Variable-categorized clustering algorithm using fuzzy logic for Internet of things local networks

This paper presents a variable-categorized clustering algorithm (VCCA) using fuzzy logic for Internet of Things (IoT) local networks. The VCCA selects the cluster head (CH) that has the highest network capacity through a classification process of cluster variables in accordance with the characteristics in order to configure a clustered network, which differs for different IoT applications. To achieve this, the VCCA employs a fuzzy inference system (FIS) that calculates an outcome through rule-based variable mapping for low complexity in the CH election and high scalability of cluster variables. In addition, experimental simulations using MATLAB are conducted to evaluate the performance of the VCCA. The simulation results show that the VCCA exhibits better network performance compared to the existing algorithms in terms of throughput, end-to-end latency, network lifetime, and energy consumption.