Identifying crucial nodes is a key aspect of analyzing networks, addressing which nodes have the maximum influence on network functionality and whose removal would cause the most disruption. Many iterative selection methods and heuristic approaches have been employed to determine these critical nodes. The paper surverys the top iterative selection algorithms to the detection of critical nodes in complex networks. Additionally, we discuss our use of the RPL-powered 6LoWPAN Cooja simulator in testing these methods, highlighting its effectiveness in simulating complex network scenarios and enhancing our understanding of node influence.