Minimizing Age-upon-Decisions in Bufferless System: Service Scheduling and Decision Interval
Shutong Chen, Tianci Zhang, Zhengchuan Chen, Yunquan Dong, Min Wang,, Yunjian Jia, Tony Q. S. Quek

TL;DR
This paper analyzes the timeliness of decision-making in bufferless IoT systems, showing how service time and decision intervals affect age-upon-decisions and missing probabilities, with theoretical and simulation validation.
Contribution
It provides a comprehensive analysis of age-upon-decisions and missing probabilities in bufferless queue systems with various service and decision interval models, including new theoretical insights.
Findings
Deterministic service time yields lower average AuD and missing probability than exponential or uniform.
Periodical decision systems have larger AuD but smaller missing probability than Poisson decision systems.
Bufferless systems outperform systems with infinite buffers in decision timeliness and usefulness.
Abstract
In Internet of Things (IoT), the decision timeliness of time-sensitive applications is jointly affected by the statistics of update process and decision process. This work considers an update-and-decision system with a Poisson-arrival bufferless queue, where updates are delivered and processed for making decisions with exponential or periodic intervals. We use age-upon-decisions (AuD) to characterize timeliness of updates at decision moments, and the missing probability to specify whether updates are useful for decision-making. Our theoretical analyses 1) present the average AuDs and the missing probabilities for bufferless systems with exponential or deterministic decision intervals under different service time distributions; 2) show that for service scheduling, the deterministic service time achieves a lower average AuD and a smaller missing probability than the uniformly distributed…
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Taxonomy
TopicsAge of Information Optimization · Context-Aware Activity Recognition Systems · Distributed systems and fault tolerance
