# An Efficient Relayed Broadcasting Based on the Duplication Estimation Model for IoT Applications
## 2 Statement of the Problem
### Related Work  
Flooding mechanisms have been extensively studied in mobile ad hoc networks, especially for the purpose of routing [10; 12]. Depending on the criterion or means of broadcast suppression, they can be largely classified as \((i)\) probability-based flooding (PBF), \((ii)\) counter-based flooding (CBF), and \((iii)\) distance-based flooding (DBF). The basic idea behind these mechanisms is as follows: each node determines the relaying (or rebroadcasting) of a frame with a given probability as long as the number of duplicate frames received is smaller than the counter threshold or when the distance between itself and the adjacent relay node is larger than the distance threshold. The value of the probability or the threshold is usually predetermined or fixed in conventional flooding mechanisms [10; 12], and so their performance critically depends on one of these predetermined values which is unadaptable to changes in network conditions like the number of nodes or the size of the network. Moreover, the optimal value of probability or threshold may be different for each node. To overcome these drawbacks, many variants of conventional flooding mechanisms have been proposed. In [13], dynamically adjusting the probability of rebroadcast depending on the density of the nodes (i.e., the number of adjacent nodes) was suggested; the node in a dense area rebroadcasts frames with a low probability to mitigate the redundancy whereas a high value of probability is used in a sparse area to improve the reachability of frames. According to [14; 15; 16], the probability of rebroadcasting is calculated by considering the additional coverage due to it as well as the degree of connectivity, which is analogous to the number of adjacent nodes. Subsequently, if a frame can be delivered to more adjacent nodes, it is preferentially transmitted. Similarly, the mechanism proposed in our previous work [11] sets the rebroadcast probability as inversely proportional to the number of adjacent nodes but unlike the conventional PBF, it does not drop the duplicate frame but defers the transmission to improve the reliability of flooding. The performance of CBF can be improved in a similar way. In [17], the value of the counter threshold was adjusted as a function of the number of adjacent nodes. The study in [18] proposed using multiple differentiated levels of the counter threshold depending on the number of adjacent nodes. Meanwhile, there have been several approaches to enhance the performance of DBF. Instead of using a pre-determined threshold of distance, the study in [19] suggested using three differentiated values of the rebroadcast probability depending on the distance from the sender, i.e. if the node is far from (or close to) the source node, it has a higher (or lower) rebroadcast probability. A similar idea was applied to vehicular ad hoc networks [20]; depending on the distance between two adjacent nodes, the rebroadcast probability or delay is controlled so that the traffic dissemination time can be decreased while decreasing the redundancy. It was proposed in [21] to set the distance threshold by considering the probability of transmission failure due to channel error, i.e., a smaller threshold is used if the quality of a wireless channel worsens. Furthermore, a hybrid approach of combining PBF and CBF has been proposed in the literature. In [22], the rebroadcast probability was set based on the number of duplicate frames received; if the number of duplications was greater or smaller than a predetermined counter threshold, the transmission probability was decreased or increased accordingly. The study in [23] proposed that the node rebroadcasts a frame at a fixed probability if the number of duplications is less than the counter threshold; otherwise, the node drops the frame. It was also proposed in [24; 25] to dynamically control the rebroadcast probability depending on the number of duplications such that the probability decreases as the number of duplications increases.