EFTA: An Energy-efficient, Fault-Tolerant, and Area-optimized UAV Placement Scheme for Search Operations

Unmanned aerial vehicle (UAV) networks have widespread applications, ranging from surveillance and disaster management in the military domain to transportation and delivery of goods in the civilian domain. Regardless of the application, the placement of routing UAV nodes (especially in networks spanning long distances) is crucial in determining network performance parameters such as network lifetime and data transmission delay. In this paper, an Energy-efficient, Fault-Tolerant, and Area-optimized UAV placement scheme (EFTA) is proposed for search operations. A cluster-based UAV network is considered, in which the Cluster Members (CMs) are mobile and scan the geographic area of interest. The Cluster Heads (CHs) are quasi-static and route information from the CMs to the Ground Control Station (GCS). A multi-objective Cuckoo Search Algorithm is used to determine the placement of the CHs while minimizing energy consumption, maximizing area coverage, and maximizing tolerance to node failures. Further, a comprehensive analysis was performed against a state-of-theart UAV placement algorithm. The analysis showed that EFTA gives a significant performance improvement when compared to the competing placement scheme in fault tolerance, power consumption, network lifetime, end-to-end delay, and packet delivery ratio.