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A Queueing-Based Model Performance Evaluation for Internet of People Supported by Fog Computing

Author

Listed:
  • Laécio Rodrigues

    (Computer Science Department, Universidade Federal do Piauí (UFPI), Teresina 64049-550, PI, Brazil)

  • Joel J. P. C. Rodrigues

    (Research, Development and Innovation, Senac Faculty of Ceará, Fortaleza 60160-194, CE, Brazil
    Covilhã Delegation, Instituto de Telecomunicações, 6201-001 Covilhã, Portugal)

  • Antonio de Barros Serra

    (Covilhã Delegation, Instituto de Telecomunicações, 6201-001 Covilhã, Portugal
    Federal Institute of Ceará, Fortaleza 60040-531, CE, Brazil)

  • Francisco Airton Silva

    (Computer Science Department, Universidade Federal do Piauí (UFPI), Teresina 64049-550, PI, Brazil)

Abstract

Following the Internet of Things (IoT) and the Internet of Space (IoS), we are now approaching IoP (Internet of People), or the Internet of Individuals, with the integration of chips inside people that link to other chips and the Internet. Low latency is required in order to achieve great service quality in these ambient assisted living facilities. Failures, on the other hand, are not tolerated, and assessing the performance of such systems in a real-world setting is difficult. Analytical models may be used to examine these types of systems even in the early phases of design. The performance of aged care monitoring systems is evaluated using an M/M/c/K queuing network. The model enables resource capacity, communication, and service delays to be calibrated. The proposed model was shown to be capable of predicting the system’s MRT (mean response time) and calculating the quantity of resources required to satisfy certain user requirements. To analyze data from IoT solutions, the examined architecture incorporates cloud and fog resources. Different circumstances were analyzed as case studies, with four main characteristics taken into consideration. These case studies look into how cloud and fog resources differ. Simulations were also run to test various routing algorithms with the goal of improving performance metrics. As a result, our study can assist in the development of more sophisticated health monitoring systems without incurring additional costs.

Suggested Citation

  • Laécio Rodrigues & Joel J. P. C. Rodrigues & Antonio de Barros Serra & Francisco Airton Silva, 2022. "A Queueing-Based Model Performance Evaluation for Internet of People Supported by Fog Computing," Future Internet, MDPI, vol. 14(1), pages 1-18, January.
  • Handle: RePEc:gam:jftint:v:14:y:2022:i:1:p:23-:d:720222
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    Citations

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    Cited by:

    1. Sunil K. Panigrahi & Veena Goswami & Hemant K. Apat & Ganga B. Mund & Himansu Das & Rabindra K. Barik, 2023. "PQ-Mist : Priority Queueing-Assisted Mist–Cloud–Fog System for Geospatial Web Services," Mathematics, MDPI, vol. 11(16), pages 1-21, August.
    2. Guillermo Fuertes & Jorge Zamorano & Miguel Alfaro & Manuel Vargas & Jorge Sabattin & Claudia Duran & Rodrigo Ternero & Ricardo Rivera, 2022. "Opportunities of the Technological Trends Linked to Industry 4.0 for Achieve Sustainable Manufacturing Objectives," Sustainability, MDPI, vol. 14(18), pages 1-36, September.

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