检索结果-内蒙古大学图书馆

3rd International Conference on Machine Learning and Data Engineering, ICMLDE 2024

作者： Behera, Ranjit Kumar Manjula Gururaj, H. Roy, Diptendu Sinha Tripathy, Siba Computer Science and Engineering Silicon University Bhubaneswar India Information Science and Engineering NMAM Institute of Technology NITTE University Karnataka Mangalore India Computer Science and Engineering NIT Meghalaya Shilong India Computer Science and Engineering SOA University Bhubaneswar India

Fog computing also known as Edge computing is emerging as an attention gaining computing technology for providing Cloud services to IoT applications which requires instantaneous and real-time responses. In absence of an efficient and systematic task scheduling algorithm, Fog with limited computing power and resources may fail to handle high traffic and hence may result in delays. Although many studies have been carried out and many task scheduling models has been proposed by researchers pertaining to different application areas, many of these models have some inherent drawbacks like increase in response time and execution time, as well as migration delays which hinders these models from being the most competent ones particularly the case of delay sensitive IoT applications. Hence, being mindful of the mentioned issues and challenges, in this paper, an efficient Completion Time Aware Task scheduling (CTATS) algorithm has been proposed at Fog Computing layer. We have implemented reinforcement learning (RL), a machine learning strategy that is environment-adaptive, to enhance performance with respect to predict the suitable VM for a delay sensitive task and for this we have used our own dataset. To check the efficacy of the proposed model, the simulation has been carried out using CloudSim simulator and the obtained results is compared with the existing models for the comparison of average response time and overall completion time. Obtained results shows the superior efficacy of CTATS over the QBT and Prioritized Scheduled Mechanism. © 2025 The Author(s).

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

A New Multiple Agricultural Machinery scheduling via a Genetic Algorithm Improved by Large Neighborhood Search Method

A New Multiple Agricultural Machinery Scheduling via a Genet...

引用

Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Xin Feng Xingyu Chen Lvwen Huang Pan Pu Northwest A&F University Yangling Shaanxi China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

Aiming at the problem that the commonly used scheduling algorithm in the process of intelligent scheduling of agricultural machinery are easy to fall into local optimum, a multiple agricultural machinery scheduling operation method with a genetic algorithm improved by large neighborhood search method is proposed. To begin with, focusing on the shortcomings of high cost and inefficient of agricultural machinery scheduling, an agricultural machinery scheduling model with a time window is constructed, with the optimization goal of least total operating cost. Subsequently, a genetic algorithm improved by large neighborhood search algorithm is designed. Through selection, crossover, mutation and local search, better solutions are continuously sought. By adding adaptability to the crossover and mutation processes and simultaneously improving the large neighborhood search operator, a more efficient and flexible search for the optimal solution is achieved. Finally, comparative experiments with six commonly used algorithms are carried out based on real data sets. The experimental results show that even if the number of farmlands increases, the scheduling cost of the proposed algorithm still maintains a significant advantage. When the number of farmlands is 17, 27 and 37, the total cost is reduced by an average of 171.40, 305.28 and 460.39 CNY respectively. Moreover, the advantages of this algorithm in terms of convergence results and speed are more prominent.

关键词： Smart agriculture Adaptation models Costs scheduling algorithms Search methods Optimal scheduling Agricultural machinery scheduling Genetic algorithms Convergence

来源：评论

学校读者我要写书评

暂无评论

MATCH: Real-Time scheduling of Multiple and Parallel Data Copies in Heterogeneous Architectures

MATCH: Real-Time Scheduling of Multiple and Parallel Data Co...

引用

IEEE Symposium on Real-Time and Embedded Technology and Applications

作者： Yinchen Ni Yuankai Xu Jintao Chen Jing Li Chris Gill Xuan Zhang Yier Jin An Zou Shanghai Jiao Tong University New Jersey Institute of Technology Washington University in St.louis University of Florida

ISBN: (数字)9798331543402

ISBN: (纸本)9798331543419

In recent years, multiple data copies become popular in heterogeneous computing architectures. They enable parallel data transfer among diverse processing units. Tasks executed on such heterogeneous architectures often exhibit heightened re-source competitions and intricate task dependencies, posing challenges in meeting strict timing constraints. Due to the dominant roles of data copies in the heterogeneous architecture, effective scheduling and tight response time analysis could contribute to the timing performance of the entire heterogeneous computing system. In this work, we introduce MATCH, which offers realtime scheduling and end-to-end response time analysis for the multiple parallel data copies that are popular in mainstream heterogeneous architectures. We first identify the aggravated resource competition and task dependency from multiple data copies and comprehensive task execution patterns. Then, we provide a real-time scheduling strategy and cross-granularity schedulability analysis to deal with resource competition and task dependency. Extensive evaluation demonstrates that efficient scheduling and analysis on multiple parallel data copies can significantly improve the schedulability by 55.5%-144.4%. Additionally, experiments conducted on various scales of heterogeneous systems demonstrate that MATCH can significantly reduce pessimism in response time analysis by up to 22.8%-57.5%. Importantly, the proposed approach is compatible with existing scheduling approaches that do not consider multiple parallel data copies and are readily applied to off-the-shelf heterogeneous computing systems.

