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A Large-Scale Wired Network Energy Model for Flow-Level Simulations

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Abstract

The use of simulators to predict network energy consumption is a good way for scientists to improve and develop new algorithms and also to assess them. However, the average size of a network platforms is continuously increasing with the emergence of new technologies like the Internet Of Things and Fog Computing. Packet-level simula-tors start to reach their limits in terms of performance and this calls for newer solutions in the domain of large-scale platform energy models. In this paper, we propose two energy models for wired networks adapted to flow level simulators in order to estimate the energy consumption of large platforms. An evaluation of these models is proposed and it demonstrates their applicability in practice and their accuracy. Indeed, we obtain simulation results with a relative error lower than 4% compared to an ns-3-based solution, and our flow-based simulation is 120 times faster.
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Dates and versions

hal-02020045 , version 1 (15-02-2019)
hal-02020045 , version 2 (26-02-2019)

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Loic Guegan, Betsegaw Lemma Amersho, Anne-Cécile Orgerie, Martin Quinson. A Large-Scale Wired Network Energy Model for Flow-Level Simulations. AINA 2019 - 33rd International Conference on Advanced Information Networking and Applications, Mar 2019, Matsue, Japan. pp.1047-1058, ⟨10.1007/978-3-030-15032-7_88⟩. ⟨hal-02020045v2⟩
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