Virtual Network Function Placement for Mapping SFC Requests of UAV-Sourced Video Streaming in Cloud Networks

Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. They are particularly useful in applications of video surveillance, especially in modern battlefield. However, due to the large amount of resources consumed by video streaming, the issue of poor resource utilization still prevents the use of multi-UAV systems for sharing videos with users in a stable and reliable way. Since the development of network function virtualization (NFV), traditional dedicated network devices in cloud networks can be implemented as software and network functions (NFs) can be flexibly instantiated on common off-the-shelf servers, enabling NFs to be deployed in the form of virtual network functions (VNFs) and hence improving the resource utilization in communication networks. In this article, we investigate the VNF placement problem for mapping users' service function chain requests (SFCRs) of UAV-sourced video streaming in cloud networks. To be more practical, we consider the fundamental resource overheads and synchronization cost of virtual machines (VMs) on servers for processing VNF requests. The VNF placement problem is formulated as an integer linear programming model with the aim of minimizing the total resource consumption under the constraints of the delay requirements. We propose a node ranking-based method (UAV-MA) to find a near optimal solution for UAV-sourced video streaming, including an SFCR mapping phase to map SFCRs onto servers and an adjustment phase to refine the placement of VNFs. Evaluations demonstrate that the proposed approaches can derive a resource-efficient VNF placement strategy, outperforming baseline methods.