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CARE: an efficient modelling for topology robustness of an IoT based healthcare network using Go-GA

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Abstract

The proliferation of the Internet of Things (IoT) in healthcare necessitates networks that are robust against potential node or link failures to ensure uninterrupted patient care. This research concentrates on enhancing the topology robustness of IoT-based smart healthcare networks. Utilizing Schneider R as a robustness metric, a system model is developed, where IoT nodes’ geographic information is centrally stored. Introducing the Convergence And Robustness Efficiency (CARE) solution, we exploit a geometric approach within genetic algorithms (GA) to enhance the network’s topology robustness. CARE’s nested strategy tackles the slow convergence and high computational costs seen in contemporary techniques, leading to optimized results. Simulations show that CARE surpasses conventional GA by an impressive 21% in Schneider R and only degrades by 7.5% (compared to 16% of existing solutions) when node density surges to 200 in healthcare settings. By tapping into efficient computing methods, this research paves the way for robust healthcare IoT networks, ensuring patient safety and data integrity.

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Authors and Affiliations

  1. Riphah Institute of Systems Engineering (RISE), Riphah International University, Islamabad, 47000, Pakistan

    Sabir Ali Changazi, Muhammad Yousaf & Muhammad Hasan Islam

  2. Military College of Signals (MCS), National University of Sciences and Technology (NUST), Rawalpindi, 46000, Pakistan

    Asim Dilawar Bakhshi

  3. Department of Computer Science, COMSATS University Islamabad, Islamabad, 45550, Pakistan

    Syed Muhammad Mohsin & Bashir Ahmad

  4. College of Intellectual Novitiates (COIN), Virtual University of Pakistan, Lahore, 55150, Pakistan

    Syed Muhammad Mohsin

  5. Department of Computer Science, COMSATS University Islamabad, Vehari Campus, 61071, Pakistan

    Muhammad Rafiq Mufti

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  1. Sabir Ali Changazi
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  3. Muhammad Yousaf
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  4. Muhammad Hasan Islam
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Contributions

Sabir Ali Changazi: Conceptualization, Data curation, Methodology, Writing - original draft, Software, Writing-review & editing; Asim Dilawar Bakhshi: Conceptualization, Data curation, Methodology, Writing - original draft, Software, Writing-review & editing, Formal analysis, Visualization, Investigation; Muhammad Yousaf: Supervision, Project administration, Visualization, Investigation, Writing - review & editing; Formal analysis; Muhammad Hasan Islam: Formal analysis, Data curation, Methodology, Project administration; Syed Muhammad Mohsin: Writing - review & editing; Formal analysis, Methodology, Investigation, Project administration; Muhammad Rafiq Mufti: Writing - review & editing; Formal analysis, Data curation, Methodology, Project administration; Bashir Ahmad: Writing - review & editing; Formal analysis, Methodology, Investigation, Project administration.

Corresponding author

Correspondence to Muhammad Rafiq Mufti.

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Changazi, S.A., Bakhshi, A.D., Yousaf, M. et al. CARE: an efficient modelling for topology robustness of an IoT based healthcare network using Go-GA. Soft Comput (2023). https://doi.org/10.1007/s00500-023-09429-6

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