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Many online platforms are providing valuable real-time contents (e.g.,traffic) by continuously acquiring the status of different Points of Interest(PoIs). In status acquisition, it is challenging to determine how frequently aPoI should upload its status to a platform, since they are self-interested withprivate and possibly time-varying preferences. This paper considers a generalmulti-period status acquisition system, aiming to maximize the aggregate socialwelfare and ensure the platform freshness. The freshness is measured by ametric termed age of information. For this goal, we devise a long-termdecomposition (LtD) mechanism to resolve the time-varying informationasymmetry. The key idea is to construct a virtual social welfare that onlydepends on the current private information, and then decompose the per-periodoperation into multiple distributed bidding problems for the PoIs andplatforms. The LtD mechanism enables the platforms to achieve a tunabletrade-off between payoff maximization and freshness conditions. Moreover, theLtD mechanism retains the same social performance compared to the benchmarkwith symmetric information and asymptotically ensures the platform freshnessconditions. Numerical results based on real-world data show that when theplatforms pay more attention to payoff maximization, each PoI still obtains anon-negative payoff in the long-term.

Taming Time-Varying Information Asymmetry in Fresh Status Acquisition