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

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Efficient Resource Management of Kubernetes Pods using Artificial Intelligence

Efficient Resource Management of Kubernetes Pods using Artif...

引用

international conference on parallel distributed and grid computing (PDGC)

作者： Karanbir Singh Deepak Muppiri Inderveer Chana Infrastructure Lifecycle Management Cloud Salesforce San Francisco USA Computer Science & Engineering Department Thapar Institute of Engineering and Technology Patiala India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

In the realm of cloud infrastructure management, efficient resource utilization is a classic problem. It is imperative to use cloud resources optimally to make them more cost effective. A resource can be a unit of compute, memory, etc. Considerable research and development have been done to efficiently run a cloud service such that it can serve varying requirements of the consumers at the same time. Tools such as Kubernetes are widely used in the industry to auto scale services based on their demand. The identification of adequate sets of resources that are just right for the services at the pod level is still a challenge. This paper presents an efficient resource management model at the Kubernetes pod level with the help of Artificial Intelligence.

关键词： Industries Deep learning Cloud computing Costs Computational modeling Memory management grid computing Resource management Artificial intelligence Research and development

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ISAR Imaging of Targets with Complex Motions Based on the Non-uniformed Sampled Integrated Modified Chirp Rate-Quadratic Chirp Rate Distribution 26

ISAR Imaging of Targets with Complex Motions Based on the No...

引用

26th ACIS international Winter conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD-Winter 2023

作者： Sun, Zongyang Bai, Linting Xu, Kangfa Xi'an Aeronautics Computing Technique Research Institute Avic Aviation Key Laboratory of Science and Technology on Airborne and Missle-borne Computer Xi'an China

ISBN: (纸本)9798350345865

This paper proposes a new ISAR algorithm for obtaining well-focused images of targets with complex motions in low signal-to-noise ratio (SNR) environments. The algorithm models the echo signals of targets with complex motions as cubic phase signals (CPS) after motion compensations and uses the Non-uniformed Sampled Integrated Modified Chirp Rate-Quadratic Chirp Rate Distribution (NIM-CRQCRD) to estimate CPS parameters. The proposed algorithm compensates the echo signals using the parameter estimates and generates ISAR images of targets with complex motions. Simulation results show that the proposed algorithm has superior anti-noise performance. © 2023 IEEE.

关键词： Parameter estimation

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High-Performance computing for Efficient Transaction Processing: A Comparative Study of parallel and Sequential Execution using SQLite 5

High-Performance Computing for Efficient Transaction Process...

引用

5th international conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Balaji, C.V.Roshan Shaman, K.R. Pritham Raj, V. Kumar, N.Nithish Kumaran, K. School of Computer Science and Engineering Vellore Institute of Technology Chennai campus India

ISBN: (纸本)9798331518097

High-performance computing (HPC) has become an essential tool for improving the efficiency and scalability of transaction processing systems, especially as data volumes continue to grow in fields like finance, e-commerce, and blockchain. This paper presents a comparative study of parallel and sequential transaction processing methods using an SQLite database. Specifically, the research investigates the impact of HPC techniques on transaction throughput, processing speed, and efficiency by simulating 1,000 user transactions. The study employs Python's multiprocessing module to simulate parallel execution, contrasting it with traditional sequential execution. Key performance indicators, including execution time, transaction success rate, and system efficiency, were analyzed to determine the advantages of parallel processing in a transaction-heavy environment. Our results reveal that parallel execution significantly reduces processing time, boosts throughput, and increases overall system efficiency compared to sequential processing. Additionally, the study discusses how parallel processing techniques can address common bottlenecks in transaction-heavy applications and provide solutions for improving the performance of large-scale, data-intensive systems. The findings demonstrate the potential for using HPC to optimize database operations, particularly in systems where high-volume transaction processing is a critical requirement. Future work will explore advanced parallelization strategies, fault tolerance mechanisms, and integrations with distributed databases and blockchain systems. This research contributes to the growing body of knowledge on optimizing transaction processing in high-performance computing environments, with potential applications across various sectors, including financial services, e-commerce, and blockchain technology. © 2024 IEEE.

关键词： Blockchain

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An Improved Method to Find Location and Sizing of DG In IEEE-69 Bus Distribution System 2

An Improved Method to Find Location and Sizing of DG In IEEE...

