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Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

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Abstract

The necessity of energy-efficient systems in order to protect our environment, cope with global warming, and facilitate sustainable development is paramount for the researching world because the survival of the planet is at stake. Thus, optimizing the energy efficiency of wireless communications not only reduces environmental impact, but also cuts overall network costs and helps make communication more practical and affordable in a pervasive setting. This paper is focused on a solution to enhance the energy efficiency in outdoor wireless local area networks using the standard IEEE 802.11b/g. So, from a previous study about the weather’s impact on the number of control frame errors and retransmissions, we propose a green cognitive algorithm that adapts wireless transmissions to the channel conditions caused by the weather. The goal is to reduce retransmissions and control errors in order to save energy and to enhance network performance. Our proposal is based on a mathematical analysis in which we see how the frame error rate is related to the power consumption according to the modulation scheme and data rate used by transmitters. Finally, several simulations show that the green cognitive algorithm presented in this paper involves significant energy savings for outdoors WLANs.

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Acknowledgments

This work has been supported by the Vice-Rectorate for Research, Innovation and Transfer of the Universitat Politècnica de València through the programme of International Campus of Excellence funded by Ministry of Education of Spain, and through the programme of Predoctoral Research Grants (FPI-UPV). The authors would like to thank the Information and Communications Systems Office (ASIC), Borja Opticos Enterprise and Azimut Electronics Company for their collaboration and support.

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Authors and Affiliations

  1. Department of Communications, Universitat Politècnica de València, Camino de Vera, s/n, 46022, Valencia, Spain

    Diana Bri, Francisco Ramos & Jaime Lloret

  2. Department of Computer Science, Universitat de València, Carrer de la Universitat, s/n, 46100, Burjassot, Spain

    Miguel Garcia

Authors
  1. Diana Bri
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  2. Miguel Garcia
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  3. Francisco Ramos
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  4. Jaime Lloret
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Correspondence to Diana Bri.

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Bri, D., Garcia, M., Ramos, F. et al. Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks. Mobile Netw Appl 20, 673–691 (2015). https://doi.org/10.1007/s11036-015-0602-7

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  • DOI: https://doi.org/10.1007/s11036-015-0602-7

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