A Wi-Fi Energy Model for Scalable Simulation
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| Title: | A Wi-Fi Energy Model for Scalable Simulation |
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| Authors: | Courageux-Sudan, Clément, Orgerie, Anne-Cécile, Quinson, Martin |
| Contributors: | Design and Implementation of Autonomous Distributed Systems (MYRIADS), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Centre National de la Recherche Scientifique (CNRS) |
| Source: | 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) WoWMoM 2023 - 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks https://hal.science/hal-04055720 WoWMoM 2023 - 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, Jun 2023, Boston (MA), United States. pp.1-10 |
| Publisher Information: | HAL CCSD |
| Publication Year: | 2023 |
| Collection: | Université de Rennes 1: Publications scientifiques (HAL) |
| Subject Terms: | Wi-Fi Simulation Power Model Energy Consumption, Wi-Fi Simulation, Power Model, Energy Consumption, [INFO]Computer Science [cs], [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] |
| Subject Geographic: | Boston (MA), United States |
| Time: | Boston (MA), United States |
| Description: | International audience ; Wi-Fi devices are ubiquitous, thus they have been extensively studied to understand, for example, the impact of different channel conditions and network properties over network performance. However, improving network performance without considering energy consumption can lead to critical issues: battery depletion, higher costs, and increased latency. Existing works provide algorithms and techniques for more efficient use of energy for Wi-Fi communication, especially in the case of IoT networks, limited by battery capacity. But the evergrowing number of Wi-Fi devices along with the increase in traffic and heterogeneity of current networks make measuring the energy footprint of Wi-Fi communication particularly complex, especially at a large scale. Existing simulation models to study the energy consumption of Wi-Fi devices either suffer from scalability issues due to their fine granularity, or lack realism hindering their usage in practice. In this paper, we propose a power model tackling these scalability and accuracy issues through the use of a flow-based simulation model. By comparing the accuracy and performance of our model to state-of-the-art solution, we show that our approach achieves accurate energy predictions on largescale and heterogeneous network infrastructures. Our flow-level model allows us to simulate the energy consumption of 800 nodes in a few seconds compared to more fine-grained simulators such as ns-3 that require more than 8 hours under the same scenario, with similar accuracy. |
| Document Type: | conference object |
| Language: | English |
| Availability: | https://hal.science/hal-04055720 https://hal.science/hal-04055720v1/document https://hal.science/hal-04055720v1/file/WoWMoM2023.pdf |
| Rights: | info:eu-repo/semantics/OpenAccess |
| Accession Number: | edsbas.984C90 |
| Database: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | International audience ; Wi-Fi devices are ubiquitous, thus they have been extensively studied to understand, for example, the impact of different channel conditions and network properties over network performance. However, improving network performance without considering energy consumption can lead to critical issues: battery depletion, higher costs, and increased latency. Existing works provide algorithms and techniques for more efficient use of energy for Wi-Fi communication, especially in the case of IoT networks, limited by battery capacity. But the evergrowing number of Wi-Fi devices along with the increase in traffic and heterogeneity of current networks make measuring the energy footprint of Wi-Fi communication particularly complex, especially at a large scale. Existing simulation models to study the energy consumption of Wi-Fi devices either suffer from scalability issues due to their fine granularity, or lack realism hindering their usage in practice. In this paper, we propose a power model tackling these scalability and accuracy issues through the use of a flow-based simulation model. By comparing the accuracy and performance of our model to state-of-the-art solution, we show that our approach achieves accurate energy predictions on largescale and heterogeneous network infrastructures. Our flow-level model allows us to simulate the energy consumption of 800 nodes in a few seconds compared to more fine-grained simulators such as ns-3 that require more than 8 hours under the same scenario, with similar accuracy. |
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