Internet traffic forecasting using neural networks
Main Author: | |
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Publication Date: | 2006 |
Other Authors: | , , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/6581 |
Summary: | The forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a Neural Network Ensemble (NNE) for the prediction of TCP/IP traffic using a Time Series Forecasting (TSF) point of view. Several experiments were devised by considering real-world data from two large Internet Service Providers. In addition, different time scales (e.g. every five minutes and hourly) and forecasting horizons were analyzed. Overall, the NNE approach is competitive when compared with other TSF methods (e.g. Holt-Winters and ARIMA). |
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Internet traffic forecasting using neural networksArtificial intelligenceComputer communicationsNetworksScience & TechnologyThe forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a Neural Network Ensemble (NNE) for the prediction of TCP/IP traffic using a Time Series Forecasting (TSF) point of view. Several experiments were devised by considering real-world data from two large Internet Service Providers. In addition, different time scales (e.g. every five minutes and hourly) and forecasting horizons were analyzed. Overall, the NNE approach is competitive when compared with other TSF methods (e.g. Holt-Winters and ARIMA).Engineering and Physical Sciences Research Council (EP/522885 grant).Portuguese National Conference of Rectors (CRUP)/British Council Portugal (B-53/05 grant).Nuffield Foundation (NAL/001136/A grant).IEEEUniversidade do MinhoRocha, MiguelSousa, PedroCortez, PauloRio, Miguel2006-072006-07-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/6581engINTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, Vancouver, BC, Canada, 2006 – “IJCNN 2006 : proceedings of the International Joint Conference on Neural Networks”. [S.l.] : IEEE, 2006. ISBN 0-7803-9490-9. p. 4942-4949.0-7803-9490-92161-4393info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:12:08Zoai:repositorium.sdum.uminho.pt:1822/6581Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:19:05.704278Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Internet traffic forecasting using neural networks |
title |
Internet traffic forecasting using neural networks |
spellingShingle |
Internet traffic forecasting using neural networks Rocha, Miguel Artificial intelligence Computer communications Networks Science & Technology |
title_short |
Internet traffic forecasting using neural networks |
title_full |
Internet traffic forecasting using neural networks |
title_fullStr |
Internet traffic forecasting using neural networks |
title_full_unstemmed |
Internet traffic forecasting using neural networks |
title_sort |
Internet traffic forecasting using neural networks |
author |
Rocha, Miguel |
author_facet |
Rocha, Miguel Sousa, Pedro Cortez, Paulo Rio, Miguel |
author_role |
author |
author2 |
Sousa, Pedro Cortez, Paulo Rio, Miguel |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Rocha, Miguel Sousa, Pedro Cortez, Paulo Rio, Miguel |
dc.subject.por.fl_str_mv |
Artificial intelligence Computer communications Networks Science & Technology |
topic |
Artificial intelligence Computer communications Networks Science & Technology |
description |
The forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a Neural Network Ensemble (NNE) for the prediction of TCP/IP traffic using a Time Series Forecasting (TSF) point of view. Several experiments were devised by considering real-world data from two large Internet Service Providers. In addition, different time scales (e.g. every five minutes and hourly) and forecasting horizons were analyzed. Overall, the NNE approach is competitive when compared with other TSF methods (e.g. Holt-Winters and ARIMA). |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-07 2006-07-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/6581 |
url |
http://hdl.handle.net/1822/6581 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, Vancouver, BC, Canada, 2006 – “IJCNN 2006 : proceedings of the International Joint Conference on Neural Networks”. [S.l.] : IEEE, 2006. ISBN 0-7803-9490-9. p. 4942-4949. 0-7803-9490-9 2161-4393 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
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