Title :
Energy-constrained bi-objective data muling in underwater wireless sensor networks
Author :
Li, Ke ; Shen, Chien-Chung ; Chen, Guaning
Author_Institution :
Comput. & Inf. Sci., Univ. of Delaware, Delaware, OH, USA
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..
Keywords :
Pareto optimisation; computational complexity; energy consumption; underwater acoustic communication; wireless sensor networks; NP-hard problem; Pareto-efficient solutions; data mule collecting sensor data; energy consumption; energy-constrained bi-objective optimization problem; mobile data mule; tour planning; underwater data muling problem; underwater wireless sensor networks; wireless communication; Approximation algorithms; Batteries; Energy consumption; Planning; Robot sensing systems; Wireless communication; Wireless sensor networks; data muling; heuristic algorithm; tour planning; underwater wireless sensor networks;
Conference_Titel :
Mobile Adhoc and Sensor Systems (MASS), 2010 IEEE 7th International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4244-7488-2
DOI :
10.1109/MASS.2010.5664026