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Planning a secure and reliable IoT-enabled FOG-assisted computing infrastructure for healthcare

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Abstract

Transmitting electronic medical records (EMR) and other communication in modern Internet of Things (IoT) healthcare ecosystem is both delay and integrity-sensitive. Transmitting and computing volumes of EMR data on traditional clouds away from healthcare facilities is a main source of trust-deficit using IoT-enabled applications. Reliable IoT-enabled healthcare (IoTH) applications demand careful deployment of computing and communication infrastructure (CnCI). This paper presents a FOG-assisted CnCI model for reliable healthcare facilities. Planning a secure and reliable CnCI for IoTH networks is a challenging optimization task. We proposed a novel mathematical model (i.e., integer programming) to plan FOG-assisted CnCI for IoTH networks. It considers wireless link interfacing gateways as a virtual machine (VM). An IoTH network contains three wirelessly communicating nodes: VMs, reduced computing power gateways (RCPG), and full computing power gateways (FCPG). The objective is to minimize the weighted sum of infrastructure and operational costs of the IoTH network planning. Swarm intelligence-based evolutionary approach is used to solve IoTH networks planning for superior quality solutions in a reasonable time. The discrete fireworks algorithm with three local search methods (DFWA-3-LSM) outperformed other experimented algorithms in terms of average planning cost for all experimented problem instances. The DFWA-3-LSM lowered the average planning cost by 17.31%, 17.23%, and 18.28% when compared against discrete artificial bee colony with 3 LSM (DABC-3-LSM), low-complexity biogeography-based optimization (LC-BBO), and genetic algorithm, respectively. Statistical analysis demonstrates that the performance of DFWA-3-LSM is better than other experimented algorithms. The proposed mathematical model is envisioned for secure, reliable and cost-effective EMR data manipulation and other communication in healthcare.

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The present study is based on synthesized data generated randomly by the authors based on some parameters mentioned in the above text.

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Authors and Affiliations

  1. College of Business and Information Systems, Dakota State University, Madison, USA

    Hafiz Munsub Ali & Jun Liu

  2. Division of Computer Science, Mathematics and Science, Collins College of Professional Studies, St. John’s University, Jamaica, USA

    Syed Ahmad Chan Bukhari

  3. Department of Computer Science, Faculty of Engineering & Informatics, University of Bradford, Bradford, UK

    Hafiz Tayyab Rauf

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  1. Hafiz Munsub Ali
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  2. Jun Liu
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  4. Hafiz Tayyab Rauf
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Contributions

This work is conceptualized, designed, and formulated by H. M. A. and J. L. Associated application concepts and experimentation design is done by H. M. A., S. A. C. B., and J. L. After initial draft by H. M. A., H. T. R., and S. A. C. B. give technical input to improve quality and presentation of work which significantly improved the manuscript. All the authors read and approved the final manuscript.

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Correspondence to Hafiz Munsub Ali.

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Ali, H.M., Liu, J., Bukhari, S.A.C. et al. Planning a secure and reliable IoT-enabled FOG-assisted computing infrastructure for healthcare. Cluster Comput 25, 2143–2161 (2022). https://doi.org/10.1007/s10586-021-03389-y

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