Using Clique to Identify Access Points with High-Density Coverage in Different Locations

This study aims to identify sensor network devices located in areas of high connection density within a network. By doing so, it will be possible to determine regions with dense and more comprehensive connectivity. The dataset used in this study is modeled as a disc graph representing a university’s campus network. In the disc graph, overlapping areas are depicted as edges in the original graph, with the number of these edges indicating the extent of connectivity and coverage. To identify these dense edges in the designed network, the maximum clique approach has been applied. The members of the maximum clique have been determined using the Malatya independent set algorithm. The study aims to prevent the overlap of maximum cliques in the same area, focusing on identifying maximum clique members that are not directly connected to each other. The resulting data provides critical insights into the hub points of the network and the optimal placement of main routers.