UAVs assessment in software-defined IoT networks: An overview

2020-01-15
Al-Turjman, Fadi
Abujubbeh, Mohammad
Malekloo, Arman
Mostarda, Leonardo
The technological advancements in the ubiquitous IoT era and the ever-growing desire of communities to enforce smart cities with security and safety of user data as their priority, mini Unmanned Aerial Vehicles (UAVs), or drones, are perceived as a tool for raising living standards by meeting the requirements of societies. Traditionally in UAV communication links, meshed ad hoc networks were among the first options of connectivity. However, the increased demand for deploying multi-UAV networks necessitates the development of a more robust and more secure networking infrastructure. In this regard, Software-Defined Networking (SDN) paradigm has proved to be the better alternative for multi-UAV communication since it can offer flexible services for management and control owing to its unique features such as decoupling control from UAVs and network programmability. Therefore, in this paper, we provide an overview of drone applications in SDN-enabled Drone Base Stations (DBS), surveillance monitoring and emergency networks, and review the performance assessment techniques and the associated cybersecurity aspects in these applications. Moreover, future research directions, after a thorough analysis of the literature, is presented in this paper. Through the development of an innovative and multifaceted drone performance-assessment framework with the primal concerns, that are meeting user-defined requirements and the provision of secure and reliable services, it is, therefore, necessary to advance in IoT-enabled spaces. We believe the present work is a step in the right direction, and it is essential for fastening the movement toward UAV-enabled smart cities.
COMPUTER COMMUNICATIONS

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Citation Formats
F. Al-Turjman, M. Abujubbeh, A. Malekloo, and L. Mostarda, “UAVs assessment in software-defined IoT networks: An overview,” COMPUTER COMMUNICATIONS, pp. 519–536, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67607.