Dynamic Routing for Flying Ad Hoc Networks

Abstract

Abstract-This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes.In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance.Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.

Delay-Constrained Routing Based on Stochastic Model for Flying Ad Hoc Networks

“…For simplifying the transmission process, each relay node only has one chance to retransmit the packet on each link. We divide the experimental results into two parts: Figures 2-4 show the changing trends of network parameters when the di erent moving speeds and hello intervals are considered that only our proposed routing policy is followed, and the Figures 5-10 indicate the di erent network performances under two di erent routing policies which include the proposed method, OR-DSP [14], P-OLSR [15], and GRAA [19]. e reason for comparison with these three routing algorithms is the di erent path selection criteria for designing the routing algorithms.…”

“…Sugranes and Razi [14] proposed an optimal routing method based on Dijkstra's shortest path algorithm (OR-DSP) and prediction technique for UAV networks with queued communication systems by incorporating predicted network topology. Rosati et al [15] proposed predictive OLSR (P-OLSR) which is an OLSR extension designed for FANETs, to solve the challenging issues that the existing routing protocols designed for MANETs partly fail in tracking network topology changes. P-OLSR computes the relative speed between two nodes and takes the relative speed as a parameter of path metric to help each node making a wise routing decision.…”

File Transfer in FANET using Dijkstra Algorithm

“…The communication range, routing performance and the performance are evaluated through this experiment. P-OLSR is better than the OLSR in frequent topology changes [7]. …”

UAV Cloud Operating System

“…Unmanned Aerial Vehicle systems (UAV), fly autonomously and it can be thought as an aircraft without no pilot on the board, the UAV can be remote controlled from a ground control station or can fly autonomously based on a pre-programmed flight plans. Usage of UAVs promises new ways for both military and civilian applications, ranging from search and rescue operations to disaster monitoring [3]. FANET develops a group of small UAVs which form a special kind of ad hoc networks Architecture.…”