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Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

Author

Listed:
  • Giovanni Pau

    (Kore University of Enna, Faculty of Engineering and Architecture, Cittadella Universitaria, 94100 Enna, Italy)

  • Mario Collotta

    (Kore University of Enna, Faculty of Engineering and Architecture, Cittadella Universitaria, 94100 Enna, Italy)

  • Vincenzo Maniscalco

    (Kore University of Enna, Faculty of Engineering and Architecture, Cittadella Universitaria, 94100 Enna, Italy)

Abstract

Energy efficiency is a fundamental requirement for a wireless protocol to be suitable for use within the Internet of Things. New technologies are emerging aiming at an energy-efficient communication. Among them, Bluetooth Low Energy is an appealing solution. Recently, the specifications of Bluetooth 5 have been presented with the purpose to offer significant enhancements compared to the earlier versions of the protocol. Bluetooth 5 comes with new communication modes that differ in range, speed, and energy consumption. This paper proposes a fuzzy-based solution to cope with the selection of the communication mode, among those introduced with Bluetooth 5, that allows the best energy efficiency. This communication mode, used by mobile devices, is dynamically regulated by varying the transmission power, returned as the output of a Fuzzy Logic Controller (FLC). A Particle Swarm Optimization (PSO) algorithm is presented to achieve the optimal parameters of the proposed FLC, i.e., optimizing the triangular membership functions, by varying their range, to reach the best results concerning the battery life of mobile devices. The proposed FLC is based on triangular membership functions because they represent a good trade-off between computation cost and efficiency. The paper presents a detailed description of the FLC design, a logical analysis of the PSO algorithm for the derivation of best performance conditions values, and experimental assessments, obtained through testbed scenarios.

Suggested Citation

  • Giovanni Pau & Mario Collotta & Vincenzo Maniscalco, 2017. "Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things," Energies, MDPI, vol. 10(7), pages 1-22, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:992-:d:104602
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    References listed on IDEAS

    as
    1. Yancai Xiao & Tieling Zhang & Zeyu Ding & Chunya Li, 2016. "The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters," Energies, MDPI, vol. 9(5), pages 1-17, May.
    2. Mario Collotta & Giovanni Pau, 2015. "A Solution Based on Bluetooth Low Energy for Smart Home Energy Management," Energies, MDPI, vol. 8(10), pages 1-23, October.
    3. Babayo, Aliyu Aliyu & Anisi, Mohammad Hossein & Ali, Ihsan, 2017. "A Review on energy management schemes in energy harvesting wireless sensor networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1176-1184.
    4. Po-Chen Cheng & Bo-Rei Peng & Yi-Hua Liu & Yu-Shan Cheng & Jia-Wei Huang, 2015. "Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique," Energies, MDPI, vol. 8(6), pages 1-23, June.
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