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In Internet of Things (IoT), the decision timeliness of time-sensitiveapplications is jointly affected by the statistics of update process anddecision process. This work considers an update-and-decision system with aPoisson-arrival bufferless queue, where updates are delivered and processed formaking decisions with exponential or periodic intervals. We useage-upon-decisions (AuD) to characterize timeliness of updates at decisionmoments, and the missing probability to specify whether updates are useful fordecision-making. Our theoretical analyses 1) present the average AuDs and themissing probabilities for bufferless systems with exponential or deterministicdecision intervals under different service time distributions; 2) show that forservice scheduling, the deterministic service time achieves a lower average AuDand a smaller missing probability than the uniformly distributed and thenegative exponentially distributed service time; 3) prove that the average AuDof periodical decision system is larger than and will eventually drop to thatof Poisson decision system along with the increase of decision rate; however,the missing probability in periodical decision system is smaller than that ofPoisson decision system. The numerical results and simulations verify thecorrectness of our analyses, and demonstrate that the bufferless systemsoutperform the systems applying infinite buffer length.

Minimizing Age-upon-Decisions in Bufferless System: Service Scheduling and Decision Interval