA fabric implementations highlights model flexibility and quantifies the benefits of compute specialization for energy efficiency and speedup at 1.23x and 1.43x, respectively.

关键词： distributed accelerator near-data offload energy efficiency heterogeneous architecture interface

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A Columnar Storage Cone Search Method for Massive Astronomical Data

A Columnar Storage Cone Search Method for Massive Astronomic...

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

作者： Yu-hai Liu Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (数字)9798350352719

ISBN: (纸本)9798350352726

In recent years, with the continuous advancement of astronomical instrument manufacturing technology, astronomical observation data has shown an exponential growth trend, and traditional database technologies are no longer able to meet the storage and retrieval performance requirements. To address the challenges of storing massive astronomical data and efficient cone search, a solution utilizing columnar storage is proposed, leveraging the separate storage of each attribute column in columnar storage for independent retrieval to enhance data read efficiency. Building upon this, a specialized cone search area retrieval method tailored for columnar storage mode is introduced to reduce data read and computation in cone search, further enhancing retrieval efficiency.

关键词： Information science Search methods Instruments Buildings Relational databases Market research Manufacturing

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ECCH: Erasure Coded Consistent Hashing for distributed Storage systems 19

ECCH: Erasure Coded Consistent Hashing for Distributed Stora...

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19th IEEE international symposium on parallel and distributed Processing with Applications (IEEE ISPA)

作者： Xiong, Yinglong Zhou, Jiang Su, Lin Wang, Weiping Chen, Yong Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Texas Tech Univ Dept Comp Sci Lubbock TX 79409 USA

ISBN: (纸本)9781665435741

In this paper, we propose ECCH, an Erasure Coded Consistent Hashing scheme to make better data placement in distributed storage systems. It combines the inherent advantages of consistent hashing together with the storage-efficiency of erasure coding technology. Specifically, ECCH divides data block stream of files into groups according to block IDs. In each group, it encoded data blocks with additional parity blocks by erasure coding. All encoded blocks in the same group are stored on different nodes with consistent hashing distribution. For node failure or data loss, ECCH locates required data through the ID of missing block in a same group for fast recovery. To deal with node changes, ECCH introduces a design of multi-version hash rings to manage data layout. It can prevent the impact of data migration on erasure coding, while achieving data balance with little data movement. We have implemented ECCH on the Sheepdog, a distributed object-based storage system. Evaluation results show that ECCH can greatly improve the space utilization of hashing-based storage systems, while achieving efficient fault tolerance.

关键词： Consistent hashing erasure coding replication data distribution fault tolerance

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