## 1 Introduction  
A wireless sensor network (WSN) consists of a number of dedicated sensor nodes with sensing and computing capabilities, which can sense and monitor the physical parameters and transmit the collected data to a central location using wireless communication technologies. A WSN has a number of inherent characteristics including uncontrollable environments, topological constraints, and limited node resources for energy and computational power [1]. Generally, a WSN deploys more sensors than the optimal placement in order to improve the system reliability and the fault tolerance [2]. During the last decade, WSNs have been widely utilized in a variety of application fields related to water monitoring [3; 4; 5], forest monitoring [6; 7], industrial monitoring [8; 9], agriculture monitoring [10; 11], battlefield surveillance [12; 13], intelligent transportation [14; 15], smart homes [16; 17], animal behavior monitoring [18; 19], and disaster prevention [20; 21]. This technology can certainly be applied to the monitoring of marine environments. On the other hand, with the development of society and economy, more and more people have started to pay attention to the marine environment. Marine environment systems are particularly vulnerable to the effects of human activities related to industry, tourism and urban development [22]. Traditionally, oceanographic research vessels were used to monitor marine environments, which is a very expensive and time-consuming process that has a low resolution both in time and space. For marine environment research, a WSN-based approach can dramatically improve the access to real-time data covering long periods and large geographical areas [23]. According to [PERSON] _et al._[24], a WSN-based approach is at least one order of magnitude cheaper than a conventional oceanographic research vessel. In a WSN-based marine environment monitoring system, various kinds of sensors are used to monitor and measure different physical and chemical parameters such as water temperature, pressure, wind direction, wind speed, salinity, turbidity, pH, oxygen density, and chlorophyll levels. While the development and deployment of an adaptive, scalable and self-healing WSN system need to address a number of critical challenges such as autonomy, scalability, adaptability, self-healing and simplicity [25; 26], the design and deployment of a lasting and scalable WSN for marine environment monitoring should take into account the following challenges different from those on land [22]:  
1. _Higher water resistance:_ Sensor nodes of a marine monitoring system require greater levels of water resistance;
2. _Stronger robustness:_ A marine monitoring system needs stronger robustness, since the marine environment with waves, marine currents, tides, typhoons, vessels, _etc._, is aggressive and complex, and causes movement of nodes;
3. _Higher energy consumption:_ Energy consumption is higher due to long communication distances and an environment in constant motion;(4) _More unstable line-of-sight_: The oscillation of the radio antenna can cause a more unstable line-of-sight between transmitters and receivers [27]. (5) _Other problems:_ There are also some other problems including the difficulty for deployment and maintenance of nodes, the need for buoy and mooring devices, sensor coverage problems [2], and possible acts of vandalism. There have been a few literature reviews on Wireless Sensor Networks for marine environment monitoring. [PERSON] _et al_. [22] provided a comprehensive review of the research and development of oceanographic monitoring using wireless sensor networks and pointed out the challenges and difficulties of WSNs for oceanographic monitoring. This paper is intended as an update and extension of [PERSON] _et al_'s review [22] based on recent developments in this area during the past five years. The limitations and challenges of wireless sensor networks for environmental research were discussed in [28].