# An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs
## 1 Introduction  
Unmanned aerial vehicles (UAVs) have shown tremendous growth, both in the areas of research and application. UAVs are capable of supporting a wide range of civilian and military applications as a result of their flexible movements and ease of configurations [1; 2]. UAVs can further be deployed to form collaborative networks with the ground nodes. The cooperation between ground and aerial nodes has resulted in significant gains in data dissemination, monitoring, and control over strategic locations. UAVs also prove significant when it comes to data gathering from inaccessible locations. One such case is autonomous networking where UAVs help with raising the problem of coverage, failures, limiting guidance and dead nodes by acting as supervisors [3]. Efficient and intelligent surveying is one of the key aspects of UAV networks. Nature-based algorithms help in performing cooperative rendezvous and efficient task allocation for coordinated UAV networks [4]. A cooperative ground to air surveillance mechanism that employs UAVs for broad coverage and ground nodes for a detailed zoomed in picture of the area under surveillance is presented in [5; 6; 7]. The various UAV application scenarios are presented in Figure 1. The multi-hop characteristics of WSN data transmission were replaced by direct communication between UAV and sensor nodes where UAVs served as sinks [7; 8]. Alongside available performance gains, the network formation and setting up way-points for UAV movements are an issue. Efficient deployment of available resources can help improve the coverage and reduce the number of hops, in turn, boosting the overall throughput. Wireless Sensor Networks are spatially dispersed energy concentric dedicated sensor nodes, largely deployed in inaccessible locations. A few major applications of WSN include air pollution monitoring, forest fire detection, landslide detection, water quality monitoring, natural disaster prevention, industrial monitoring, machine health monitoring, data center monitoring, data logging, waste water monitoring, structural health monitoring and wine production [9; 10; 11]. Due to their small size and ease of deployment, WSNs have found their applications in varying fields, but this comes with an inherent drawback. WSNs are energy sensitive devices and suffer from depletion constantly. Moreover, they are deployed in such specific areas where human intervention is not necessarily possible. A major amount of energy is depleted while finding an optimal path and multi-hopping transmissions. This optimal path finding becomes a major issue as the sensor nodes die frequently due to their charge depletion resulting in iterative re-searching. Also together with path selection, the multi-hopping produces un-necessary traffic, delays and packet drops. These issues present an opportunity towards an efficient mobility model where WSN nodes are applied alongside UAV and also help facilitate efficient data dissemination. In order to test protocols, real-time scenarios or disaster management practices, simulations serve as a major test bed. To adapt to the real-time traffic and realistic environment conditions, the mobility model must be able to represent a realistic scenario. The mobility model defines a movement scheme that mimics the real world movements, traffic and response scenarios. One key characteristic of a good mobility model is its ability to adapt to the dynamically changing network behavior. The major vehicular mobility models are classified as synthetic, survey-based, trace-based and traffic simulation-based models. Synthetic models include the mathematical representation of the realistic scenarios, whereas survey based models are basically derived from the movement surveys conducted by authoritative organizations. Trace-based models are built over real-time mobility traces. Trace based models are preferred over both survey and synthetic models as it is not always possible to devise a mathematical representation of the mobility or conduct a survey in order to gather information.