Control plane improvement for video dissemination in Software Defined Unmanned Aircraft Networks
SDN, UAV, and QoE
With the emerging development of Smart Cities, monitoring services is also increasingly becoming crucial for citizens and government in daily life applications, such as domestic electricity measurements gathering and traffic light control, which are composed by predicted events. Moreover, Flash Crowd events, considered as non-predicted events that shall require extra network resources in order to provide in-situ services (such as video transmission in a natural disaster context, critical emergency data, robber or kidnapping tracking for police force), may be highly recommended in a Smart City environment. On the one hand, the predicted events can be easily tracked by the infrastructure built for its purpose. Besides, it's possible to know most of the occurrence details, such as time, average frequency and location. On the other hand, Flash Crowd events monitoring may be an issue as its details are completely unknown. Researches had already shown the viability of Unmanned Aerial Vehicles (UAVs) to track predictable and scheduled events. Moreover, UAV-Network seems to be a suitable technology to work in monitoring Flash Crowd events since its nodes are capable to quickly reach any location in an short period of time, collect and re-transmit the most kind of sensor data, facilitating and shortening the decision-making response time for Flash Crowd events. This work aims to present a UAV-Network architecture based on Software Defined Network (SDN) paradigm to support the management and control of UAV-Networks to monitor Flash Crowd events in Smart City scenario. SDN enables the management automation of the network resources, making feasible a fast and reliable allocation of those. UAV is a emerging technology that aims to enrich the variety of services that shall be provided in a Smart City scenario. Moreover its might be a key tool to reach the requirements of the 5G.