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A data mule represents a mobile device that collects data in a sensor field by physically visiting the nodes in a sensor network. The data mule collects data when it is in the proximity of a sensor node. This can be an alternative to multihop forwarding of data when we can utilize node mobility in a sensor network. To be useful, a data mule approach needs to minimize data delivery latency. In this paper, we first formulate the problem of minimizing the latency in the data mule approach. The data mule scheduling (DMS) problem is a scheduling problem that has both location and time constraints. Then, for the 1D case of the DMS problem, we design an efficient heuristic algorithm that incorporates constraints on the data mule motion dynamics. We provide lower bounds of solutions to evaluate the quality of heuristic solutions. Through numerical experiments, we show that the heuristic algorithm runs fast and yields good solutions that are within 10 percent of the optimal solutions.