KATO uses a knowledge-guided attention-style encoder to select roadside units and an iterative algorithm to allocate tasks, achieving near-optimal offloading times at low computational cost in simulations.
Vehicular edge computing and networking: A survey,
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Knowledge-Guided Attention-Inspired Learning for Task Offloading in Vehicle Edge Computing
KATO uses a knowledge-guided attention-style encoder to select roadside units and an iterative algorithm to allocate tasks, achieving near-optimal offloading times at low computational cost in simulations.