Throughput of Hybrid UAV Networks With Scale-Free Topology

Abstract

Unmanned Aerial Vehicles (UAVs) hold great potential to support a wide range of applications due to the high maneuverability and flexibility. Compared with single UAV, UAV swarm carries out tasks efficiently in harsh environment, where the network resilience is of vital importance to UAV swarm. The network topology has a fundamental impact on the resilience of UAV network. It is discovered that scale-free network topology, as a topology that exists widely in nature, has the ability to enhance the network resilience. Besides, increasing network throughput can enhance the efficiency of information interaction, improving the network resilience. Facing these facts, this paper studies the throughput of UAV Network with scale-free topology. Introducing the hybrid network structure combining both ad hoc transmission mode and cellular transmission mode into UAV Network, the throughput of UAV Network is improved compared with that of pure ad hoc UAV network. Furthermore, this work also investigates the optimal setting of the hop threshold for the selection of ad hoc or cellular transmission mode. It is discovered that the optimal hop threshold is related with the number of UAVs and the parameters of scale-free topology. This paper may motivate the application of hybrid network structure into UAV Network.

A Co-Adaptation Method for Resilience Rebound in Unmanned Aerial Vehicle Swarms in Surveillance Missions

“…In other words, under the co-adaptation model, a resilient swarm can be achieved. Secondly, we use Equation (10) to calculate the resilience value with Tran's method, and our proposed method for each individual disruption-recovery event across various quantities of communication links. The comparison results are shown in Figure 13.…”

“…Additionally, Xu [9] identified node movement as a key factor impacting network performance and developed a novel model for information exchange networks in unmanned swarm systems. Furthermore, Bai et al [10] investigated the topology characteristics of UAV swarms, taking into consideration the influence of limited communication range, and proposed an improved UAV swarm model. They also presented an effective method to mitigate the adverse effects of unforeseen threats and disruptive events through topology self-adaptation in UAV swarms.…”

“…Tran defined the total received information in an information exchange network at any given time as the system performance [2]. Based on Tran's work, Bai et al [10] proposed an improved resilience metric, where the standard performance of the swarm was calculated using different methods. The operation loop was described as the working process of an unmanned weapon, representing a specific instance of the primary operation loop.…”

“…Li expanded on the generalized baseline function of information exchange capacity in communication networks, and also considered the heterogeneous communication network topology of UAV swarms. Compared with Tran [2] and Bai [10,23] incorporated functional factors into the exchange capacity model for network information. The majority of studies on surveillance missions predominantly concentrate on achieving optimal coverage area [24,25], the recognition and tracking of multiple targets [26], and the effective distribution of UAVs in a surveillance area [27].…”