A Content-based Clustering and Routing Method with Artificial Intelligence and Fuzzy Logic Infrastructure for the Internet of Things

Internet of Things in technology studies is a new concept in which any object can receive data through communication networks such as the Internet and send it if necessary. Clustering in wireless networks has been proposed and used as a solution in the field of Internet of Things in various protocols. In this study, first a method based on fuzzy logic is proposed for clustering the Internet of Things network. In this method, the parameters of residual energy, node hardware capability, number of neighbors, cluster head distance and data type are used to select cluster heads. Then, based on the presented clustering, a routing method is proposed and proposed. In this routing protocol, we have selected the parameters of residual energy, possible bit rate, buffer queue length and data type for the best path. The data type parameter is used by the proposed routing and also the proposed clustering; In this way, the data is classified into two groups: multimedia and text, and therefore, routing will be performed based on the content. The evaluation results show that the proposed method improves energy consumption, network lifetime, latency, and data delivery rate at the destination compared to previous methods.

Keywords:

Clustering , fuzzy logic , content-based routing , Internet of Things