多层云计算中资源配置的新趋势

Marwah Hashim Eawna, Salma Hamdy, El-Sayed M. El-Horbaty
{"title":"多层云计算中资源配置的新趋势","authors":"Marwah Hashim Eawna, Salma Hamdy, El-Sayed M. El-Horbaty","doi":"10.1109/INTELCIS.2015.7397226","DOIUrl":null,"url":null,"abstract":"Cloud Computing is an emerging trend in the outsourced information technology (OIT) and provides a lot of functions as services. However, it suffers from many challenges such as resource provisioning, integrity, federation, and security. This paper focuses on the major problem, resource provisioning, that explored by many companies and researchers as a critical problem. Such researches are attempted to find method that minimizes provisioning time and reduces the number of resources in the cloud environment. Consequently, this paper proposes a dynamic resources provisioning algorithm by using Artificial Bees Colony (ABC) and Ant Colony Optimization (ACO) and focus on time optimization in multi-tier clouds. Accordingly, the obtained results show that the ACO faster than other meta-heuristic algorithm such as ABC, Particle Swarm Optimization (PSO), Simulated Annealing (SA) and hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA).","PeriodicalId":6478,"journal":{"name":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","volume":"21 1","pages":"224-230"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"New trends of resource provisioning in multi-tier Cloud computing\",\"authors\":\"Marwah Hashim Eawna, Salma Hamdy, El-Sayed M. El-Horbaty\",\"doi\":\"10.1109/INTELCIS.2015.7397226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud Computing is an emerging trend in the outsourced information technology (OIT) and provides a lot of functions as services. However, it suffers from many challenges such as resource provisioning, integrity, federation, and security. This paper focuses on the major problem, resource provisioning, that explored by many companies and researchers as a critical problem. Such researches are attempted to find method that minimizes provisioning time and reduces the number of resources in the cloud environment. Consequently, this paper proposes a dynamic resources provisioning algorithm by using Artificial Bees Colony (ABC) and Ant Colony Optimization (ACO) and focus on time optimization in multi-tier clouds. Accordingly, the obtained results show that the ACO faster than other meta-heuristic algorithm such as ABC, Particle Swarm Optimization (PSO), Simulated Annealing (SA) and hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA).\",\"PeriodicalId\":6478,\"journal\":{\"name\":\"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)\",\"volume\":\"21 1\",\"pages\":\"224-230\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INTELCIS.2015.7397226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INTELCIS.2015.7397226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

云计算是外包信息技术(OIT)的一个新兴趋势,它以服务的形式提供了许多功能。然而,它面临着许多挑战,例如资源供应、完整性、联合和安全性。本文重点讨论了许多公司和研究人员都在探讨的一个关键问题——资源配置问题。这些研究试图找到最小化配置时间和减少云环境中资源数量的方法。为此,本文提出了一种基于人工蜂群(Artificial Bees Colony, ABC)和蚁群算法(Ant Colony Optimization, ACO)的动态资源分配算法,并重点研究了多层云环境下的时间优化问题。结果表明,蚁群优化算法比ABC、粒子群优化算法(PSO)、模拟退火算法(SA)和粒子群优化-模拟退火混合算法(PSO-SA)的求解速度更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
New trends of resource provisioning in multi-tier Cloud computing
Cloud Computing is an emerging trend in the outsourced information technology (OIT) and provides a lot of functions as services. However, it suffers from many challenges such as resource provisioning, integrity, federation, and security. This paper focuses on the major problem, resource provisioning, that explored by many companies and researchers as a critical problem. Such researches are attempted to find method that minimizes provisioning time and reduces the number of resources in the cloud environment. Consequently, this paper proposes a dynamic resources provisioning algorithm by using Artificial Bees Colony (ABC) and Ant Colony Optimization (ACO) and focus on time optimization in multi-tier clouds. Accordingly, the obtained results show that the ACO faster than other meta-heuristic algorithm such as ABC, Particle Swarm Optimization (PSO), Simulated Annealing (SA) and hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
On the use of probabilistic model-checking for the verification of prognostics applications Prospective, knowledge based clinical risk analysis: The OPT-model Partial deduction in predicate calculus as a tool for artificial intelligence problem complexity decreasing XML summarization: A survey Finding the pin in the haystack: A Bot Traceback service for public clouds
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1