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3rd International Conference on Big Data, Information and Computer Network, BDICN 2024

作者： Wu, Kefan Tao, Dapeng Wang, Linfei Ni, Jun Zhu, Da School of Information Yunnan University Kunming650000 China

ISBN: (纸本)9798350363821

ETL cluster scheduling technology plays a crucial role, which unveils the latent value of medical data and improve the medical digitization. However, in real-world scheduling scenarios, variations in the performance configurations of cluster nodes can significantly impact scheduling times. In addition, most mainstream ETL tools often neglect hospital business requirements in the governance process, leading to meaningless time consumption for important *** solve these problems, we propose the Weight-ETL, a multi-stage cluster scheduling algorithm specifically tailored for medical data governance. This algorithm takes into account the task importance and node performance comprehensively throughout the ETL governance process, thus enhancing data governance efficiency and aligning with hospital requirements. Quantitative experiments demonstrate that our proposed algorithm effectively prioritizes the tasks with high demand relevance and improves the efficiency of cluster scheduling compared with previous methods. © 2024 IEEE.

关键词： scheduling algorithms

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Research on green hybrid flow shop batch scheduling problem based on improved grey wolf algorithm 4

Research on green hybrid flow shop batch scheduling problem ...

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4rth International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2024

作者： Tang, Hongtao Xiang, Yingjie School of Mechanical and Electronic Engineering Wuhan University of Technology Hubei Wuhan430070 China

ISBN: (纸本)9781510681637

This article focuses on the green hybrid flow shop batch scheduling problem (EHFSP) considering energy consumption, establishes an optimization model with the goal of minimizing maximum completion time and total energy consumption, and proposes an improved grey wolf optimization algorithm. Firstly, a hybrid population initialization strategy based on cubic mapping is designed. According to the characteristics of the model, a forward window group batching strategy based on machine processing thresholds is used to divide workpieces into batches. A nonlinear convergence factor is designed to improve the optimization and convergence performance of the algorithm, enhancing the local search ability and solution quality of the algorithm. Through simulation experiments based on different datasets, the effectiveness of the proposed algorithm is verified. The comparison results show that the proposed algorithm is more effective than other algorithms in solving the EHFSP problem. © 2024 SPIE.

关键词： scheduling algorithms

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Research on the verification method of the Event-B model for the heterogeneous multi-core scheduling algorithm 4

Research on the verification method of the Event-B model for...

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4th International Conference on Communication Technology and Information Technology, ICCTIT 2024

作者： Zuo, Junjie Han, Yahui Xiao, Feng Huang, Shujuan Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798331528973

It is well known that the logical verification for the operating system is very essential. Event-B, as a formal verification tool, is one of the most widely used methods for verifying programs at the operating system level. However, it lacks the precise time semantics expression that will make the representation of the behavioral logic complicated for verified scheduling process. To address this limitation, we proposes an EMPT (Event-B Multi-core Processor Time) model in rodin platform, which can represent the time semantics by using set mappings and operations. After that we apply it to the logical verification for the heterogeneous multicore scheduling algorithm (HEFT), and the results show that it can verify the accuracy of this algorithm. © 2024 IEEE.

关键词： scheduling algorithms

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A Heuristic Algorithm for Time Triggered Traffic scheduling in Time-Sensitive Networks 43

A Heuristic Algorithm for Time Triggered Traffic Scheduling ...

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43rd Chinese Control Conference, CCC 2024

作者： Chen, Shengming Wang, Wending Zhou, Suolan Zhang, Lei College of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China Technology Co. Ltd Changzhou China

ISBN: (纸本)9789887581581

Time Sensitive Networks (TSN) is a set of revisions to the IEEE 802.1 standard enabling safety-critical and real-time transmission over Ethernet. It is crucial in TSN to use a reasonable scheduling algorithm to guarantee the deterministic delivery of streams. A heuristic algorithm is proposed in this paper for incremental time triggered traffic scheduling in TSN. It identifies available time slots with pruning operations. If the available time slot is insufficient to generate a scheduling plan, fallback operations are executed to extend the time slots. Experimental results show that the proposed algorithm can effectively improve the success rate of traffic scheduling in the application scenarios with different network sizes and stream scales. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： scheduling algorithms

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An Intelligent approach for the short-term generation scheduling of a hydrothermal power system employing the Osprey Optimization Algorithm

An Intelligent approach for the short-term generation schedu...

