检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

6,808 篇 会议
1,802 篇 期刊文献
1 册 图书

馆藏范围

8,611 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,415 篇 工学
- 3,903 篇 计算机科学与技术...
- 1,643 篇 信息与通信工程
- 1,585 篇 软件工程
- 1,519 篇 电气工程
- 592 篇 控制科学与工程
- 336 篇 电子科学与技术（可...
- 305 篇 机械工程
- 194 篇 动力工程及工程热...
- 186 篇 交通运输工程
- 120 篇 仪器科学与技术
- 79 篇 航空宇航科学与技...
- 68 篇 生物工程
- 62 篇 冶金工程
- 47 篇 土木工程
- 45 篇 安全科学与工程
- 42 篇 建筑学
- 39 篇 网络空间安全
- 38 篇 环境科学与工程（可...
- 37 篇 力学（可授工学、理...
1,882 篇 管理学
- 1,763 篇 管理科学与工程(可...
- 1,430 篇 工商管理
- 222 篇 图书情报与档案管...
1,786 篇 理学
- 1,465 篇 数学
- 224 篇 系统科学
- 201 篇 统计学（可授理学、...
- 148 篇 物理学
- 90 篇 生物学
- 41 篇 化学
102 篇 经济学
- 100 篇 应用经济学
65 篇 法学
- 62 篇 社会学
49 篇 医学
35 篇 农学
27 篇 教育学
24 篇 文学
5 篇 艺术学
2 篇 军事学

主题

8,611 篇 scheduling algor...
1,060 篇 scheduling
571 篇 schedules
536 篇 resource managem...
520 篇 real-time system...
487 篇 cloud computing
448 篇 throughput
434 篇 heuristic algori...
390 篇 quality of servi...
377 篇 delays
317 篇 dynamic scheduli...
309 篇 optimization
307 篇 task analysis
265 篇 computational mo...
230 篇 simulation
219 篇 energy consumpti...
209 篇 bandwidth
208 篇 job shop schedul...
203 篇 servers
193 篇 algorithm design...

机构

26 篇 beijing universi...
25 篇 state key labora...
21 篇 university of ch...
18 篇 national mobile ...
15 篇 institute of com...
13 篇 hong kong polyte...
13 篇 purple mountain ...
12 篇 northeastern uni...
12 篇 college of compu...
11 篇 shanghai jiao to...
10 篇 college of compu...
10 篇 sun yat sen univ...
10 篇 georgia state un...
10 篇 school of softwa...
10 篇 university of el...
10 篇 scuola super san...
9 篇 tsinghua univers...
9 篇 school of electr...
9 篇 college of compu...
9 篇 department of el...

作者

21 篇 ghaderi javad
16 篇 baruah sanjoy
15 篇 guan nan
13 篇 yi wang
13 篇 gao hong
13 篇 buyya rajkumar
11 篇 anderson james h...
11 篇 xie zhiqiang
11 篇 jing liu
10 篇 wei hu
10 篇 wang wei
10 篇 li bo
10 篇 zhang jie
10 篇 wang yi
9 篇 zhang lei
9 篇 deng qingxu
9 篇 ying lei
9 篇 guo song
9 篇 hsu yu-pin
9 篇 shakkottai sanja...

语言

8,086 篇 英文
445 篇 其他
77 篇 中文
7 篇 西班牙文
4 篇 朝鲜文
2 篇 日文
1 篇 斯洛文尼亚文
1 篇 土耳其文

检索条件"主题词=Scheduling algorithms"

共 8611 条记录，以下是1621-1630 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Graph Coding Aided Deep Reinforcement Learning for Fault-tolerant Workflow scheduling

Graph Coding Aided Deep Reinforcement Learning for Fault-tol...

引用

International Conference on Communication Technology (ICCT)

作者： Jiangming Li Sen Li Jian Tan Siyu Cheng Dong Jin Shuangwu Chen Jian Yang University of Science and Technology of China Hefei China Guangxi Key Laboratory of Digital Infrastructure Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Multi-access Edge Computing (MEC), as a novel computing paradigm, aims to execute workflows at the edge, thereby minimizing service latency. However, due to the high failure rate of edge servers, how to ensure reliable execution of workflows and improve service quality is a challenge. To address this challenge, this paper proposes a novel Deep Reinforcement Learning (DRL) based fault-tolerant workflow scheduling algorithm. The algorithm consists of an encoder based on a Graph Attention Neural Network (GAT) and a two-layer decoder based on a Long Short-Term Memory (LSTM) network. The encoder models the workflow as a Directed Acyclic Graph (DAG), capturing the dependencies between subtasks and learning the inherent correlation among their states. The decoder takes into account the influence of predecessor tasks on successors and generates scheduling actions for all subtasks concurrently through multi-step decision-making. Simulation results demonstrate that the proposed algorithm effectively reduces workflow makespan and resource consumption while fulfilling workflow reliability requirements.

