Energy-constrained bi-objective data muling in underwater wireless sensor networks

Abstract

For underwater wireless sensor networks (UWSNs), data muling is an effective approach to extending network coverage and lifetime. Sensor data are collected when a mobile data mule travels within the wireless communication range of the sensor. Given the constrained energy available on a data mule and the energy consumption of its communications and movement operations, 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 minimizing the length of a tour and maximizing the number of sensors contacted, while satisfying the energy constraint of the data mule at all times. We design an approximation algorithm to solve one special case of this NP-hard problem, which computes a set of Pareto-efficient solutions addressing the tradeoff between the two optimization objectives so as to make proper tour planning. Simulation results validate the effectiveness of this algorithm..