Abstract

The recent advances in unmanned aerial vehicles (UAVs) enormously improve their utility and expand their application scope. The UAV and swarm implementation further prevail in Smart City practices with the aid of edge computing and urban Internet of Things. The lead–follow formation in UAV swarm is an important organization means and has been adopted in diverse exercises, for its efficiency and ease of control. However, the reliability of centralization makes the entire swarm system in risk of collapse and instability, if a fatal fault incident happens in the leader. The motivation is to build a mechanism helping the distributed swarm recover from possible failures. Existing ways include assigning definite backups, temporary clustering and traversing to select a new leader are traditional ways that lack flexibility and adaptability. In this article, we propose a voting-based leader election scheme inspired by the Raft method in distributed computation consensus to solve the problem. We further discuss the impact of communication conditions imposed on the decentralized voting process by implementing a network resource pool. To dynamically evaluate UAV individuals, we outline measurement design principles and provide a realizable calculation example. Lastly but not least, empirical simulation results manifest better performance than the Raft-based method. Our voting-based approach exhibits advantages and is a promising way for quick regrouping and fault recovery in lead–follow swarms.

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