关键词： Fault tolerance Multi-access edge computing scheduling algorithms Simulation Fault tolerant systems Neural networks Deep reinforcement learning Decoding Servers Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Physiological Conversations For Detection and Prediction of Emotion Recognition Using scheduling Algorithm

Physiological Conversations For Detection and Prediction of ...

引用

Applied Intelligence and Computing (AIC), IEEE World Conference on

作者： R. Sathiyapriya R. Vanitha Department of Computer Science and Engineering IFET College of Engineering Villupuram Tamilnadu

ISBN: (数字)9798350384598

ISBN: (纸本)9798350384604

By anticipating behavioural patterns and preventing the spread of harmful memes, machine learning enhances psychology. Cutting-edge algorithms identify meme humour and assess its influence on communities. Psychology’s ability to forecast future behaviours and societal difficulties is enhanced by this combination. New tools are produced via interdisciplinary collaboration in computer science, data science, and psychology. This combination strengthens psychology’s capacity for accurate prediction and practical application. The combination of machine learning and psychology is expected to advance understanding of human behaviour. This synergy promotes interventions that improve mental health and the general well-being of society in addition to helping to fathom the intricacies of the mind.

关键词： Human computer interaction Emotion recognition Machine learning algorithms scheduling algorithms Psychology Collaboration Machine learning Predictive models Prediction algorithms Data processing

来源：评论

学校读者我要写书评

暂无评论

A Cluster scheduling Algorithm for Concurrent Tasks Based on Global Optimization and Differential Privacy

A Cluster Scheduling Algorithm for Concurrent Tasks Based on...

引用

International Conference on Electronic Engineering and Informatics (EEI)

作者： Quanxing Zhou Qiuxian Li College of Big Data Engineering Kaili University Kaili China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

This study addresses the challenge of efficiently scheduling concurrent Extract, Transform, Load (ETL) tasks in the era of big data. It introduces Aetsa (Advanced Efficient Task scheduling Algorithm), an algorithm that combines global optimization with differential privacy. Aetsa is designed to balance the IO load and real-time CPU usage of tasks while employing differential privacy techniques to safeguard data privacy. Additionally, Aetsa harnesses the Quartz framework to facilitate high-performance task scheduling. Experimental results indicate that Aetsa surpasses traditional strategies in terms of response time and task completion time, particularly in environments with high CPU utilization. Aetsa proves its effectiveness and reliability across various scenarios, offering an innovative solution for concurrent ETL task scheduling and ensuring dual optimization of scheduling efficiency and data privacy.

关键词： Differential privacy scheduling algorithms Transforms Big Data Real-time systems scheduling Time factors Security Optimization Testing

来源：评论

学校读者我要写书评

暂无评论

CVTSA: Cooperative VNF and Time-Slot scheduling Algorithm for NFV Orchestration

CVTSA: Cooperative VNF and Time-Slot Scheduling Algorithm fo...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Chenxi Liao Jia Chen Deyun Gao Xu Huang Jingjing Liu Shang Liu Dongsheng Qian School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Peng Cheng Laboratory Shenzhen China China Mobile Group Liaoning Company Limited Liaoning China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

A successful blend of network function virtualization (NFV) and software-defined networking (SDN) can offer flexible and varied network services, given the quick ascent of developing applications propelled by the next-generation 6G network vision. In NFV, the ordered execution of service functions that constitute emerging applications is modeled as service function chaining (SFC) and is no longer limited to traditional network functions. Nevertheless, concurrent demands for joint scheduling of network and computing resources with latency sensitivity in resource allocation frequently accompany these application demands. In this paper, we conduct SFC scheduling as an integer linear programming (ILP) problem to tackle this issue. Secondly, we provide a resource-aware SFC scheduling algorithm that combines VNF and timeslots. In order to increase the acceptance rate of latency-sensitive network services, it aims to optimize resource utilization while strictly adhering to application latency requirements by dynamically sensing the availability of resources under various time slots and, consequently, efficiently and collaboratively scheduling computing and network resources under spatiotemporal states. Experimental results demonstrate that the proposed algorithm not only maximizes resource utilization but also accommodates a larger number of latency-sensitive service requests.