关键词： Schedules Processor scheduling scheduling algorithms Computer architecture Real-time systems Heterogeneous networks scheduling Timing Time factors Servers

来源：评论

学校读者我要写书评

暂无评论

ClubHeap: A High-Speed and Scalable Priority Queue for Programmable Packet scheduling 22

ClubHeap: A High-Speed and Scalable Priority Queue for Progr...

引用

22nd USENIX Symposium on Networked Systems Design and Implementation, NSDI 2025

作者： Chen, Zhikang Song, Haoyu Zhang, Zhiyu Xu, Yang Liu, Bin Tsinghua University China Futurewei Technologies United States Fudan University China

ISBN: (纸本)9781939133465

While PIFO is a powerful priority queue abstraction to support programmable packet scheduling in network devices, the efficient implementation of PIFO faces multiple challenges in performance and scalability. The existing solutions all fall short of certain requirements. In this paper, we propose ClubHeap to address the problem. On the one hand, we develop a novel hardware-friendly heap data structure to support faster PIFO queue operations that can schedule a flow in every clock cycle, reaching the theoretical lower bound;on the other hand, the optimized hardware architecture reduces the circuit complexity and thus enables a higher clock frequency. The end result is the best scheduling performance in its class. Combined with its inherently better scalability and flexibility, ClubHeap is an ideal solution to be built in programmable switches and SmartNICs to support various scheduling algorithms. We build an FPGA-based hardware prototype and conduct a thorough evaluation by comparing ClubHeap with the other state-of-the-art solutions. ClubHeap also allows graceful trade-offs between throughput and resource consumption through parameter adjustments, making it adaptable on different target devices. © 2025 by The USENIX Association All Rights Reserved.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

ESBMC v7.7: Efficient Concurrent Software Verification with scheduling, Incremental SMT and Partial Order Reduction: (Competition Contribution) 31th

ESBMC v7.7: Efficient Concurrent Software Verification with ...

引用

31st International Conference on Tools and algorithms for the Construction and Analysis of Systems, TACAS 2025, which was held as part of the International Joint Conferences on Theory and Practice of Software, ETAPS 2025

作者： Wu, Tong Li, Xianzhiyu Manino, Edoardo Menezes, Rafael Sá Gadelha, Mikhail R. Xiong, Shale Tihanyi, Norbert Petoumenos, Pavlos Cordeiro, Lucas C. The University of Manchester Manchester United Kingdom Federal University of Amazonas Manaus Brazil Igalia A Coruña Spain Eötvös Loránd University Budapest Hungary Arm® Cambridge United Kingdom

ISBN: (纸本)9783031906596

ESBMC v7.7 improves the verification of concurrent C programs by incorporating techniques such as dynamic thread scheduling, incremental SMT solving, and partial order reduction (POR). These improvements enhance the tool’s performance, particularly in exploring complex multi-threaded executions. The new scheduler prioritizes higher-thread identifiers during context switches, which helps explore deeper program states. The use of incremental SMT solving and a refined POR algorithm reduces the exploration of unreachable interleavings and redundant states. These updates enable ESBMC to detect bugs faster, making it a more effective tool for ensuring the safety of multi-threaded applications. © The Author(s) 2025.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Fuzzy-Based Two-Layered HRRN CPU Scheduler: FHRRN

引用

International Journal of Fuzzy System Applications 2022年第1期11卷 1-20页

作者： Raheja, Supriya Amity University Noida India

Fuzzy-based CPU scheduler has become an emerging component of an operating system. It can handle the imprecise nature of parameters used in scheduler. This paper introduces an adaptive fuzzy-based highest response ratio next CPU scheduler which is an extension of conventional CPU scheduler. The proposed scheduler works in two layers. At the first layer, a fuzzy inference system is defined that handles the uncertainties of parameters, and at the second layer, an adaptive scheduling algorithm is used to schedule each task. The proposed scheduler intelligently generates the response ratio for each ready-to-run task which makes the system adaptive at run time. The work is compared with the conventional highest response ratio next scheduling and the existing fuzzy highest ratio next scheduling algorithms. Results validate the better performance of proposed scheduler. The proposed scheduler also provides comparable results with respect to shortest job-first scheduling and shortest remaining task-first scheduling algorithms. Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Enhancing investigations in data migration and security using sequence cover cat and cover particle swarm optimization in the fog paradigm

引用

International Journal of Intelligent Networks 2022年 3卷 204-212页

作者： Saravanan, T. Saravanakumar, S. Department of CSE GITAM University Bengaluru India Department of CSE Jain University Bengaluru India

