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To solve the overload problem of edge servers, the virtualization technology can be applied to integrate idle vehicles on the roadside and mobile vehicles into a resource pool to provide elastic services for delay-sensitive tasks. Therefore, a communication system model of packet transmission is established. In order to reduce the probability of channel collision in the binary exponential backoff algorithm (BEB), the minimum competition window is adjusted according to the number of vehicle nodes in the network. Considered the characteristics of timing decision of resource allocation, a computational offloading strategy is proposed for vehicle edge computing (VEC) system based on the improved semi-Markov decision process(SMDP). When formulating the optimal strategy of system action, nonlinear weight factor with cosine term is introduced to dynamically weight immediate reward and future expected reward. An iterative algorithm based on Bellman equation is utilized to approach the maximum long-term reward. Simulation results show that the proposed strategy can effectively reduce offloading delay, optimize throughput, and significantly improve the long-term rewards of the system.