检索结果-内蒙古大学图书馆

Path Generation Method of UAV Autopilots Using max-min algorithm

JOURNAL OF INFORMATION PROCESSING SYSTEMS 2018年第6期14卷 1457-1463页

作者： Kwak, Jeonghoon Sung, Yunsick Dongguk Univ Dept Superintelligence Lab Seoul South Korea Dongguk Univ Dept Multimedia Engn Seoul South Korea

In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has found widespread application across a diverse range of fields and is also utilized for controlling unmanned aerial vehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult for the user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs a flight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally fly straight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVs may collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust the generated path taking the locations of the obstacles into consideration. This paper proposes a natural path generation method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, the proposed method generates paths that allow UAVs to avoid obstacles.

关键词： Autopilot max-min algorithm Path Generation Unmanned Aerial Vehicle

来源：评论

学校读者我要写书评

暂无评论

Fair-Share Methods for Scheduling Scientific Workflows in Cloud 20

Fair-Share Methods for Scheduling Scientific Workflows in Cl...

引用

20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)

作者： Aldabaybah, Balqees Alrawashdeh, Tawfiq Butt, Talal Ashraf Almiani, Khaled Al Hussein Tech Univ Amman Jordan Univ Jordan Amman Jordan Al Hussein Bin Talal Univ Maan Jordan Higher Coll Technol Fujairah U Arab Emirates

ISBN: (纸本)9798350319439

Efficient execution of scientific workflows in cloud environments, specifically using virtual machines (VMs) necessitates the optimal allocation of resources. However, striking the delicate balance between over-renting and under-renting resources poses a significant challenge, impacting cost and execution time. To address this issue, this paper introduces two fair-share-based scheduling methods that bridge the gap between scheduling scientific workflows in the cloud and traditional fair-share scheduling problems. These methods encompass three crucial steps: partitioning, resource allocation, and scheduling. The workflow is divided into distinct partitions during the partitioning step, with computational requirements calculated for each partition. The resource allocation step distinguishes the two methods, wherein a fair distribution of VMs among partitions is pursued. The proposed methods employ the strategies of max-min and proportional fair share to ensure fair resource allocation. Subsequently, the scheduling step determines the execution schedule based on the allocated resources. Experimental results demonstrate the significant improvements achieved by the proposed methods, enhancing resource utilization and minimizing the elusive concept of makespan. This research paper describes the complexities associated with resource management in cloud-based scientific workflows and provides practical solutions to optimize execution efficiency in these environments.

关键词： algorithms cloud computing fair-share division scientific workflow scheduling max-min algorithm

来源：评论

学校读者我要写书评

暂无评论

A New Modified max-min Workflow Scheduling algorithm for Cloud Environment 15

A New Modified Max-min Workflow Scheduling Algorithm for Clo...

引用

15th International Conference on Electronics, Computer and Computation (ICECCO)

作者： Auna, Shuaibu Yau Ambursa, Faruku Umar Ibrahim, Abdulhakeem Bayero Univ Kano Fac Comp Sci & Informat Technol Dept Comp Sci Kano Nigeria Bayero Univ Kano Fac Comp Sci & Informat Technol Dept Informat Technol Kano Nigeria Fed Univ Fac Sci Dept Comp Sci Birnin Kebbi Nigeria

ISBN: (纸本)9781728151601

In cloud computing, Service rendering is achieved through virtualization and the use of very large scalable resources where users access services by paying for the share of resources used by them. Several workflow scheduling techniques have been proposed for efficient scheduling. max-min approach is prominent among them, its features includes efficiency and the ability to guarantee optimal or near optimal solution because of its heuristic nature. Several enhancement to its functionalities have been proposed in the literature and works are still ongoing for improving it. This paper proposed a solution by minimizing total execution time where workflow tasks length are invariably considered before proper scheduling. Our proposed work is compared with standard max-min scheduling scheme. The proposed scheme outperforms the standard scheme;two realistic scientific workflows were used as test data for the simulation.

