Abstract
This study aims to improve execution time, CPU utilization, network efficiency, and scalability while upholding robust security measures. The IOTA-DLT-based RA-WRW algorithm is developed in Python, considering node resources and transaction weights for optimal tip selection—verification procedures confirming tip authenticity and transaction validity. The algorithm significantly improves IOTA network transaction processing efficiency tips exhibit high authenticity and consistency, affirming the algorithm's effectiveness. The research presents the innovative IOTA-DLT RA-WRW algorithm, which integrates Resource Allocation (RA) and Weighted Random Walk strategies. This novel approach tackles challenges like lazy tip selection, network congestion, and double spending. By performance parameter and the tip selection process, the algorithm improves comparative analyses against existing methods and confirms the superior performance of our model, boasting high accuracy, f-measure, recall, precision, and scalability in distributed ledger transactions, significantly enhancing the IOTA network's transaction processing capabilities.
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