# Designing a Softwarized Network Deployed on a Fleet of Drones for Rural Zone Monitoring
## 1 Introduction
Cloud computing is a new Internet-based computing paradigm that provides shared computer processing resources and data to any device on demand, so enabling ubiquitous, on-demand access to a pool of configurable resources (e.g., computer networks, servers, storage, applications and services) which can be rapidly provisioned and released with minimal management effort. SDNs and NFV, on the other hand, are two paradigms for network softwarization, the first aimed at decoupling the control plane from the data plane [26; 27], and the second enabling the network infrastructure to be virtualized as building block classes and functions managed by a centralized orchestration entity called management and orchestration (MANO) [28; 29; 30; 31; 32]. Deployment of SDN has been extensive in fixed infrastructure-based networks, especially in networks within data centers. More recently, both academia and the industry are manifesting increasing interest in application of SDN in dynamic mobile wireless environments [33; 34; 35; 36; 37; 38]. More specifically, SDN results very suitable for UAV networks where nodes are non-permanent, connectivity is intermittent and channels may be impaired. In this context, SDN is able to easily change flow paths dynamically after topology modifications due for example to link intermittence, or node failures because of battery drainage. Up to now, at the best of our knowledge, works using both softwarized and non-softwarized networks of drones in an agriculture scenario are limited to sensor applications, where the network is able to gather data from sensors (e.g., soil humidity [39], gases or smoke from fires, air quality in different layers of the atmosphere [40], etc.) in order to react with some action like, for example, efficiently spraying pesticides and fertilizers on crops [41]. Application of a joint SDN/NFV paradigm has led some researchers to overcome the limitation of drone systems developed for specific applications. Authors in [42; 43] introduced for the first time the idea of integrating UAVs with the cloud, and then in [44; 45] proposed leveraging on the SDN and NFVto realize a cloud platform for developing drone applications for accessing UAVs through a third party. Drone connectivity scenarios have already been considered in recent 3 GPP Release 14 documents [46], but are limited to consideration of the remote control of drones. A step ahead is done in [47], which considers the utilization of drones equipped with base stations (BS) to realize a multi-tier drone-cell network to complement the terrestrial HetNets, and propose a management framework based on the SDN/NFV paradigm. However, one of the main challenges in deploying cloud and fog computing paradigms on fleet of drones is battery duration, since computing hardware is powered by the same energy source of the drone engine: an excessive computing power required by the fog-computing node installed on a drone would compromise its flight duration. With all this in mind, this paper proposes a video monitoring platform as a service (VMPaaS) for wide rural areas not covered by Internet access. The platform is realized with a FANET, whose target is providing connectivity backbone, and a set of drones equipped with high-resolution cameras, each transmitting a video stream of a portion of the considered area. This platform, thanks to its flexibility due to the application of the cloud/fog and the SDN/NFV paradigms, allows, on the one hand, third-party users to contribute to the whole service by installing new cameras on the area or launching new video-transmitter drones that automatically connect to the platform, and on the other hand, users to connect to the platform and, through their terminal, choose one or more cameras to receive video flows of interest.