关键词： Cloud Computing Workflow Scheduling Heuristic algorithms max-min algorithm

来源：评论

学校读者我要写书评

暂无评论

Task-scheduling algorithm based on Improved Genetic algorithm in Cloud Computing Environment

引用

RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2021年第1期14卷 13-19页

作者： Weiqing, G. E. Cui, Yanru Univ Technol City Coll Dongguan Dongguan Guangdong Peoples R China

Background: min-min and max-min algorithms were combined on the basis of the traditional genetic algorithm to make up for its shortcomings. Methods: In this paper, a new cloud computing task-scheduling algorithm that introduces min-min and max-min algorithms to generate initialization population, selects task completion time and load balancing as double fitness functions, and improves the quality of initialization population, algorithm searchability and convergence speed, was proposed. Results: The simulation results proved that the cloud computing task-scheduling algorithm was superior to and more effective than the traditional genetic algorithm. Conclusion: The paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

关键词： Cloud computing genetic algorithm task scheduling min-min algorithm max-min algorithm EIGA scheduling

来源：评论

学校读者我要写书评

暂无评论

Optimization of Tasks in Cloud Computing Based on max-min, min-min and Priority 4

Optimization of Tasks in Cloud Computing Based on MAX-MIN, M...

引用

4th International Conference on Web Research (ICWR)

作者： Derakhshan, Majid Bateni, Zohreh Univ Sci & Culture Comp Engn Tehran Iran

ISBN: (纸本)9781538653647

Considering the growing use of cloud computing and the need for optimal use of resources in the cloud, and attention to users that pay for services they use based on their pay-as-you-go basis, There should be a quicker way for users to decrease the user's waiting time and task's waiting time. The main purpose of this paper is to provide an optimal algorithm using the advantages of the two traditional min-min and max-min algorithms. The other point that follow in this algorithm (TOMMP) is the priority of the tasks. There are a lot of scheduling algorithms in the world today, but the priority given to the tasks has been neglected and overlooked in most algorithms. In this algorithm, priority is firstly selected for tasks based on a prioritization algorithm, and then using the median number to decide which one of the min-min or max-min algorithms is to be used. It should be noted that according to the TOMMP algorithms, its waiting time is lower than comparisons of the compared algorithms and is shown to be better than the comparable algorithms.

关键词： TOMMP algorithm optimal scheduling algorithm scheduling algorithm cloud scheduling algorithm min-min algorithm max-min algorithm cloud computing

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Clustering algorithm Based on CFSFDP 33

An Adaptive Clustering Algorithm Based on CFSFDP

引用

33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yang, Feng Cao, Jinming Zhou, Kuang Zhang, Pengyan Wang, Yongting Northwestern Polytech Univ Sch Automat Xian Shaanxi Peoples R China Northwestern Polytech Univ Sch Nat & Appl Sci Xian Shaanxi Peoples R China Sci & Technol Electroopt Control Luoyang Peoples R China

ISBN: (纸本)9781538672556

The main idea of the recent proposed clustering by fast search and find of density peaks (CFSFDP) clustering algorithm depicts the cluster center with the local density and distance and it achieves significant effects in typical applications. But it can't select the cluster centers adaptively. Therefore, an improved CFSFDP algorithm is proposed in this paper, which determines the cluster centers by the max-min algorithm. First, the max-min algorithm is introduced to obtain the number of categories. Then the local density and distance information is used to determine the cluster centers as do in CFSFDP algorithm. It can not only adaptively obtain categories number of the data, but also obtain the corresponding clustering centers. The simulation results show that the proposed algorithm can find the number of categories and find the cluster centers. Meanwhile, it can find the cluster centers which are hard to be obtained through decision diagram.

关键词： clustering CFSFDP algorithm adaptively max-min algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of Improved Genetic algorithm in the Channel Allocation of OFDMA System

Application of Improved Genetic Algorithm in the Channel All...