关键词： Sensitivity scheduling algorithms Service function chaining Heuristic algorithms Computational modeling Routing Sensors

来源：评论

学校读者我要写书评

暂无评论

Optimizing Resource Management in Hadoop YARN for Efficient Allocation, Utilization, and scheduling

Optimizing Resource Management in Hadoop YARN for Efficient ...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： B N Arunakumari J M Suhas Abha Nair BMS Institute of Technology and Management Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The Hadoop YARN(Yet Another Resource Negotiator) resource manager plays a critical role in the efficient functioning of Hadoop clusters by managing resources and scheduling tasks. This research paper explores various improvements to the Hadoop YARN resource manager to enhance resource allocation, utilization, and scheduling. The objective is to tackle the challenges posed by contemporary big data applications and workloads, enhancing overall system performance and responsiveness. This is achieved through the implementation of a capacity scheduling algorithm, emphasizing resource pre-emption. The aim is to distinguish and enhance efficiency of Capacity scheduler compared to existing algorithms such as FIFO and Fair scheduling using grep algorithm, backed by a thorough study of the same.

关键词： scheduling algorithms File systems System performance Big Data applications scheduling Resource management Yarn

来源：评论

学校读者我要写书评

暂无评论

Prompt Palate: A Prompt-Based Restaurant Recommendation System with scheduling and Chatbot Integration

Prompt Palate: A Prompt-Based Restaurant Recommendation Syst...

引用

International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Vidula N.A T.Hemanth Babu V. Gopi Kiran Roshni M. Balakrishnan Sreebha Bhaskaran Dept.of Computer Science & Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

In today's fast-paced world, individuals often find themselves craving a culinary adventure but struggle to decide on the perfect restaurant to satisfy their desires. Traditional restaurant search platforms typically offer rigid filters such as location, cuisine, and price range, limiting users' ability to explore options tailored to their specific cravings or preferences. We introduce Prompt Palate, a novel prompt-based restaurant recommendation system that uses natural language processing (NLP) techniques to address this challenge. Prompt Palate allows users to input their culinary desires via human-like prompts whose details and preferences are extracted through NLP algorithms. Moreover, the integration of a chatbot interface enhances user engagement and provides additional information about recommended restaurants. Users can engage in interactive conversations with the chatbot to learn more about menu offerings, ambiance, and special features of preferred restaurants. Additionally, the chatbot facilitates food ordering directly from the recommended restaurants, streamlining the dining or home delivery experience. To ensure a seamless and uncrowded dining experience, we incorporate intelligent scheduling algorithms for efficient table management, staff allocation, and delivery coordination. These algorithms optimize resource allocation, minimize wait times, and prevent overcrowding, thereby enhancing customer satisfaction.

关键词： Limiting Filters scheduling algorithms Customer satisfaction Oral communication Chatbots Feature extraction Resource management Information technology Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Online Job scheduling for Energy Cost Optimization in Geo-Distributed Data Centers Considering Data Locality: A Multi-Agent Reinforcement Learning Approach

Online Job Scheduling for Energy Cost Optimization in Geo-Di...

引用

IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)

作者： Junyi Lang Xiaokang Zheng Yimeng Sun Zhaohao Ding Department of electrical and electronic engineering North China Electric Power University Beijing China

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

With the rapid growth of cloud computing, geo-distributed data centers are becoming more energy-intensive. Given the unique characteristics of computing jobs, they can be executed across data centers in different geographic locations to better utilize lower electricity prices. However, data locality is a crucial factor to be considered in this process, as it is a precondition for the execution of jobs. In this paper, we propose a multi-agent deep reinforcement learning-based job scheduling algorithm that addresses constraints such as data locality and job deadlines to achieve real-time scheduling of jobs and data across data centers to optimize energy costs. First, we formulate the data locality-aware job scheduling problem across geo-distributed data centers as a Partially Observable Markov Decision Process (POMDP). Then, we develop a multi-agent system where agents handle job scheduling and data transfer respectively. The job scheduling agent needs to consider data transfer conditions when taking actions, as the necessary data for job execution must be available before executing. These agents collaborate by sharing the reward function to optimize the scheduling strategy, reducing the overall energy costs of job execution and data transfer. Finally, we conduct numerical experiments to validate the effectiveness of our proposed scheduling method in reducing data center energy costs while maintaining high service quality.

