Abstract
In the unmanned aerial vehicle (UAV) swarm combat system, multiple UAVs’ collaborative operations can solve the bottleneck of the limited capability of a single UAV when they carry out complicated missions in complex combat scenarios. As one of the critical technologies of UAV collaborative operation, the mobility model is the basic infrastructure that plays an important role for UAV networking, routing, and task scheduling, especially in high dynamic and real-time scenarios. Focused on real-time guarantee and complex mission cooperative execution, a multilevel reference node mobility model based on the reference node strategy, namely, the ML-RNGM model, is proposed. In this model, the task decomposition and task correlation of UAV cluster execution are realized by using the multilayer task scheduling model. Based on the gravity model of spatial interaction and the correlation between tasks, the reference node selection algorithm is proposed to select the appropriate reference node in the process of node movement. This model can improve the real-time performance of individual tasks and the overall mission group carried out by UAVs. Meanwhile, this model can enhance the connectivity between UAVs when they are performing the same mission group. Finally, OMNeT++ is used to simulate the ML-RNGM model with three experiments, including the different number of nodes and clusters. Within the three experiments, the ML-RNGM model is compared with the random class mobility model, the reference class mobility model, and the associated class mobility model for the network connectivity rate, the average end-to-end delay, and the overhead caused by algorithms. The experimental results show that the ML-RNGM model achieves an obvious improvement in network connectivity and real-time performance for missions and tasks.
Highlights
Over the last decade, the usage of unmanned aerial vehicle (UAV) has been strictly increasing in the area like agriculture, construction, industry, and defense
High concentration reduces the time overhead brought by information exchange between the associated UAVs and effectively guarantees the makespan of the subsequent mission groups assigned to the considered UAV cluster
A new group mobility model is proposed for the UAV swarm, namely, the multilevel reference node group mobility (ML-RNGM) model
Summary
The usage of UAVs has been strictly increasing in the area like agriculture, construction, industry, and defense. Several UAVs are considered to perform a complicated mission cooperatively as they can handle practical tasks with complexity, diversity, and relevance, such as close air support, reconnaissance, air defense, and coordinated attack. UAV warm is a complex system, which involves many aspects, such as task allocation, path planning, effectiveness evaluation, and networking protocol. Among the above aspects, networking plays the most important role for UAV mission execution [1] and usually constructs a hierarchical cluster network. Wang et al [5] proposed a multilayer task scheduling model for layered and clustered UAV swarms. Their research mainly focused on the cooperative task processing and International Journal of Aerospace Engineering resource scheduling for the UAV group but did not consider the group mobility model which has an obvious influence on UAV mission execution
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