3D Transformative Routing for UAV Swarming Networks: A Skeleton-Guided, GPS-Free Approach
Lin Zhang, Fei Hu, Zhe Chu, Elizabeth Serena Bentley, Sunil Kumar
Abstract
A challenging issue for a three-dimensional (3D) unmanned aerial vehicle (UAV) network is addressed in this paper - how do we efficiently establish and maintain one or multiple routes among swarm regions (i.e., groups of UAVs), during the dynamic swarming process? Inspired by the human nervous system which can efficiently send brain signals to any tissue, we propose a 3D transformative routing (3D-TR) scheme, which consists of three novel designs: (1) Proactive routing skeleton establishment: 3D-TR first identifies the skeleton of the UAV network, which has a trunk-stem-stemlet (TSS) structure. The trunk is located in the relatively stable area of the network (i.e., the central area), and stems/stemlets reside in the outer areas with more swarming movements. Such a TSS skeleton enables the easy establishment of the path(s) with low end-to-end delay and a high packet delivery rate. (2) Reactive, transformative path selection: The 3D-TR scheme can smoothly adapt to the formation changes through dynamic TSS adjustments. (3) Bottleneck-aware route maintenance: We propose an efficient scheme to recognize the bottleneck nodes in each path and build the diversified routing pipes with different thickness/stability levels. The proposed routing scheme is distributed (only uses local message exchanges among 1-hop neighbors) and does not require the GPS (global positioning system) positions of the UAVs. Extensive simulations are conducted to validate the performance of the proposed 3D-TR scheme during the dynamic UAV swarming process.