关键词： Data centers Costs scheduling algorithms Heuristic algorithms Scalability Reinforcement learning Data transfer scheduling Robustness Optimization

来源：评论

学校读者我要写书评

暂无评论

Radar Task scheduling with Gaussian Random Shifted Start Time

Radar Task Scheduling with Gaussian Random Shifted Start Tim...

引用

IEEE National Conference on Radar

作者： Zhen Ding Petar Przulj Zhen Qu Peter Moo DRDC Ottawa Research Centre Radar Sensing and Exploitation Section Ottawa Canada

ISBN: (数字)9798350329209

ISBN: (纸本)9798350329216

A radar task scheduling algorithm, Gaussian random shifted start time (GRSST), is proposed. The algorithm shifts each task's start time by a Gaussian distribution instead of a uniform distribution within the time window which was used in the random shifted start time (RSST) algorithm. Each task's priority is used to calculate its distribution variance. The random search is not related to the priorities. A higher priority task will have a smaller variance, so that its movable range is less than that of a lower priority task. Similar to the RSST, multiple searches help to find the solution with the lowest cost. Monte Carlo simulations show that the GRSST reduces the cost significantly with much less searches, which saves a lot of computation time too. The GRSST with 50 searches provides a better solution which costs around 2 times less than the RSST with 350 searches. The GRSST's average computation time is reduced to 1ms from 7ms.

关键词： Costs Monte Carlo methods scheduling algorithms Radar Gaussian distribution scheduling Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Farmland Segmentation and Multiple Agricultural Machines Cooperative scheduling Method Under Sudden Disasters

Farmland Segmentation and Multiple Agricultural Machines Coo...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Guiping Dou Liruizhi Jia Shengquan Liu Cheng Zhang Yuan Liu Bo Kong School of Computer Science and Technology Xinjiang University Urumqi China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

With the rapid development of smart farm models, multi-machine collaborative operations are an important trend. Nevertheless, in the face of sudden disasters, the traditional multi-machine collaborative operations have unclear operation area allocations, simplistic path planning, and scheduling algorithms easily falling into the local optimal solution, resulting in low efficiency and inability to meet the task needs of urgent tasks. A multiple agricultural machine cooperative scheduling method based on farmland segmentation is proposed to solve these problems. The method first segmented large-scale farmland based on multiple machine task requirements to obtain location information for the segmented sub-regions. Next, to minimize the turning time in the headland, complete coverage path planning inside the field is planned to obtain the best coverage angle and the shortest operation time. Lastly, an optimal simulated annealing algorithm is employed to obtain the task allocation of agricultural machinery to minimize the longest working time. The simulation results show that the study has achieved optimization results. Under urgent tasks, the method can effectively schedule agricultural machine resources, ensuring task completion and generating a high-yield solution.

关键词： Smart agriculture scheduling algorithms Disasters Simulation Collaboration Simulated annealing Turning Path planning scheduling Resource management

来源：评论

学校读者我要写书评

暂无评论

Joint Power Control and Device scheduling in Federated Learning with Energy Harvesting

Joint Power Control and Device Scheduling in Federated Learn...

引用

International Conference on Communications, Signal Processing, and their Applications (ICCSPA)

作者： Boyuan Zhang Ning Lu Department of Electrical and Computer Engineering Queen's University Kingston ON Canada

ISBN: (数字)9798350384819

ISBN: (纸本)9798350384826

Federated Learning (FL) is emerging as a promising approach for enabling collaborative machine learning without centralizing data, particularly within Internet of Things (IoT) networks. Despite its potential, the challenge of reducing communication delay and energy consumption in client-server transmissions is considered a critical challenge in wireless network implementations of FL. Moreover, the capability of many IoT devices to harvest energy introduces a novel dimension to optimizing FL efficiency, which remains underexplored. In this paper, we present POLISH, a novel POwer controL, and devIce scheduling algorithm derived from an optimization problem designed to navigate a tripartite trade-off between minimizing communication delay (specifically, the transmission time for model updates), reducing total energy consumption, and maximizing device participation. Through simulations, POLISH has shown superior performance in reducing communication delay and energy consumption when compared to existing benchmarks, highlighting its effectiveness in enhancing FL performance in energy-constrained IoT networks.

关键词： Performance evaluation Energy consumption scheduling algorithms Federated learning Power control Signal processing algorithms Delays Internet of Things Energy harvesting Optimization

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 159 160 161 162 163 164 165 166 167 168 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：