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2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Pasupulati, Baburao Sushmi, Mavuluru Sudhakiran, P. Amosedinakaran, S. Sreedhar, R. Vinoth John Prakash, S. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Electrical and Electronics Engineering Chennai India Srinivasa Ramanujan Institute of Technology Department of Electrical and Electronics Engineering Andhra Pradesh India New Horizon College of Engineering Department of Electronics and Communication Engineering Bengluru India

ISBN: (纸本)9798350381887

In an electric power system, the main goal of Hydrothermal Generation scheduling (HTGS) is to effectively manage hydrothermal unit power generation while abiding by system restrictions. The scheduling timeframe can range from a single day to multiple days. HTGS poses a challenging optimization problem due to its non-linear, non-convex, and non-smooth nature, making traditional techniques less effective. To address this complexity, a novel Osprey Optimization Algorithm (OAA) is introduced in this study. The algorithm is structured around three key stages: Initialization, Position Identification, and Fish Hunting and Transport to Optimal Locations. Notably, the OAA algorithm stands out for its unique feature of not requiring algorithmic tuning parameters, thereby expanding the search space for achieving optimal solutions. The effectiveness of the proposed OAA algorithm is demonstrated through its application to a test system comprising four hydro and three thermal units, with simulation results compared against recent experimental findings in the literature. © 2024 IEEE.

关键词： scheduling algorithms

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An Empirical Study on Various Workflow scheduling Techniques in Cloud Computing 1

An Empirical Study on Various Workflow Scheduling Techniques...

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1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Madhumala, G. Suma, R. Sri Siddhartha Institute of Technology Department of Information Science and Engineering Karnataka Tumkur72103 India

ISBN: (纸本)9798350367720

Cloud computing (CC) is a modern technology which deploys networks of servers, positioned in extensive remote areas, for conducting operations on a larger quantity of data. In CC, a workflow module is employed for representing diverse scientific and web applications. One of the major problems is scheduling larger workflows of tasks on the heterogeneous CC environment. This article summarizes some important research works in the field of CC associated with workflow scheduling (WS). At first, this survey represents the common structure of WS in cloud and then, scheduling approaches are catalogued into four techniques like Machine Learning (ML), Deep Learning (DL), Hybrid and Algorithmic-based approaches are discussed in detail. Thereafter, the research gaps faced by the traditional approaches for WS will help the researchers in future for building an innovative model. This study considers 25 research articles focused on different methodologies employed for WS in cloud. Lastly, the evaluation is performed in the survey regarding year of publication, performance measures, research technique, and attainment of the research models. It is acknowledged that algorithmic based modules are usually employed approaches, while cloudsim is repeatedly applied tool for WS in CC. Moreover, makespan is the utilized analytic measure with superior value. © 2024 IEEE.

关键词： scheduling algorithms

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An Improved Linux Priority scheduling Method Based on XGBoost 20

An Improved Linux Priority Scheduling Method Based on XGBoos...

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20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2024

作者： Yang, Ningke Shu, Xinfeng Liang, Chen School of Computer Science and Technology Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9798350356328

In order to address the issue of excessive resource consumption due to frequent context switching when running a large number of compute-intensive tasks in high-load scenarios on Linux. The paper proposes a scheduling algorithm that utilizes eBPF programs to extract fine-grained data such as process memory usage, execution time, read/write rates, etc. This data is then used to construct a dataset, and an XGBoost algorithm model is employed to predict the future resource consumption of processes. Simultaneously, based on the characteristics of binary classification and multi-classification tasks in the XGBoost algorithm, tasks are assigned different scheduling priorities according to CPU utilization rates. Tasks of corresponding types are then executed based on CPU status before the priority scheduling algorithm is *** comparisons reveal that under similar conditions, reducing the overhead of context switching results in a 1.03% improvement in overall task execution time and enhances CPU running efficiency. Consequently, it is concluded that this improved Linux priority scheduling method based on XGBoost can enhance execution efficiency when running numerous compute-intensive tasks in high-load environments. © 2024 IEEE.

关键词： scheduling algorithms

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Application of Artificial Intelligence in Optimal scheduling of Light Storage and Charging Microgrid Parks

Application of Artificial Intelligence in Optimal Scheduling...

