Research Article
Time-Driven Scheduling Based on Reinforcement Learning for Reasoning Tasks in Vehicle Edge Computing
Table 1
Notations and descriptions.
| Notation | Description |
| , , | A reasoning task, a set of subtasks, and the data dependencies between subtasks | | Computational scheduling plan for tasks | , , | Task size, computation intensity, tolerable delay of subtask | , | Computation latency in vehicle and RSU | , | Local computing capacity and scheduling capacity | | Transmission latency of subtasks | | Completion latency of a reasoning task | , , | State, action, and reward of an MDP at time step t | , | Parametrized policy and value function for computation scheduling |
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