A Q-learning-based approach in clock synchronisation in wireless sensor networks

In this paper, clock synchronisation in wireless sensor networks through Q-learning-based approach is investigated. This paper proposes a distributed approach that leverages distributed Q-learning-based synchronisation (DQS) to optimise packet transmission decisions for enhancing clock synchronisation. The proposed DQS method dynamically adjusts transmission behaviours based on historical experiences, aiming to minimise packet loss and energy consumption while synchronising clocks among sensor nodes. In particular, DQS approach presents a more efficient communication path with only fewer updates and transmission which result in less energy consumption for enhancing clock variance. The experimental result reveals that the proposed DQS approach has 3% to 7% reduction in energy consumption when compared to traditional distributed synchronisation (TDS) and gradient time synchronisation (GTS). Further, the packet loss and logical clock variance are reduced to 31% and 33% comparing with TDS and GTS with 500 rounds of synchronisation.