Novel Drift-Based Design and Analysis for Synchronized and Fresh Communication over Broadcast Channels

Synchronized and fresh communication of common information is vitally important in numerous multi-user network scenarios, whereby end-users must perform coordinated real-time action with the available information. However, developing efficient policies with performance guarantees is greatly complicated by the abruptly changing nature of related age and synchronization metrics. In particular, powerful approaches that are based on so-called drift- plus- penalty (D PP) methods could not be employed due to the non-traditional multiplicative update dynamics of age and synchronization. In this paper, we overcome these limitations by designing and analyzing a Lyapunov-drift-based algorithm under the non-traditional age and synchronization dynamics that is not only low-complexity and analyzable, but also performs better than all the prior designs in numerical investigations. By comparing our design with two alternatives using the DPP approach, we also shed some light on the key aspect of our design that enables the performance analysis, which may be useful in future studies in multiplicative update dynamics. Moreover, our design reveals that a previously unconsidered feature of ‘maximum age’ also contains key information that governs a good policy. As such, our design naturally supplies a new critical feature that can be integrated into future reinforcement-learning-based designs.