Abstract-For underwater wireless sensor networks (UWSNs), data muling is an effective approach to data gathering, where sensor data are collected when a mobile data mule travels within the wireless communication range of the sensors. However, given the constrained energy available on a data mule and the energy consumption of its motions and communications a data mule may be prevented from visiting every deployed sensor in a tour. We formulate the tour planning of a data mule collecting sensor data in UWSNs as an energy-constrained bi-objective optimization problem termed the Underwater Data Muling Problem (UDMP). UDMP has the two conflicting objectives of maximizing the number of sensors contacted and minimizing the length of a tour, while satisfying the energy constraint on the data mule at all times. We design two heuristic algorithms to solve one special case and one generalized case of this NP-hard problem, respectively. Each algorithm computes a set of Pareto-efficient solutions addressing the tradeoff between the two optimization objectives to facilitate tour planning. Simulation results validate the effectiveness of both algorithms.

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