A Distributed Scheduling Method for Networked UAV Swarm based on Computing for Communication

UAV swarms have attracted much attention for post-disaster search and rescue, pollution monitoring and trace-ability, etc. , where distributed scheduling is required to arrange careful tasks and time quickly. The market-based methods are widely favored but they rely on the environmentally influenced communication network to complete negotiation, while the on-board computing of UAV is robust and redundant. This paper proposes a distributed scheduling method for networked UAV swarm based on computing for communication, which trades a modest increase in computing for a significant decrease in communication. First, by analyzing the task removal strategies of two representative methods, the consensus-based bundle algorithm (CBBA) and performance impact (PI) algorithm, a new removal strategy is proposed, which expands the explo-ration of the bundle and can potentially reduce communication rounds. Second, the proposed task-related optimization method can extract task conflict nodes from the native communication protocol, and use the sampling and estimation strategies to resolve task conflicts in advance. Third, historical bids are cleverly used to infer others' locations, which is necessary for task-related optimization. Fourth, to verify the algorithm in real communication, a hardware-in-the-loop (HIL) ad-hoc network simulation system is constructed, which uses real network protocols and simulated channel transmissions. Finally, the HIL Monte Carlo simulation results show that, compared with CBBA and PI, the proposed method can significantly reduce the number of communication rounds and the total scheduling time, without increasing the communication protocol overhead and loss of optimization.

Authors

• Runfeng Chen
• Jie Li
• Yiting Chen
• Yuchong Huang

Keywords

• Protocols
• Pollution
• Monte Carlo methods
• Processor scheduling
• Optimization methods
• Autonomous aerial vehicles
• Prediction algorithms
• Unmanned Aerial Vehicles
• Unmanned Aerial Vehicle Swarm
• Communication Protocol
• Real Networks
• Pollution Monitoring
• Ad Hoc Networks
• Removal Strategies
• Real Communication
• Communication Rounds
• Task Conflict
• Performance Of Algorithm
• Scoring Function
• Travel Time
• Network State
• Path Loss
• Bit Error
• Packet Loss
• Rayleigh Fading
• Scheduling Algorithm
• Task Scheduling
• Speed Of The Unmanned Aerial Vehicles
• Virtual Nodes
• Market-based Approach
• Additional Protocol
• Transmission Control Protocol
• Time Division Multiple Access
• Unmanned Aerial Vehicles Communication
• Medium Access Control
• Connection Topology
• Communication Situations