CCNSim: An artificial intelligence enabled classification, clustering and navigation simulator for Social Internet of Things

Abstract

With the advent of the IoT technology stack and the need for information and process ubiquity, social IoT (SIoT) is becoming popular to cater to intelligent and connected living needs. Furthermore, increasing AI-based big traffic data analytics for device and service discovery, service and application recommendations, and personalizations have garnered interest from the research community. To satisfy the needs of lifestyle research problems like smart-city applications, we propound a SIoT simulator called CCNSim, which offers basic network simulator functionalities and sophisticated AI-based traffic analytics and visualization. The proposed functionalities form a middleware that enables communication between the hardware and software interfaces. In addition, the proposed middleware offers a configuration environment for object selection and navigation, service provisioning, object profiling, service and application recommendations, and user behavior predictions. The simulation experimentations and results emphasize the scope and ease of use of the proposed simulation framework.