# Routing Protocols for UAV-Aided Wireless Sensor Networks
## 4 Routing Protocols for UAWSNs
### Network Structure-Based Routing
#### 4.1.1 Flat Routing  
Hybrid heuristic approach (HHA): [PERSON] et al. worked on data gathering via UAVs in WSNs that have a delivery-limit constraint [35]. The network is assumed to be a wireless sensor network graph, where a set of UAVs have a different limited buffer size. There are time-window constraints for UAV nodes along with the delivery limit. The goal is to find an efficient set of paths for the UAVs to accumulate sensor data at certain places and deliver these data to the sink node by fulfilling the mentioned constraints. A mathematical analysis of the problem, along with the hybrid heuristic approach (HHA), was also presented. The heuristic approach includes an improvement mechanism, which is well suited for the data-gathering purpose of UAVs. The simulation results showed that the heuristic is capable of solving the problem for a wide range of data sets and deadline ranges. The protocol can be improvised further to work with multiple base stations and self-managing UAV nodes in clusters. UAV-enabled sensor node (SN-UAV): SN-UAV [36] is a flat-topology routing protocol that addresses the problem of energy scarcity and network lifetime for the UAV working as a mobile data collector for sensor nodes (SNs). The wake-up schedule of the SNs and the trajectory of the UAV are optimized in a combined way to reduce the energy consumption while confirming that the amount of data needed is gathered from every single WSN. In SN-UAV, UAVs are deployed as mobile data collectors to obtain data from SNs in the ground. The optimization problem of the wake-up schedule and the UAV trajectory is designed as a mixed-integer non-convex problem, which is solved using an iterative algorithm. The technical strength of SN-UAV lies in its reliable data collection in the fading channel. The protocol is also suitable for multi-UAV scenarios. UAV-WSN-based border surveillance (UAV-WSN): To prevent dangerous entities from entering, UAWSNs can be a promising technology for border surveillance. Owing to this concept, [PERSON] et al. proposed a multilayer hybrid architecture to design a surveillance system for border monitoring by using cameras, scalar sensors, radars, and UAVs [37]. They also addressed an activation scheduling strategy based on load balancing and energy saving. The main purpose and aim of the proposed scheme in Reference [37] is to track and detect any border intrusion in the possible human involvement. There are three kinds of nodes used in the network. They are scalar sensors, multimedia sensors, and UAVs. They collaborate with each other to build an efficient intrusion detection system. Scalar sensors form the first layer called the detection layer. This layer is responsible for intrusion detection. Once the scalar sensors detect any kind of intrusion, an alert is sent to the multimedia sensor nodes which constitute the second layer of the network. Finally, UAVs are called upon to track the intruder after they receive necessary information from the multimedia sensor nodes. The majority of existing UAV-aided systems suffer from a decreased network lifetime that is overcome in the scheme proposed in Reference [37]. Although the network is designed with three-layer hierarchy, data transmission (i.e., routing) among the three layers is flat-based. That is why UAV-WSN is classified as flat-based routing. UAV-based automated sensor deployment for mobile sink (UAV-AS-MS): [PERSON] et al. proposed a new method that combines a heterogeneous WSN based on a multi-agent system and a mobile agent (UAV) for data acquisition in places that are inaccessible for a human being [38]. The goal is to automate the network deployment and data acquisition. The primary concern is to facilitate data gathering beyond the communication range of sensor nodes in the network. According to Reference [38], a UAV is responsible for transporting and releasing sensors at a certain location that is considered dangerous to access through direct human intervention.