Traffic Estimation for Dynamic Capacity Adaptation in Load Adaptive Network Operation Regimes

Andreas Ahrens, Christoph Lange, César Benavente-Peces

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.

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Paper Citation


in Harvard Style

Ahrens A., Lange C. and Benavente-Peces C. (2016). Traffic Estimation for Dynamic Capacity Adaptation in Load Adaptive Network Operation Regimes . In - SPCS, (PECCS 2016) ISBN , pages 0-0. DOI: 10.5220/0005932800990104


in Bibtex Style

@conference{spcs16,
author={Andreas Ahrens and Christoph Lange and César Benavente-Peces},
title={Traffic Estimation for Dynamic Capacity Adaptation in Load Adaptive Network Operation Regimes},
booktitle={ - SPCS, (PECCS 2016)},
year={2016},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005932800990104},
isbn={},
}


in EndNote Style

TY - CONF
JO - - SPCS, (PECCS 2016)
TI - Traffic Estimation for Dynamic Capacity Adaptation in Load Adaptive Network Operation Regimes
SN -
AU - Ahrens A.
AU - Lange C.
AU - Benavente-Peces C.
PY - 2016
SP - 0
EP - 0
DO - 10.5220/0005932800990104