网络切片的预见资源发放

Q. Luu, S. Kerboeuf, M. Kieffer
{"title":"网络切片的预见资源发放","authors":"Q. Luu, S. Kerboeuf, M. Kieffer","doi":"10.1109/HPSR52026.2021.9481832","DOIUrl":null,"url":null,"abstract":"Network slicing has emerged as a pivotal concept in 5G systems, allowing mobile operators to build isolated logical networks (slices) on top of shared infrastructure networks. Within a network slice, several Service Function Chains are usually deployed on a best-effort premise. Nevertheless, this approach does not guarantee the availability of enough infrastructure resources to accommodate the uncertain and time-varying slice resource demands.This paper investigates two adaptive slice resource provisioning methods accounting for the evolution with time of the slice resource demands. A probabilistic guarantee of meeting the slice resource requirements can be obtained, while being robust against uncertainties. The myopic approach accounts for the past demands when provisioning the current demands, while the foresighted approach accounts for both past and future demands. These two methods lead to MILP problems. Their performance is compared with a quasi-static method, where provisioning is agnostic of the past and future demands.","PeriodicalId":158580,"journal":{"name":"2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Foresighted Resource Provisioning for Network Slicing\",\"authors\":\"Q. Luu, S. Kerboeuf, M. Kieffer\",\"doi\":\"10.1109/HPSR52026.2021.9481832\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network slicing has emerged as a pivotal concept in 5G systems, allowing mobile operators to build isolated logical networks (slices) on top of shared infrastructure networks. Within a network slice, several Service Function Chains are usually deployed on a best-effort premise. Nevertheless, this approach does not guarantee the availability of enough infrastructure resources to accommodate the uncertain and time-varying slice resource demands.This paper investigates two adaptive slice resource provisioning methods accounting for the evolution with time of the slice resource demands. A probabilistic guarantee of meeting the slice resource requirements can be obtained, while being robust against uncertainties. The myopic approach accounts for the past demands when provisioning the current demands, while the foresighted approach accounts for both past and future demands. These two methods lead to MILP problems. Their performance is compared with a quasi-static method, where provisioning is agnostic of the past and future demands.\",\"PeriodicalId\":158580,\"journal\":{\"name\":\"2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPSR52026.2021.9481832\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPSR52026.2021.9481832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

网络切片已经成为5G系统中的一个关键概念,允许移动运营商在共享基础设施网络之上构建孤立的逻辑网络(切片)。在一个网络片中,通常在尽力而为的前提下部署几个服务功能链。然而,这种方法不能保证有足够的基础设施资源来适应不确定和时变的片资源需求。本文研究了考虑切片资源需求随时间变化的两种自适应切片资源分配方法。在对不确定性具有鲁棒性的同时,可以获得满足切片资源需求的概率保证。短视的方法在提供当前需求时考虑过去的需求,而预见的方法兼顾过去和未来的需求。这两种方法都会导致MILP问题。将它们的性能与准静态方法进行比较,在准静态方法中,供应与过去和未来的需求无关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Foresighted Resource Provisioning for Network Slicing
Network slicing has emerged as a pivotal concept in 5G systems, allowing mobile operators to build isolated logical networks (slices) on top of shared infrastructure networks. Within a network slice, several Service Function Chains are usually deployed on a best-effort premise. Nevertheless, this approach does not guarantee the availability of enough infrastructure resources to accommodate the uncertain and time-varying slice resource demands.This paper investigates two adaptive slice resource provisioning methods accounting for the evolution with time of the slice resource demands. A probabilistic guarantee of meeting the slice resource requirements can be obtained, while being robust against uncertainties. The myopic approach accounts for the past demands when provisioning the current demands, while the foresighted approach accounts for both past and future demands. These two methods lead to MILP problems. Their performance is compared with a quasi-static method, where provisioning is agnostic of the past and future demands.
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
×
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