Simulation of Clustering Protocol and Mobility Model for UAV Networks

Abstract

The network of autonomous Unmanned Aerial Vehicles (UAVs) is a powerful system that can assess the severity of damages during disaster events and support search and rescue missions. UAVs can carry payloads such as cameras, sensors, and a built-in navigation system and can be readily deployed in the surveillance region with limited or no infrastructure support. This work assumes that UAVs can be randomly deployed in the affected area for surveillance. The network is then arranged in the form of clusters of UAV nodes to create a hierarchy and aid in the collection and routing of sensed data. Metrics of residual energy and connectivity have been used to select a Cluster-Head (CH) node iteratively. This proposed clustering algorithm has been detailed in this paper. For the implementation of this protocol, an integrated platform of ROS and NS3 has been utilized to provide a more realistic deployment scenario. The proposed clustering protocol has been compared with prominent clustering protocols of Wireless Sensor Networks (WSNs) such as Hybrid Energy-Efficient Distributed (HEED) and Low-Energy Adaptive Clustering Hierarchy (LEACH) for analysis of parameters such as the lifetime of the network and clustering overhead. The mobility model achieved from the robot simulator has been compared against probabilistic mobility models available in the network simulator. The proposed deterministic clustering protocol outperforms in terms of network lifetime against prominent clustering protocols. Upon stimulation, it has also been observed that the realistic mobility model obtained from the robot simulator is more suited for real-world applications.