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2nd IEEE international conference on Advancements and Key Challenges in Green Energy and computing, AKGEC 2024

作者： Saurabh, Kumar Prusty, B. Rajanarayan Kumar, Kanhaiya Galgotias University Department of Electrical Electronics and Communication Engineering Greater Noida India Galgotias College of Eng. and Tech. Department of Electrical and Electronics Engineering Greater Noida India

ISBN: (纸本)9798350390179

Getting more power is seen as one of the fastest effective means for nations to develop and one of the greatest challenges in the world at present. Countries have changed their strategies for utilizing renewable energies rather than nonrenewable sources of energy since there aren't many of them and utilizing them is terrible for the environment. Renewable energies are easy to get, never lose worth over time, and don't depend on fluctuations in price. This means they can be used more in energy systems today. The electrical grid will have to change because of the most suitable location to position these resources and the best way to utilizethem. There is an approach to sort through which and how large to put DG (distributed generation) in energy distribution networks so that there is as little energy reduction, voltage-age constraints, distributed generation loading constraints, current limits, and distributed generation in filtration constraints as possible. In the first step, you need to find the distributed generation feature that helps each bus the most. After that, pick the best spot for the distributed generation to ensure it helps every bus most effectively. This method is able to be used to figure out the number and location of both single and multiple DG. For determining the most suitable area for, size and power factor of distributed generation in the distributional structure, the Coot Bird Optimization Technique (CBOM) is proposed. The suggested method has been tested on distributed Networking and IEEE 69-bus. The CBOM method that was mentioned is a good way to determine the best place, terms of sizes and power factors for distributed creation. It could also be used for other kinds of distribution structures. © 2024 IEEE.

关键词： distributed energy

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Decentralized parallel Blockchain Agricultural Product Traceability System Security Analysis 5

Decentralized Parallel Blockchain Agricultural Product Trace...

引用

5th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2024

作者： Fenglin, Sun Guangxi Normal University Qixing District Guangxi Guilin City541000 China

ISBN: (纸本)9798350395235

This research work presents a decentralized parallel blockchain-based agricultural product traceability system, which aims to enhance information security and data model efficiency, and achieve real-time tracking of agricultural products. Through an in-depth analysis of decentralized blockchain applications, the system adopts distributed ledger processing for low-cost transactions. The Digital Promise technology ensures the credibility of the data transmission and privacy protection. The proposed decentralized parallel blockchain structure shows significant traceability results, ensuring transparent traceability of agricultural products. Experimental results demonstrate the effectiveness of the system, improving food safety and quality management. The decentralized nature reduces the risk of data tampering, thereby enhancing public trust. Experimental results show short query response times, efficient data transfers, and zero failures, highlighting the system's excellent performance in handling traceability queries. These results underscore the remarkable advantages of blockchain technology in increasing the efficiency and reliability of traceability systems. © 2024 IEEE.

关键词： Blockchain

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Flink Task Scheduling Based on LBGA 4

Flink Task Scheduling Based on LBGA

引用

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

作者： Cao, Qingzhuo She, Ping Chai, Xiaoli East China Institute of Computing Technology Shanghai China

ISBN: (纸本)9798350337181

In order to solve the problem of uneven task load of different nodes affecting task execution time and throughput caused by the Flink's default scheduling strategy, a task scheduling strategy based on load balancing genetic algorithm (LBGA) in the Flink streaming computing environment is proposed. The strategy starts by calculating resource node performance metrics based on the resource data monitored by the Ganglia module. Considering the matching relationship between task resource requirements and performance metrics, this paper proposes an idea of applying the genetic algorithm (GA) to a streaming computing platform for optimisation. In addition, the LBGA scheduling is proposed on this basis and then experiments are conducted to verify the effectiveness of the algorithm. The experimental results show that compared to the default scheduling algorithm of Flink, the proposed algorithm reduces the execution time of WordCount benchmark tasks by 7.6% and 7.7% for parallelism degrees of 8 and 16 respectively. Not only is the performance of resource node load balancing optimised, but throughput is also significantly improved. © 2023 IEEE.

关键词： Genetic algorithms

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Software and hardware co-design strategy of RISC-V chip for power business application

Software and hardware co-design strategy of RISC-V chip for ...

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2024 international conference on Electronics, Electrical and Information Engineering, ICEEIE 2024

作者： Shuhua, Zhang Chuanqi, Zhao Wei, Yang Chao, Tong Bo, Gao Lisha, Gao Chengling, Jiang China Electric Power Research Institute Beijing100192 China School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China State Grid Jiangxi Electric Power Co. Ltd. Electric Power Research Institute Nanchang330096 China State Grid Ningxia Electric Power Research Institute Ningxia Hui Autonomous Region Yinchuan750001 China Nanjing Power Supply Branch State Grid Jiangsu Electric Power Co. Ltd. Nanjing210000 China State Grid Jiangsu Electric Power Co. Ltd. Nanjing210000 China

ISBN: (数字)9781510686809

ISBN: (纸本)9781510686793

With the increasing data scale and the increasing complexity of data processing requirements in the power industry, the demand for high-performance and low-power processor solutions is increasingly urgent. According to the characteristics of power business applications, this paper proposes a software and hardware co-design strategy of RISC-V (Reduced Instruction Set computing-V) chip for power business applications. The strategy focuses on instruction set optimization, memory system optimization, parallel computing optimization and hardware accelerator design, aiming at improving the performance and energy efficiency of the chip and meeting the demand of large-scale data processing in the power field. Through case study and verification, the research results show the remarkable effects of this strategy in improving processing speed, reducing power consumption and improving energy efficiency. The research results of this paper provide an efficient processor scheme for data processing in power industry, and also provide new ideas and methods for the application of RISC-V architecture in power industry. © 2024 SPIE.

