基于MANET的发布/订阅系统的QoS感知预测方案

Imene Lahyani, M. Gassara, M. Jmaiel, C. Chassot
{"title":"基于MANET的发布/订阅系统的QoS感知预测方案","authors":"Imene Lahyani, M. Gassara, M. Jmaiel, C. Chassot","doi":"10.1109/ISPDC.2012.11","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a failure prediction methodology for quality of service (QoS) degradation prediction for publish/subscribe systems on MANET. Our propose is to use the Auto Regressive Integrated Moving Average (ARIMA) method to predict failure occurrence in the system and to provide optimal QoS provision of applications. Besides, our forecasting algorithm looks for the source behind QoS degradation using the Correlation method. Simulations results are performed to prove the efficiency of the proposed approach. A comparison is done proving that our proposal outperforms the Auto Regression (AR) based prediction approach.","PeriodicalId":287900,"journal":{"name":"2012 11th International Symposium on Parallel and Distributed Computing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Predictive Schemes for QoS Awareness of Publish/Subscribe Systems on MANET\",\"authors\":\"Imene Lahyani, M. Gassara, M. Jmaiel, C. Chassot\",\"doi\":\"10.1109/ISPDC.2012.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a failure prediction methodology for quality of service (QoS) degradation prediction for publish/subscribe systems on MANET. Our propose is to use the Auto Regressive Integrated Moving Average (ARIMA) method to predict failure occurrence in the system and to provide optimal QoS provision of applications. Besides, our forecasting algorithm looks for the source behind QoS degradation using the Correlation method. Simulations results are performed to prove the efficiency of the proposed approach. A comparison is done proving that our proposal outperforms the Auto Regression (AR) based prediction approach.\",\"PeriodicalId\":287900,\"journal\":{\"name\":\"2012 11th International Symposium on Parallel and Distributed Computing\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 11th International Symposium on Parallel and Distributed Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2012.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 11th International Symposium on Parallel and Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDC.2012.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

在本文中,我们提出了一种故障预测方法,用于预测MANET上发布/订阅系统的服务质量(QoS)退化。我们的建议是使用自回归综合移动平均(ARIMA)方法来预测系统中的故障发生,并为应用程序提供最佳的QoS提供。此外,我们的预测算法使用相关性方法寻找QoS退化背后的来源。仿真结果证明了该方法的有效性。通过比较,证明了该方法优于基于自回归(AR)的预测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Schemes for QoS Awareness of Publish/Subscribe Systems on MANET
In this paper, we propose a failure prediction methodology for quality of service (QoS) degradation prediction for publish/subscribe systems on MANET. Our propose is to use the Auto Regressive Integrated Moving Average (ARIMA) method to predict failure occurrence in the system and to provide optimal QoS provision of applications. Besides, our forecasting algorithm looks for the source behind QoS degradation using the Correlation method. Simulations results are performed to prove the efficiency of the proposed approach. A comparison is done proving that our proposal outperforms the Auto Regression (AR) based prediction approach.
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