USING CLOUD PLATFORMS TO BUILD DISTRIBUTED LEARNING MANAGEMENT SYSTEMS

Volodymyr Sokol, Pavlo Yuriiovych Sapronov, M. Bilova
{"title":"USING CLOUD PLATFORMS TO BUILD DISTRIBUTED LEARNING MANAGEMENT SYSTEMS","authors":"Volodymyr Sokol, Pavlo Yuriiovych Sapronov, M. Bilova","doi":"10.20998/2079-0023.2020.02.06","DOIUrl":null,"url":null,"abstract":"Distributed systems have problems with downtime, data loss during malfunctions, scalability and efficient use of computing resources. At the same time in the learning and training process, the use of a distributed system has the advantage of data processing: storage of information about students, construction of training courses, verification of passed material, etc. The problems of scaling and efficient use of resources in distributed learning management systems are investigated in this research. Cloud platforms for hosting the system, such as Amazon Web Services, Microsoft Azure, Google Cloud Platform and DigitalOcean are reviewed. Problems and features of a scalability in cloud computing are discussed. Methods, scaling and load balancing algorithms for the efficient use of computing resources are proposed. According to the list of advantages, the DigitalOcean platform was selected for the investigation. DigitalOcean provides cloud servers that can be used for quick creation of the new virtual machines for the projects. These servers allow to fully control the web hosting environment at the same time that the user pays only for the resources used. The main goal of DigitalOcean is to use a solid-state drive (SSD) to create a user-friendly platform that will allow clients to migrate projects to and from the cloud, increasing productivity with high speed and efficiency. As a result of analyzing information on existing technologies, approaches and methods for using cloud platforms in distributed systems, they have been applied to develop a solution to reduce downtime for a distributed adaptive Learning Management System (LMS). It is concluded that the use of cloud platforms for the construction of distributed LMS a practice that allows to use only the required amount of computing capacity. It is proven, that the implementation of the proposed solution into the work of adaptive LMS will improve its efficiency by reducing the time of the content delivering.","PeriodicalId":391969,"journal":{"name":"Bulletin of National Technical University \"KhPI\". Series: System Analysis, Control and Information Technologies","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of National Technical University \"KhPI\". Series: System Analysis, Control and Information Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20998/2079-0023.2020.02.06","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Distributed systems have problems with downtime, data loss during malfunctions, scalability and efficient use of computing resources. At the same time in the learning and training process, the use of a distributed system has the advantage of data processing: storage of information about students, construction of training courses, verification of passed material, etc. The problems of scaling and efficient use of resources in distributed learning management systems are investigated in this research. Cloud platforms for hosting the system, such as Amazon Web Services, Microsoft Azure, Google Cloud Platform and DigitalOcean are reviewed. Problems and features of a scalability in cloud computing are discussed. Methods, scaling and load balancing algorithms for the efficient use of computing resources are proposed. According to the list of advantages, the DigitalOcean platform was selected for the investigation. DigitalOcean provides cloud servers that can be used for quick creation of the new virtual machines for the projects. These servers allow to fully control the web hosting environment at the same time that the user pays only for the resources used. The main goal of DigitalOcean is to use a solid-state drive (SSD) to create a user-friendly platform that will allow clients to migrate projects to and from the cloud, increasing productivity with high speed and efficiency. As a result of analyzing information on existing technologies, approaches and methods for using cloud platforms in distributed systems, they have been applied to develop a solution to reduce downtime for a distributed adaptive Learning Management System (LMS). It is concluded that the use of cloud platforms for the construction of distributed LMS a practice that allows to use only the required amount of computing capacity. It is proven, that the implementation of the proposed solution into the work of adaptive LMS will improve its efficiency by reducing the time of the content delivering.
利用云平台构建分布式学习管理系统
分布式系统在停机时间、故障期间的数据丢失、可伸缩性和计算资源的有效使用等方面存在问题。同时在学习和培训过程中,采用分布式系统具有数据处理的优势:学员信息的存储、培训课程的构建、通过材料的验证等。本文研究了分布式学习管理系统中资源的可扩展性和高效利用问题。对用于托管系统的云平台,如Amazon Web Services、Microsoft Azure、Google Cloud Platform和DigitalOcean进行了审查。讨论了云计算中可扩展性的问题和特点。提出了有效利用计算资源的方法、扩展和负载平衡算法。根据优势列表,选择DigitalOcean平台进行调查。DigitalOcean提供云服务器,可用于快速创建项目的新虚拟机。这些服务器允许完全控制网络托管环境,同时用户只需为所使用的资源付费。DigitalOcean的主要目标是使用固态硬盘(SSD)创建一个用户友好的平台,允许客户将项目迁移到云或从云迁移,以高速和高效的方式提高生产力。通过分析在分布式系统中使用云平台的现有技术、方法和方法的信息,我们将它们应用于开发一种解决方案,以减少分布式自适应学习管理系统(LMS)的停机时间。结论是,使用云平台构建分布式LMS是一种实践,它只允许使用所需的计算能力。实践证明,将所提出的解决方案应用到自适应LMS的工作中,可以通过减少内容交付的时间来提高其工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信