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2024 International Conference on New Power System and Power Electronics, NPSPE 2024

作者： Hu, Weifeng Gu, Yunchang Zhang, Yuchen Yao, Jianqi State Grid Zhejiang Electric Power Co. Ltd Cixi Power Supply Company Ningbo China

ISBN: (纸本)9798350389869

This study explores the application of artificial intelligence technology in the optimization and scheduling of photovoltaic storage and charging microgrid parks. By analyzing the characteristics and requirements of microgrids and combining intelligent algorithms, a scheduling strategy based on Deep Q-Network (DQN) algorithm is proposed. During the experimental phase, a detailed evaluation was conducted through a series of experiments. In the comparative experiment of system operating costs, the total 30 day operating cost based on DQN algorithm was ¥ 15000, significantly lower than that of genetic algorithm (GA) and linear programming (LP). Secondly, in the experiment of renewable energy utilization rate, the average utilization rate of DQN algorithm reached 98.5%. In the supply-demand balance experiment, the average balance index of DQN algorithm was 0.968. Finally, in the convergence speed experiment of the DQN algorithm, the average number of convergence iterations was only 50. From experimental data, DQN algorithm has significant advantages in optimizing scheduling, which can more efficiently reduce costs, improve renewable energy utilization, enhance supply-demand matching, and have a faster convergence speed. © 2024 IEEE.

关键词： scheduling algorithms

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Research on Intelligent Algorithm Design and Performance Evaluation Model for New Energy scheduling

Research on Intelligent Algorithm Design and Performance Eva...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Yang, Yueping Tan, Zhi Fei, Wei Chen, Yu Zhou, Ningyi Liu, Huajun Ningbo Power Supply Company Zhejiang Electric Power Co. Ltd. Ningbo China Smart Energy Co. Ltd Ningbo China

ISBN: (纸本)9798331527624

In this paper, a new energy scheduling system based on improved grey model algorithm is proposed, and its performance is evaluated comprehensively. Firstly, aiming at the uncertainty and volatility problems in new energy scheduling, this paper designs an improved grey model algorithm that integrates historical data and real-time information to improve prediction accuracy and scheduling efficiency. Then this paper introduces the application process of this algorithm in new energy scheduling system in detail, and verifies its effectiveness through model simulation experiment. The experimental results show that the proposed algorithm has significant advantages in improving energy efficiency, reducing operation cost, and enhancing system stability. In addition, people also set up a complete performance evaluation system, and carried out quantitative analysis and evaluation of each index of the algorithm. This study not only provides a new theoretical support and technical means for the field of new energy dispatching, but also provides a useful reference for the future development of related fields. © 2024 IEEE.

关键词： scheduling algorithms

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Resilient scheduling of Moldable Parallel Jobs to Cope With Silent Errors

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IEEE TRANSACTIONS ON COMPUTERS 2022年第7期71卷 1696-1710页

作者： Benoit, Anne Le Fevre, Valentin Perotin, Lucas Raghavan, Padma Robert, Yves Sun, Hongyang Ecole Normale Super Lyon LIP Lab F-69342 Lyon France Barcelona Supercomp Ctr Barcelona 08034 Spain Vanderbilt Univ Nashville TN 37235 USA Univ Tennessee Innovat Comp Lab Knoxville TN 37996 USA Univ Kansas Dept Elect Engn & Comp Sci Lawrence KS 66045 USA

We study the resilient scheduling of moldable parallel jobs on high-performance computing (HPC) platforms. Moldable jobs allow for choosing a processor allocation before execution, and their execution time obeys various speedup models. The objective is to minimize the overall completion time or the makespan, when jobs can fail due to silent errors and hence may need to be re-executed after each failure until successful completion. Our work generalizes the classical scheduling framework for failure-free jobs. To cope with silent errors, we introduce two resilient scheduling algorithms, Lpa-List and Batch-List, both of which use the List strategy to schedule the jobs. Without knowing a priori how many times each job will fail, Lpa-List relies on a local strategy to allocate processors to the jobs, while Batch-List schedules the jobs in batches and allows only a restricted number of failures per job in each batch. We prove approximation ratios for the two algorithms under several prominent speedup models (e.g., roofline, communication, Amdahl, power, monotonic, and a mix model). An extensive set of simulations is conducted to evaluate different variants of the two algorithms, and the results show that they consistently outperform some baseline heuristics. Overall, our best algorithm is within a factor of 1.6 of a lower bound on average over the entire set of experiments, and within a factor of 4.2 in the worst case.

关键词： Approximation algorithms Resource management Schedules scheduling algorithms Computational modeling Biological system modeling Heuristic algorithms Resilient scheduling parallel jobs moldable jobs speedup model failure scenario transient errors silent errors list schedule batch schedule approximation ratios

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