Enhancing Node Selection in Blockchain-Enabled Edge Internet of Things (IoT): A Fuzzy Logic Approach for Improved Performance

Abstract

The rise of connected and smart devices has heightened the demand for robust Internet of Things (IoT) applications, necessitating enhanced data storage and processing. Traditional cloud-based IoT systems, often distant from users, grapple with issues like server load, slow responses, and limited mobility. Edge computing counters some of these problems by bringing processing closer to users. Selecting appropriate nodes also addresses common IoT challenges such as network lifetime, resource allocation, and data reliability, ensuring optimal intervals for node selection. Integrating edge and blockchain tech in IoT introduces new perspectives on access control design. This study introduces an innovative approach using fuzzy logic for node selection in blockchain-powered edge IoT. Fuzzy logic processes numeric and linguistic data concurrently, alongside the Technique of Preference Ranking by Similarity of Ideal Solution (TOPSIS) for Multi-Criteria Decision Making (MCDM). This fuzzy-based method enhances IoT node selection efficiency, with three entry criteria, significantly ameliorating considered parameters, as demonstrated by experimental results.