# Development, Implementation and Evaluation of An Epidemic Communication System
## 2 Related Works and Issues
These algorithms are used to transmit information in distributed systems; among which, the epidemic algorithm demonstrated resilience to network delays and uncertainties with a small protocol overhead. The results of these evaluations indicated that the epidemic algorithm could transmit information more efficiently than the other algorithms. Epidemic communication has been shown to efficiently disseminate data, particularly when the number of terminals is high. However, realizing any of these algorithms is challenging, given the network conditions and device constraints. Figure 2: Example of epidemic communication in action. Next, we introduce an example of implementing epidemic communication to address the challenges in (B). In [12], the authors implemented an epidemic routing protocol using Network Simulator ns-3. Message diffusion was achieved using direct communication between the nodes for implementation. Although the simulation confirms that data are diffused in space up to the destination node using epidemic communication [12], factors such as radio interference affecting the surrounding nodes are not considered. However, few studies have been found on radio interference issues related to epidemic communications because many researchers are interested in mathematical models and do not assume implementation. Therefore, we investigated radio interference in ad hoc networks, which is similar to epidemic communication. Interference models for ad hoc networks have evaluated the impact of interference at various layers [29; 30]. The reason why the impact of interference per layer is evaluated is that ad hoc networks are based on the assumption that network routing is constructed, and the impact of interference varies depending on the configuration of the network topology. In addition, authentication and association procedures must be followed in the communication protocol. Epidemic communication, on the other hand, does not require the construction of network topologies or routing tables in order to cause infection. The connection procedure is also not suitable for infectious disease communication and cannot be solved by conventional ad hoc communication technology issues. Therefore, the challenges are to optimize the transmission and reception power that can be communicated, and the communication area for communication while moving, as well as interference when nodes are densely packed in a simple short distance. Finally, the challenges in (C) concern the absence of commercially available wireless devices designed for the services envisioned. However, epidemic communication is considered as an effective communication method in scenarios such as information sharing between ITSs, robots, and drones, where the information does not include personal data. The novelty of this paper is to design and develop a wireless system that is designed to be implemented in drones, based on the organization of the issues in these related works. Epidemic communication is the random spread of information by an infection method. Ref. [14] proposed the efficient method of conveying information by giving directionality to infection. For example, they proposed increasing the efficiency of infection by adding the distance that drones move in a specific direction to randomly moving drones, or by giving them radio wave directionality. On the other hand, in this study, we have examined the issues involved in actually implementing epidemic communication in a device, and solved these issues by evaluating them through theoretical analysis and experiments. However, the proposed method in Ref. [14] can be made into the device developed in this study, and this is a theme for future work. Moreover, the communication distance of the drone depends on the wireless device to be implemented. However, for epidemic communication, it is desirable to communicate at short distances, where interference to the surroundings can be avoided. In other words, the upper limit of the number of drones in a cluster is not a problem if it is not affected by interference.