A new selfish thing detection method based on Voronoi diagram for Internet of Things

Internet of Things (IoT), as an emerging technology, describes a smart world that enables objects to interact with each other and with end-users through developed communication platforms such as the Internet. The limited communication range of things allows packets to be transmitted between objects that are not in each other's range through intermediate objects, which highlights the necessity of routing in this technology. Therefore, the Quality of Service parameters of IoT entirely depend on the cooperation of things in the routing process. Several factors such as energy depletion, conquering objects by an enemy, and resource constraints lead to selfish behavior that may cause network collapse. In this paper, a new watchdog-based identification method is presented to diagnosis selfish objects in the Internet of Things, in which the selected watchdogs are responsible for evaluating the activity of other objects. In the proposed method to achieve a uniform distribution of watchdog objects in the network, the IoT objects are partitioned into disjoint cells using the Voronoi diagram, and a watchdog is selected for each cell. In this way, while the supervision overhead is distributed, the watchdog objects can identify the selfish things through examining the remaining energy and cooperation degree of other objects. The conducted simulations in the MATLAB tool have validated the effectiveness of the proposed method in terms of detection rate, false-positive rate, throughput, end-to-end delay, and energy consumption.