A security analysis of lightweight consensus algorithm for wearable kidney

In recent times, blockchain has encouraged innovations to handle challenges in many practical applications in which traditional approaches are not found to be successful. This work has proposed a game theory-based approach for consensus building in a distributed network. In this work, the wearable kidney model is analysed to understand the working of the game-theory-based consensus model. The lightweight consensus algorithm consumes fewer resources (suitable for resource constraint devices) and provides an efficient solution to simulate the functionality of a wearable kidney model. The comparative analysis of the result shows that the proposed approach is efficient in fast bit-matching and quick consensus establishment and the kidney blood and urine production are mapped to almost ideal conditions, and variations in delay for bit-matching and algorithm executions are evaluated after that. The comparative analysis shows that algorithm 1 outperforms (at least 2.1%) algorithm 2 in delay analysis because of less distributed functionality.