引用

3rd International Symposium on Computer, Consumer and Control (IS3C)

作者： Wang, Zhongli Ma, Xin Zhang, Chaodong Fu, Tianhao Beihua Univ Coll Elect & Informat Engn Jilin 132013 Jilin Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China Univ Elect Sci & Technol China Sch Phys Elect Chengdu 610051 Peoples R China

ISBN: (纸本)9781509030712

OFDMA (Orthogonal Frequency Division Multiple Access) is the key technology of the fourth-generation mobile communication and has been applied to many communication standards. In this paper, genetic algorithm (GA) is applied to channel allocation of OFDMA system and is improved from three aspects: initial population, fitness function and user fairness. At the same time, combining improved genetic algorithm with greedy algorithm, max-min algorithm to do further improvement. Throughsimulation and comparison, author has found improved genetic algorithm can be used to compensate for defects of other algorithms in channel allocation, such as improve system throughput, ensure user fairness and reduce system time, which makes channel allocation scheme better and has certain practical application value in wireless communication system.

关键词： Genetic algorithm OFDMA channel allocation greedy algorithm max-min algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of Improved Genetic algorithm in the Channel Allocation of OFDMA System

Application of Improved Genetic Algorithm in the Channel All...

引用

International Symposium on Computer, Consumer and Control

作者： Zhongli Wang Xin Ma Chaodong Zhang Tianhao Fu College of Electrical and Information Engineering Beihua University School of Traffic and Transportation Beijing Jiaotong University School of Physical Electronics University of Electronic Science and Technology of China

ISBN: (纸本)9781509030729

关键词： Genetic algorithm OFDMA Channel allocation Greedy algorithm max-min algorithm

来源：评论

学校读者我要写书评

暂无评论

IMPROVED max-min HEURISTIC MODEL FOR TASK SCHEDULING IN CLOUD

IMPROVED MAX-MIN HEURISTIC MODEL FOR TASK SCHEDULING IN CLOU...

引用

International Conference on Green Computing, Communication and Conservation of Energy (ICGCE)

作者： Devipriya, S. Ramesh, C. Bannari Amman Inst Technol Sathyamangalam India

ISBN: (纸本)9781467361255

Cloud computing is the use of computing resources that are delivered as a service over a network. It supplies a high performance computing based on protocols which allows shared computation and storage over long distances. In cloud computing, many tasks need to execute at a time by the available resources in order to achieve better performance, minimum completion time, shortest response time, resource utilization etc [4]. Because of these different factors, we need to design, develop, and propose a scheduling algorithm for the proper allocation of tasks to the resources. In this paper, a simple modification of max-min algorithm is proposed. This algorithm is built based on RASA algorithm and the concept of max-min strategy. An Improved max-min algorithm is developed to outperform scheduling process of RASA in case of total complete time for all submitted jobs. Proposed max-min algorithm is based on expected execution time instead of complete time. So the scheduling tasks within cloud environment using Improved max-min can achieve lower makespan rather than original max-min.

关键词： Cloud computing max-min algorithm min-min RASA algorithm makespan

来源：评论

学校读者我要写书评

暂无评论

Geodesical Codebook Design for Precoded MIMO Systems

引用

IEEE COMMUNICATIONS LETTERS 2009年第10期13卷 773-775页

作者： Schober, K. Janis, P. Wichman, R. Aalto Univ FIN-02015 Helsinki Finland

We propose a numerical method for finding packings of multiple-input and multiple-output (MIMO) semi-unitary precoding matrices in Grassmannian manifolds with different metrics. The proposed expansion-compression algorithm (ECA) is practical, simple and produces efficient packings without the need for a sophisticated initialization. With chordal distance metric, the algorithm tends to converge into a degenerated point constellation, where two points contain identical as well as orthogonal columns and distance between them cannot increase further along geodesic. Therefore, we alternate between max-min and min-max clustering parts of ECA algorithm, where the latter prevents degenerated constellations. With Fubini-Study distance metric, the algorithm converges to best known packings without extra min-max processing.

关键词： Codebook design max-min algorithm geodesic Grassmannian subspace packing MIMO multi-antenna systems

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：