Applied Sciences (Feb 2023)

Efficient Load Balancing for Blockchain-Based Healthcare System in Smart Cities

  • Faheem Nawaz Tareen,
  • Ahmad Naseem Alvi,
  • Asad Ali Malik,
  • Muhammad Awais Javed,
  • Muhammad Badruddin Khan,
  • Abdul Khader Jilani Saudagar,
  • Mohammed Alkhathami,
  • Mozaherul Hoque Abul Hasanat

DOI
https://doi.org/10.3390/app13042411
Journal volume & issue
Vol. 13, no. 4
p. 2411

Abstract

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Smart cities are emerging rapidly due to the provisioning of comfort in the human lifestyle. The healthcare system is an important segment of the smart city. The timely delivery of critical human vital signs data to emergency health centers without delay can save human lives. Blockchain is a secure technology that provides the immutable record-keeping of data. Secure data transmission by avoiding erroneous data delivery also demands blockchain technology in healthcare systems of smart cities where patients’ health history is required for their necessary treatments. The health parameter data of each patient are embedded in a separate block in blockchain technology with SHA-256-based cryptography hash values. Mining computing nodes are responsible to find a 32-bit nonce (number only used once) value for each data block to compute a valid SHA-256-based hash value in blockchain technology. Computing nonce for valid hash values is a time-taking process that may cause life losses in the healthcare system. Increasing the mining nodes reduces this delay; however, the uniform distribution of mining data blocks to these nodes by considering the priority data is a challenging task. In this work, an efficient scheme is proposed for scheduling nonce computing tasks at the mining nodes to ensure the timely execution of these tasks. The proposed scheme consists of two parts, the first one provides a load balancing scheme to distribute the nonce execution tasks among the mining nodes such that makespan is minimized and the second part prioritizes more sensitive patient data for quick execution. The results show that the proposed load balancing scheme effectively allocates data blocks in different mining nodes as compared to round-robin and greedy algorithms and computes hash values of most of the higher-risk patients’ data blocks in a reduced amount of time.

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