关键词： Hardware-software codesign

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OPTIMIZATION MODEL OF distributed ENERGY SUPPLY SYSTEM BASED ON MULTI-ENERGY COMPLEMENTARITY 12

OPTIMIZATION MODEL OF DISTRIBUTED ENERGY SUPPLY SYSTEM BASED...

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12th international conference on Renewable Power Generation, RPG 2023

作者： Li, Jie Chai, Bo Liu, Siyan Wang, Yishen Shi, Xinghua State Grid Laboratory of Grid Advanced Computing and Applications Beijing China State Grid Smart Grid Research Institute Co. Ltd. Beijing China State Grid Zhejiang Eletric Power Co. Ltd. Hangzhou China

The distributed energy supply system based on multi-energy complementarity is currently a research hotspot in the field of energy engineering, and the key issue faced by this system is operation optimization. The reasonable configuration or not directly affects the economic benefits and operational efficiency of the system. This article focuses on this key issue faced by distributed energy supply systems with multiple complementary energy sources. Taking a cultural tourism park as the research object, considering factors such as economic indicators, energy consumption, and carbon emissions, a multi-objective optimization model for distributed energy supply systems with multiple complementary energy sources is established by gradually decomposing and introducing hourly energy constraints. Experiments have shown that compared to traditional systems, this model can achieve hourly operation optimization and has good economic efficiency and energy-saving and emission-reduction benefits. Therefore, it provides a good reference and reference for the energy supply and comprehensive energy planning of multi-energy complementary distributed energy supply systems. © The Institution of Engineering & Technology 2023.

关键词： Parks

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Enhancing Electric Vehicle Charging Systems with distributed Edge Intelligence 16

Enhancing Electric Vehicle Charging Systems with Distributed...

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16th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Rahmani, Rahim Stojcevska, Biljana Department of Computer and Systems Sciences Stockholm University Sweden American University of Europe Skopje Macedonia

The rapid proliferation of electric vehicles (EVs) and the corresponding expansion of charging systems, driven by global regulatory mandates, present significant challenges to the electric grid. These systems also generate massive volumes of heterogeneous, distributed data, necessitating advanced edge-cloud computing solutions. Deploying distributed Edge Intelligence (DEI) offers a transformative approach by contextualizing raw data, minimizing dependency on centralized resources, enhancing task performance through experience-based learning, predicting outcomes under uncertainties, optimizing data routing, and enabling self-organization of networked devices. Traditional centralized machine learning approaches are often unsuitable due to high communication costs, low reliability, legal constraints, and scalability limitations. In this context, Federated Learning (FL) emerges as a promising solution, enabling distributed machine learning models to be trained locally on decentralized data while preserving privacy and reducing communication overhead. This paper provides a comprehensive analysis of the key challenges associated with EV charging systems, including scalability, security, and privacy concerns. It also explores the integration of blockchain technology with FL at distributed edges to enhance system efficiency, reliability, and privacy. By addressing these challenges, the study outlines a framework for sustainable EV adoption and efficient charging infrastructure deployment in the context of evolving technological and regulatory landscapes. © 2025 The Author(s).

关键词： Edge computing

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DOA Estimation in A distributed Optimization Framework: A Sparse Approach Based on Consensus ADMM Implementation

DOA Estimation in A Distributed Optimization Framework: A Sp...

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2023 international conference on Images, Signals, and computing, ICISC 2023

作者： Jia, Xiaoyuan Wu, Xiaohuan Zhu, Wei-Ping School of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China Department of Electrical and Computer Engineering Concordia University Montreal Canada

ISBN: (数字)9781510668171

ISBN: (纸本)9781510668164

Traditional direction-of-arrival (DOA) estimation methods use a single processor to deal with the array data. In recent years, the increasing of the scale of sensor arrays brings heavy workload for single processor. distributed optimization based on multiple local processors has become one of the current research hotspots due to the advantage of parallel computing. In this paper, we proposed a distributed DOA estimation method for massive large-scale arrays. First of all, we provide the signal model and the distributed optimization problem based on sparse representation in a distributed framework. Then, the optimization problem is solved by the alternating direction multiplier method (ADMM), where the overall structure of array is not changed. Compared with the centralized method, our distributed method can greatly reduce the computational complexity while ensuring the estimation accuracy under the large aperture array. Simulation results are provided to show the superiorities of our method. © 2023 SPIE.

关键词： Optimization

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