In recent years, fog and mobile edge computing have grown rapidly due to the large amount of data generated by the Internet of Thing (IoT) devices. It provides a variety of services within the end user IoT environment, but suffers from inefficient scheduling, which results in more significant delays than cloud computing. In this research we propose a data migration procedure that beats the metrics of delay, response time, and load balancing rate in the fog computing paradigm. It is possible to reduce the amount of replicated and integrated data by using Sequence Cover Cat Swarm Optimization (SCCSO) and Sequence Cover Particle Swarm Optimization (SCPSO) by using appropriate Virtual machines (VMs) which lock highly used machines and give service to low used machines in cloud communication storage.;this allows us to obtain resources efficiently in the fog environment. After being tested in the iFogsim climate, The protocols performed better in the iFogsim climate in terms of response time, scheduling time load balancing rate and delay than the other scheduling algorithms. © 2022 The Authors

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Reproducibility Report for ACM SIGMOD 2023 Paper: "MorphStream: Adaptive scheduling for Scalable Transactional Stream Processing on Multicores"

Reproducibility Report for ACM SIGMOD 2023 Paper: "MorphStre...

引用

2024 International Conference on Management of Data, SIGMOD ARI Reports 2024

作者： Singh, Ayushi Helmer, Sven Mao, Yancan Zhao, Jianjun Zhang, Shuhao Netflix Los GatosCA United States University of Zurich Zurich Switzerland National University of Singapore Singapore Singapore Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798400711794

We were able to reproduce the findings of the original paper. This includes performance comparisons with other systems, measurements of throughput and latency for different workloads and scheduling strategies, handling of abort decisions, and scalability comparisons. In total, this involves sixteen different figures in the original paper that were reproduced. © 2024 Copyright held by the owner/author(s).

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Locality-aware Fair scheduling in LLM Serving

arXiv

引用

arXiv 2025年

作者： Cao, Shiyi Wang, Yichuan Mao, Ziming Hsu, Pin-Lun Yin, Liangsheng Xia, Tian Li, Dacheng Liu, Shu Zhang, Yineng Zhou, Yang Sheng, Ying Gonzalez, Joseph Stoica, Ion UC Berkeley United States LMSYS

Large language model (LLM) inference workload dominates a wide variety of modern AI applications, ranging from multi-turn conversation to document analysis. Balancing fairness and efficiency is critical for managing diverse client workloads with varying prefix patterns. Unfortunately, existing fair scheduling algorithms for LLM serving, such as Virtual Token Counter (VTC), fail to take prefix locality into consideration and thus suffer from poor performance. On the other hand, locality-aware scheduling algorithms in existing LLM serving frameworks tend to maximize the prefix cache hit rate without considering fair sharing among clients. This paper introduces the first locality-aware fair scheduling algorithm, Deficit Longest Prefix Match (DLPM), which can maintain a high degree of prefix locality with a fairness guarantee. We also introduce a novel algorithm, Double Deficit LPM (D2LPM), extending DLPM for distributed setup that can find a balance point among fairness, locality, and load-balancing. Our extensive evaluation demonstrates the superior performance of DLPM and D2LPM in ensuring fairness while maintaining high throughput (up to 2.87× higher than VTC) and low per-client (up to 7.18× lower than state-of-the-art distributed LLM serving system) latency. Copyright © 2025, The Authors. All rights reserved.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Flexible flow shop scheduling with limited buffers based on model-driven differential evolution algorithm

Multi-objective Flexible flow shop scheduling with limited b...

引用

2025 2nd International Conference on algorithms, Software Engineering and Network Security (ASENS)

作者： Lixin Liang Zhifeng Hao School of Mathematics and Computer Science Shantou University Shantou China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

The multi-objective flexible flow shop scheduling problem with limited buffers (MO-FFSS-LB) is widely encountered in modern manufacturing systems. However, the existence of limited buffers greatly increases the complexity of job scheduling and needs to consider job completion time, replacement costs of different recipes, and dynamic buffer balancing simultaneously. To address the challenge of MO-FFSS-LB, this paper proposes a model-driven differential evolution (MDE) algorithm. Firstly, it designs a multi-layer coding mechanism to represent the solution of the problem according to the characteristics of the scheduling problem and then introduces an initialization mechanism to improve the quality of the initial solution and the solving efficiency. Moreover, the proposed MDE utilizes a machine learning-based model trained on historical scheduling data to approximate fitness, enabling rapid population evolution. To further improve the convergence speed and solution quality, a neighborhood search-based local optimization strategy and dynamically adjusted crossover rates and mutation factors strategy are introduced, enhancing the algorithm’s adaptability to complex scheduling problems. Experimental results demonstrate that the MDE algorithm can generate high-quality solutions for the MO-FFSS-LB and outperforms existing traditional scheduling algorithms in several performance metrics. This research not only provides an effective optimization tool for solving complex scheduling problems with limited buffer constraints but also offers new insights and methods for theoretical research and practical applications in related fields.

关键词： Job shop scheduling Machine learning algorithms scheduling algorithms Heuristic algorithms Software algorithms Dynamic scheduling Approximation algorithms Encoding Data models Optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：