IEEE Access (Jan 2024)

An IoT and Blockchain-Based Secure and Transparent Supply Chain Management Framework in Smart Cities Using Optimal Queue Model

  • Ahmad Yahiya Ahmadad Bani Ahmad,
  • Neha Verma,
  • Nadia Mohamed Sarhan,
  • Emad Mahrous Awwad,
  • Amit Arora,
  • Vincent Omollo Nyangaresi

DOI
https://doi.org/10.1109/ACCESS.2024.3376605
Journal volume & issue
Vol. 12
pp. 51752 – 51771

Abstract

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The process of controlling the flow of products and services from a company by encompassing each stage involved in transforming raw materials and parts into finished items, also delivering them to the final consumer is known as Supply Chain Management (SCM). The development of numerous smart city applications including smart grids, smart homes, smart supply chains, and smart healthcare has drawn attention to the Internet of Things (IoT). Nowadays, researchers are considering the smart healthcare system’s role as a Public Emergency Service (PES) to treat patients promptly. A distributed smart fire brigade system receives little attention like PES to save lives and property from catastrophic fire damage. The conventional PES methods are created using a centralized method that needs a lot of processing power and doesn’t offer timely services. The traditional systems developed for managing the supply chain have drawbacks like single-point failure issues, data integrity, transparency, and lack of trust. To alleviate the existing issues, in this paper, a Blockchain and IoT Enable Secure and Transparent Supply Chain Management framework is utilized for PES in the smart city environment. Further, two edge computing servers, like a service controller and an IoT controller are adapted. The local storage is handled by the service and IoT controller. Thus, it enhances the data processing speed of PES requests and PES fulfillment. The service controller utilizes the Optimal Queue Model to manage the PES requests based on the minimum service queue length. The efficiency of the network is improved by fine-tuning the parameters from the Queue model with the aid of a Revised Fitness-based Political Optimizer (RF-PO). The multi-objective constraints like queue length, utilization, actual arrival time, expected arrival time, and end-to-end delay are utilized for the efficient supply chain system. These stimulated results show the feasibility and effectiveness of the supply chain framework.

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