Abstract
Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to establish a Flying Ad-hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapidly deployable systems. In this context, Software-Defined Networking FANET (SDN-FANET ) separates the control and data plane and provides network programmability, which considers a centralized controller to perform all FANET control functions based on global UAV context information, such as UAV positions, movement trajectories, residual energy, and others. However, control message dissemination in an SDN-FANET with low overhead and high performance is not a trivial task due to FANET particular characteristics, i.e., high mobility, failures in UAV to UAV communication, and short communication range. With this in mind, it is essential to predict UAV information for control message dissemination as well as consider hierarchical network architecture, reducing bandwidth consumption and signaling overhead. In this article, we present a Cluster-bAsed control Plane messages management in sOftware-defined flying ad-hoc NEtwork, called CAPONE. Based on UAV contextual information, the controller can predict UAV information without control message transmission. In addition, CAPONE divides the FANET into groups by computing the number of clusters using the Gap statistics method, which is input for a Fuzzy C-means method to determine the group leader and members. In this way, CAPONE reduces the bandwidth consumption and signaling overhead, while guaranteeing the control message delivering in FANET scenarios. Extensive simulations are used to show the gains of the CAPONE in terms of Packet Delivery Ratio, overhead, and energy compared to existing SDN-FANET architectures.
Highlights
Unmanned Aerial Vehicles (UAVs) are commonly used for autonomous missions, such as search and rescue missions [1], border surveillance [2], wildfire management [3], traffic monitoring [4], remote sensing [5], and other smart applications
CAPONE reduces the bandwidth consumption and signaling overhead, while guaranteeing the control message delivering in Flying Ad-hoc Network (FANET) scenarios
Based on UAV contextual information, the controller is able to predict UAV information without disseminating control messages. It divides the network into groups of UAVs to reduce the network overhead while guaranteeing the control message delivering in FANET scenarios
Summary
Unmanned Aerial Vehicles (UAVs) are commonly used for autonomous missions, such as search and rescue missions [1], border surveillance [2], wildfire management [3], traffic monitoring [4], remote sensing [5], and other smart applications. For the control plane point of view, in each group, the CH works as a local controller to perform more complex tasks, while group members only send UAV contextual information based for the CH In this sense, CAPONE minimizes the number of control messages without compromise application performance while increases the overall network lifetime. The main contributions of this article are a cluster-based control message dissemination for SDN-FANET operations, efficient and reliable control message dissemination, implementation, and evaluation of CAPONE in a network simulator to assess network performance metrics in terms of PDR, position prediction error, overhead, and remaining energy.
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