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An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation

Author

Listed:
  • Carolina Del-Valle-Soto

    (Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan, Jalisco 45010, Mexico)

  • Ramiro Velázquez

    (Facultad de Ingeniería, Universidad Panamericana, Josemaría Escrivá de Balaguer 101, Aguascalientes 20290, Mexico)

  • Leonardo J. Valdivia

    (Facultad de Ingeniería, Universidad Panamericana, Álvaro del Portillo 49, Zapopan, Jalisco 45010, Mexico)

  • Nicola Ivan Giannoccaro

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Paolo Visconti

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

Abstract

The continuous evolution of the Internet of Things (IoT) makes it possible to connect everyday objects to networks in order to monitor physical and environmental conditions, which is made possible due to wireless sensor networks (WSN) that enable the transfer of data. However, it has also brought about many challenges that need to be addressed, such as excess energy consumption. Accordingly, this paper presents and analyzes wireless network energy models using five different communication protocols: Ad Hoc On-Demand Distance Vector (AODV), Multi-Parent Hierarchical (MPH), Dynamic Source Routing (DSR), Low Energy Adaptive Clustering Hierarchy (LEACH) and Zigbee Tree Routing (ZTR). First, a series of metrics are defined to establish a comparison and determine which protocol exhibits the best energy consumption performance. Then, simulations are performed and the results are compared with real scenarios. The energy analysis is conducted with three proposed sleeping algorithms: Modified Sleeping Crown (MSC), Timer Sleeping Algorithm (TSA), and Local Energy Information (LEI). Thereafter, the proposed algorithms are compared by virtue of two widely used wireless technologies, namely Zigbee and WiFi. Indeed, the results suggest that Zigbee has a better energy performance than WiFi, but less redundancy in the topology links, and this study favors the analysis with the simulation of protocols with different nature. The tested scenario is implemented into a university campus to show a real network running.

Suggested Citation

  • Carolina Del-Valle-Soto & Ramiro Velázquez & Leonardo J. Valdivia & Nicola Ivan Giannoccaro & Paolo Visconti, 2020. "An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation," Energies, MDPI, vol. 13(11), pages 1-31, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:3024-:d:370394
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    References listed on IDEAS

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    1. Roberto de Fazio & Donato Cafagna & Giorgio Marcuccio & Alessandro Minerba & Paolo Visconti, 2020. "A Multi-Source Harvesting System Applied to Sensor-Based Smart Garments for Monitoring Workers’ Bio-Physical Parameters in Harsh Environments," Energies, MDPI, vol. 13(9), pages 1-33, May.
    2. C. SriVenkateswaran & D. Sivakumar, 2019. "Secure cluster-based data aggregation in wireless sensor networks with aid of ECC," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 31(2), pages 153-169.
    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. Roberto de Fazio & Donato Cafagna & Giorgio Marcuccio & Paolo Visconti, 2020. "Limitations and Characterization of Energy Storage Devices for Harvesting Applications," Energies, MDPI, vol. 13(4), pages 1-18, February.
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    Cited by:

    1. Ala’ Khalifeh & Mai Saadeh & Khalid A. Darabkh & Prabagarane Nagaradjane, 2021. "Radio Frequency Based Wireless Charging for Unsupervised Clustered WSN: System Implementation and Experimental Evaluation," Energies, MDPI, vol. 14(7), pages 1-21, March.
    2. Paolo Visconti & Nicola Ivan Giannoccaro & Roberto de Fazio, 2021. "Special Issue on Electronic Systems and Energy Harvesting Methods for Automation, Mechatronics and Automotive," Energies, MDPI, vol. 14(23), pages 1-5, December.
    3. Douglas de Farias Medeiros & Cleonilson Protasio de Souza & Fabricio Braga Soares de Carvalho & Waslon Terllizzie Araújo Lopes, 2022. "Energy-Saving Routing Protocols for Smart Cities," Energies, MDPI, vol. 15(19), pages 1-19, October.

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