A context-aware timeliness metric multiplies estimation error by a context weight, and a Lyapunov scheduling policy that minimizes it cuts threshold violations and improves CartPole control versus Age-of-Information scheduling.
Age of Information in G/G/1/1 Systems
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abstract
We consider a single server communication setting where the interarrival times of data updates at the source node and the service times to the destination node are arbitrarily distributed. We consider two service discipline models. If a new update arrives when the service is busy, it is dropped in the first model; and it preempts the current update in the second model. For both models, we derive exact expressions for the age of information metric with no restriction on the distributions of interarrival and service times. In addition, we derive upper bounds that are easier to calculate than the exact expressions. In the case with dropping, we also derive a second upper bound by utilizing stochastic ordering if the interarrival times have decreasing mean residual life (DMRL) and service times have new better than use in expectation (NBUE) property.
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cs.IT 1years
2019 1verdicts
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Context-Aware Information Lapse for Timely Status Updates in Remote Control Systems
A context-aware timeliness metric multiplies estimation error by a context weight, and a Lyapunov scheduling policy that minimizes it cuts threshold violations and improves CartPole control versus Age-of-Information scheduling.