# Designing a Softwarized Network Deployed on a Fleet of Drones for Rural Zone Monitoring
## 1 Introduction  
With the rapid development of digital information technology, digital convergence (i.e., integration of a variety of all types of information such as data, voice and video through convergence terminals and services) is expected to lead people to a smart society in which anyone can use personalized services anywhere and anytime [1]. Unfortunately, the reality is that there is an ever-increasing difference between information communication technology (ICT) infrastructures when comparing urban and rural areas. This is the so-called digital divide, which is mainly due to the business situation where broadcasting and communication operators are reluctant to invest in rural ICT infrastructure, which seems much less profitable [2]. However, ICT infrastructures could strongly help rural communities and cooperatives where many operations, such as inspection and maintenance, are time consuming, labor-intensive and expensive due to limited access and large distances to cover. For these reasons, new programs are reported in a number of recent studies, and solutions are required in projects relating to rural ICTs for bridging information and service gaps between rural and urban communities (see [3, 4]). One of the most attractive solutions, which is widely recognized as promising for filling this gap, is the use of aircrafts without a human pilot aboard, commonly known as unmanned aerialvehicles (UAVs) or drones. Originally produced mostly in military applications, recently they are beginning to be used outside that domain [5; 6; 7], in large part because they can execute the \"dull, dirty, and dangerous\" tasks over extended time periods [8]. According to a recent study [9], civil UAV drones are now vastly outnumbering military ones, with a market only in the United States that could reach USD$560 million at the end of 2017. Thanks to their versatility, flexibility, easy installation and relatively small operating expenses, they are applied to many scenarios as commercial, scientific, recreational, and agricultural ones. Common applications include search and destroy operations, border surveillance, wind estimation, disaster relief, remote sensing, traffic monitoring and precision agriculture [10; 11]. In the first period, these various application opportunities have encouraged researchers and developers to focus more on improving the flight efficiency of a single drone. However, in many real-world situations there is a need to develop a drone system that is able to last much longer than the endurance of an individual UAV [12; 13; 14; 15]. A solution is to use a fleet of small-scale drones combined with methods and algorithms that leverage collaboration between multiple (possibly miniature) drones. This is the case, for example, of the idea in [16], where the authors proposed a technique of autonomous battery change/ recharge stations, which are equivalent to refueling stations. Additional advantages over the use of a single drone are in terms of covered area, load balancing, mission scalability, time efficiency, and fault tolerance. A number of applications have been proposed for fleets of drones such as managing disaster situations [17; 18], retrieving information from sensors deployed in areas that are not easy for humans to access, or even transmitting live audio/video from sports events involving fast-moving people, such as bicycle races or skiing competitions. Of course, employing a fleet of drones as a team requires strong connectivity among drones, as discussed in [19; 20; 21], where a multi-drone communication platform is defined to support applications that require coordination of multiple drones, and in [22], where the concept of a flying ad-hoc network (FANET) is introduced as a highly mobile wireless mesh network [23; 24; 25]. Three elements that can support this trend in the immediate future are cloud computing and the two recent networking paradigms, software-defined networks (SDNs) and networks functions virtualization (NFV).