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Task offloading is one of the important research directions in Internet of Vehicles. Mobile edge computing and 5G heterogeneous network frameworks bring new opportunities for task offloading research. Most research works propose resource scheduling schemes and offloading strategies for task offloading within the same period. However, the allocation of resources for offloading tasks at different periods cannot be planned uniformly. The utilization and release of resources in previous periods affect the scheduling of resource allocations in later periods. To address the task offloading problem at different periods, this paper proposes the MPTO-MT algorithm. Specifically, the algorithm first determines whether the task can be offloaded in time at a certain period according to the number of candidate offloading nodes of the task in this period. Secondly, the algorithm selects the offloading node and the task transmission method. In order to select the appropriate offloading node and transmission method, we introduce the service utility and propose three heuristics of selecting the offloading node. Finally, the algorithm updates the resource information of nodes at the next period based on the utilization and release of node resources at the period, and the service time of the nodes. Comparative experiments with other baseline algorithms show that the proposed MPTO-MT algorithm improves the task completion rate by 4.55%, the timely rate of task completion by 3.57%, and shorter average service time. [ABSTRACT FROM AUTHOR]