Multi-Agent Redundant Clustering Scheme for E-Health Reliable Data Transmission in Crisis Scenarios

A UAV-based wireless network is made up of UAVs working together to upload data to the internet. During crisis scenarios like earthquakes or floods, UAVs are highly used in transmitting valuable health-related data. Basic physiological life-saving parameters like blood pressure, temperature, and respiration rate can be tracked by sensors built into UAVs. One of the most reliable routing techniques in UAVs is clustering, where the network is separated into clusters, each of which has a cluster head (CH) and cluster members (CM). Having a damaged CH results in a disconnected cluster and loss of data. Several routing schemes target reducing delays, but ensuring a functional CH is a topic rarely discussed. Our proposed scheme targets both reducing delays and ensuring a functional CH through multiple redundancy and node type variation to ensure health data transmission. This paper suggests an enhanced redundant routing scheme based on four weighted parameters, which are the distance stability, the rewarding stability, the velocity stability, and the energy stability. The network will be formed of UAVs and vehicles to maximize the likelihood of a functional CH. The weighted calculation will result in a customized metric utilized in cluster formation. To guarantee connection stability, whenever the primary CH is not operating, a redundant CH handles the routing responsibilities. The proposed protocol was simulated using MATLAB. The results obtained demonstrated that our proposed scheme is promising in optimizing the cluster formation while reducing total delays and ensuring a functional CH.