Version Innovation Age and Age of Incorrect Version for Monitoring Markovian Sources
CoRR(2024)
摘要
In this paper, we propose two new performance metrics, coined the Version
Innovation Age (VIA) and the Age of Incorrect Version (AoIV) for real-time
monitoring of a two-state Markov process over an unreliable channel. We analyze
their performance under the change-aware, semantics-aware, and randomized
stationary sampling and transmission policies. We derive closed-form
expressions for the distribution and the average of VIA, AoIV, and AoII for
these policies. We then formulate and solve an optimization problem to minimize
the average VIA, subject to constraints on the time-averaged sampling cost and
time-averaged reconstruction error. Finally, we compare the performance of
various sampling and transmission policies and identify the conditions under
which each policy outperforms the others in optimizing the proposed metrics.
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