Traffic estimation for dynamic capacity adaptation in load adaptive network operation regimes

Ahrens, Andreas and Lange, Christoph and Benavente Peces, César (2016). Traffic estimation for dynamic capacity adaptation in load adaptive network operation regimes. In: "SPCS 2016 - International Conference on Signal Processing and Communication Systems", 25/07/2016 - 27/07/2016, Lisboa (Portugal). ISBN 978-989-758-195-3. pp. 99-104. https://doi.org/10.5220/0005932800990104.

Description

Title: Traffic estimation for dynamic capacity adaptation in load adaptive network operation regimes
Author/s:
  • Ahrens, Andreas
  • Lange, Christoph
  • Benavente Peces, César
Item Type: Presentation at Congress or Conference (Article)
Event Title: SPCS 2016 - International Conference on Signal Processing and Communication Systems
Event Dates: 25/07/2016 - 27/07/2016
Event Location: Lisboa (Portugal)
Title of Book: Proceedings of the 6th International Joint Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2016)
Date: 2016
ISBN: 978-989-758-195-3
Subjects:
Freetext Keywords: Traffic Prediction, Network Energy Efficiency, Wiener Filtering, Demand-aware Network Operation, Dynamic Network Dimensioning, Green Communications
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Teoría de la Señal y Comunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The energy demand of telecommunication equipment and networks has been identified to be significant. In the information society such networks are vital for societal and economic welfare as well as for the people’s private lives. Therefore an improved energy efficiency of telecommunication networks is essential in the context of sustainability and climate change. Load-adaptive regimes are a promising option for energy-efficient and sustainable network operation. As the capacity is adapted to temporally fluctuating traffic demands, they require a robust traffic demand estimation. As a potential solution to mitigate this problem, a method for reliable traffic demand forecasting on relevant time scales using Wiener filtering is presented. The results show that the capacity dimensioning based on the proposed Wiener filtering traffic estimation method leads to reliable outcomes enabling sustainable and efficient network operation.

More information

Item ID: 46513
DC Identifier: http://oa.upm.es/46513/
OAI Identifier: oai:oa.upm.es:46513
DOI: 10.5220/0005932800990104
Official URL: http://www.spcs.peccs.org/Home.aspx?y=2016
Deposited by: Memoria Investigacion
Deposited on: 07 Jun 2018 08:59
Last Modified: 07 Jun 2018 08:59
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