Scheduling in a Data Gathering Network to Minimize Maximum Lateness

In this work, we study scheduling in a data gathering network comprising a set of workers and a single base station. The workers produce datasets that have to be sent to the base station for further processing. Each dataset can be released at a different moment, and is assigned a due date by which it should be processed. Our goal is to schedule dataset transfers and the base station computations so as to minimize the maximum dataset lateness. We prove that the analyzed problem is strongly NP-hard, and present several polynomially solvable special cases. An exact branch-and-bound algorithm and three greedy heuristics are proposed. The performance of the algorithms is tested in computational experiments.