Research Article Localization Algorithms in Large-Scale Underwater Acoustic Sensor Networks: A Quantitative Comparison Guangjie Han, 1,2,3 Aihua Qian, 3 Chenyu Zhang, 3 Yan Wang, 4 and Joel J. P. C. Rodrigues 5 1 Nantong Ocean and Coastal Engineering Research Institute, Hohai University, Nantong 226000, China 2 Changzhou Key Laboratory of Photovoltaic System Integration and Production Equipment Technology, Changzhou 213022, China 3 Department of Information and Communication Systems, Hohai University, Changzhou 213022, China 4 School of Computer & Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China 5 Instituto de Telecomunicac ¸˜ oes, University of Beira Interior, 6201-001 Covilh˜ a, Portugal Correspondence should be addressed to Guangjie Han; hanguangjie@gmail.com Received 30 November 2013; Accepted 25 January 2014; Published 5 March 2014 Academic Editor: Long Cheng Copyright © 2014 Guangjie Han et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Recently underwater acoustic sensor networks (UASNs) have drawn much attention because of their great value in many underwater applications where human operation is hard to carry out. In this paper, we introduce and compare the performance of four localization algorithms in UASNs, namely, distance vector-hop (DV-hop), a new localization algorithm for underwater acoustic sensor networks (NLA), large-scale hierarchical localization (LSHL), and localization scheme for large scale underwater networks (LSLS). he four algorithms are all suitable for large-scale UASNs. We compare the localization algorithms in terms of localization coverage, localization error, and average energy consumption. Besides, we analyze the impacts of the ranging error and the number of anchor nodes on the performance of the localization algorithms. Simulations show that LSHL and LSLS perform much better than DV-hop and NLA in localization coverage, localization error, and average energy consumption. he performance of NLA is similar to that of the DV-hop. he advantage of DV-hop and NLA is that the localization results do not rely on the number of anchor nodes; that is, only a small number of anchor nodes are needed for localization. 1. Introduction Oceans cover about 71% of the Earth’s surface, but most of them have not been explored up to now. Recently, there has been a growing interest in ocean exploration activities [1]. UASNs have been widely applied in many ields, such as naval defense, environmental pollution monitoring, earthquake or tsunami forewarning, and ocean life monitoring systems. Sensor nodes are deployed both underwater and on the water surface covering the entire monitored space to cooperatively fulill monitoring tasks. In all applications, localization is a fundamental and signiicant task in UASNs. Although localization in terrestrial wireless sensor net- works (TWSNs) has been well studied up to now, localization in UASNs is still a challenging problem due to the following reasons [2]: (i) unavailability of global positioning system (GPS); (ii) low bandwidth, long delay, and high bit error rate of underwater acoustic links; (iii) necessity of large number of sensor nodes to cover wide and deep oceanographic regions. What is more, some uncontrollable factors such as the mobility caused by water current and oceanographic animals bring a new set of challenges to localization in UASNs. Sensor nodes in the network can be classiied into two categories according to whether they know their positions, namely, anchor node (beacon node) and ordinary node (unknown node). Anchor nodes are those who can directly get their absolute positions from GPS or by other means. Ordinary nodes are those who can communicate with anchor nodes to estimate their own positions using localization algorithms. Recently many localization algorithms for WSNs and UASNs have been proposed [3–6]. he authors classify localization algorithms into two categories [7]: range-based algorithms and range-free algorithms. he former contains the protocols which calculate locations of unknown nodes by estimating absolute point-to-point distances or angles, Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2014, Article ID 379382, 11 pages http://dx.doi.org/10.1155/2014/379382