利用贝叶斯信念网络进行节能网络管理

A. Bashar, G. Parr, S. McClean, B. Scotney, M. Subramanian, S. K. Chaudhari, T. Gonsalves
{"title":"利用贝叶斯信念网络进行节能网络管理","authors":"A. Bashar, G. Parr, S. McClean, B. Scotney, M. Subramanian, S. K. Chaudhari, T. Gonsalves","doi":"10.1109/NCC.2010.5430172","DOIUrl":null,"url":null,"abstract":"Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance.","PeriodicalId":130953,"journal":{"name":"2010 National Conference On Communications (NCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Employing Bayesian Belief Networks for energy efficient Network Management\",\"authors\":\"A. Bashar, G. Parr, S. McClean, B. Scotney, M. Subramanian, S. K. Chaudhari, T. Gonsalves\",\"doi\":\"10.1109/NCC.2010.5430172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance.\",\"PeriodicalId\":130953,\"journal\":{\"name\":\"2010 National Conference On Communications (NCC)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 National Conference On Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2010.5430172\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 National Conference On Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2010.5430172","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

摘要

网络管理系统(NMS)用于监控网络,并与运营支持系统(OSS)一起维护性能,重点是保证应用程序和服务的持续QoS。一个不太受重视的方面是网元在非高峰时段的能量消耗。本文研究了一个场景,其中NMS通过智能地将网元或其选择端口在未充分利用时转为休眠模式,在提高网络能源效率方面发挥重要作用。为此,我们提出并评估了一种基于贝叶斯信念网络(BBN)的决策管理系统(DMS),该系统为NMS提供智能决策,使其能够在不影响性能和QoS约束的情况下自适应地改变网元的运行模式。通过模拟网络进行了概念验证,并讨论了节能量及其对网络性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Employing Bayesian Belief Networks for energy efficient Network Management
Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance.
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