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In this work, we study the freshness and significance of information in an IoT status update system where an Energy Harvesting (EH) device samples an information source and forwards the update packets to a destination node through a direct channel. We introduce and optimize a semantics-aware metric, Query Version Age of Information (QVAoI), in the system along with other semantic metrics: Query Age of Information (QAoI), Version Age of Information (VAoI), and Age of Information (AoI). By employing the MDP framework, we formulate the optimization problem and determine the optimal transmission policies at the device, which involve deciding the time slots for updating, subject to the energy limitations imposed by the device's battery and energy arrivals. Through analytical and numerical results, we compare the performance of the semantics-aware QVAoI-Optimal, QAoI-Optimal, VoI-Optimal, and AoI-Optimal policies with a baseline greedy policy. All semantics-aware policies show significantly improved performance compared to the greedy policy. The QVAoI-Optimal policy, in particular, demonstrates a significant performance improvement by either providing fresher, more relevant, and valuable updates with the same amount of energy arrivals or reducing the number of transmissions in the system to maintain the same level of freshness and significance of information compared to the QAoI-Optimal and other policies.
Delfani et al. (Thu,) studied this question.
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