Secure Cloud Controlled UAS Operations

Integrating a small unmanned aircraft system (sUAS) with cloud capabilities for military or enterprise use has not usually been feasible due to cybersecurity concerns. With recent advancements in blockchain networks the possibility of large cloud connected UAS networks has emerged. Our team investigates how to integrate data collected from a sUAS with a cloud-based service for data collection, storage, and processing implemented to ensure data privacy and data integrity. Our proposed network architecture implements a blockchain network to maintain decentralized security for the network. The research’s objectives include running security tests against a blockchain network & host/client networks and then comparing their performance and abilities to support the cloud based UAS. Specifically, we are using an open-source project called AirSim to support a virtual UAS that is connected to the UAS flight controller, the Pixhawk, to test a hardware-in the loop solution. This test is a preliminary proof of concept, and after it proves successful we are moving to a test involving a physical UAS. Data is transmitted from the UAS to a client server in Amazon Web Services (AWS) where it is placed into a blockchain and sent to the host server for processing. Overall, we believe a cloud supported communication network with a blockchain to secure data is an efficient and wise method of UAS control with information processing

ASR-FANET: An adaptive SDN-based routing framework for FANET

Flying ad hoc network (FANET) is widely used in many military, commercial and civilian applications. Compared with mobile adhoc network (MANET) and vehicular ad hoc network (VANET), FANET holds unique characteristics such as high mobility, intermittent links and frequent topology changes, which cause a challenging task in the design of routing protocols. A novel adaptive software defined networking (SDN)-based routing framework for FANET called ASR-FANET is proposed in this article to solve the above challenges. The ASR-FANET framework is mainly composed of three important parts, which are the topology discovery mechanism, statistics gathering mechanism and route computation mechanism. In topology discovery mechanism, the periodic information about network topology is collected, including nodes and links. In statistics gathering mechanism, the status of the wireless network connection and flight statistics are collected. In route computation mechanism, the optimal path is calculated based on link costs. The performance of ASR-FANET framework is also has been evaluated by comprehensive simulations. The simulation results show that proposed framework is much better than other traditional protocols in packet delivery fraction, average end to end delay, normalized routing load, packet loss and throughput