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This article considers scheduling in tree data gathering networks. The worker nodes of a network acquire datasets of known sizes at possibly different times. The datasets are sent to intermediate nodes which process them and then pass the results to the base station. Each dataset is assigned a due date by which it should arrive at the base station. The scheduling problem is to minimize the maximum dataset lateness. It is proved that this problem is strongly NP-hard, and heuristic algorithms based on priority rules are proposed. The algorithms are tested in a series of computational experiments, for a wide range of changing network parameters. The results show that, although most algorithms perform well only for certain instances, one of the proposed priority rules achieves very good results for all settings analysed.

A comparison of priority rules for minimizing the maximum lateness in tree data gathering networks