A two-time-scale approximate MDP scheduler for vehicular task offloading combines deterministic average-trajectory pre-allocation with online value-function improvement, claiming a provable cost bound and large simulated gains.
Maximizing spatial– temporal coverage in mobile crowd-sensing based on public transports with predictable trajectory,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.SY 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A Dynamic Programming Framework for Vehicular Task Offloading with Successive Action Improvement
A two-time-scale approximate MDP scheduler for vehicular task offloading combines deterministic average-trajectory pre-allocation with online value-function improvement, claiming a provable cost bound and large simulated gains.