## 1 Introduction  
A wireless sensor network (WSN) is a wireless network of spatially distributed autonomous devices (sensor nodes) using sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations. [1-3] Each sensor node in a sensor network has functions to sense physical or environmental conditions, to process sensed data, and to send or receive the sampled data or processed results. Sometimes, a sensor node might be equipped with actuators to control itself or the environment. Recently, applications of wireless sensor networks to underwater environments arose as a promising division of research among scientists due to the systems' various application possibilities [4-6]. Underwater sensor networks are designed for applications like pollution monitoring, disaster prevention, strategic surveillance, oceanographic data collection and offshore exploration. Unmanned vehicles with several underwater sensors can also be utilized for underwater resource investigation and collaborative underwater data gathering monitoring tasks [4]. Acoustic arrays and sensors can also be deployed for underwater ecosystem monitoring, in which transceivers can detect and track the number, health and location of aquatic creatures [7,8]. One important challenge with underwater sensor networks is enabling underwater communications. Wireless sensor network communication on land is conducted mostly through radio frequency (RF) wave propagation, taking advantage of its speed, long range and reasonable energy expenditure [9]. For underwater communications, however, RF waves are inappropriate due to several reasons such as high dissemination rate, immense propagation power [10,11], and high exposure to communication interference due to low and restricted transmission bandwidth [12,13]. Therefore, efforts have been undertaken to apply acoustic waves as a means for underwater sensor network communication [12,14]. Underwater acoustic wireless sensor networks, however, still display severe flaws that hinder their utilization for comprehensive and exhaustive communication tasks. First, acoustic waves are much slower than RF waves and can travel at only 1.5 km/s, so real-time data transmission and time synchronization are very difficult [4]. Also, pulsing an acoustic signal underwater requires more transmission power than for terrestrial RF signals [4]. Lastly, due to the high bit error rate, a greater amount of data transmission incurs a proportionally large amount of data failures [14]. Therefore, we face an urgent need to reduce the amount and frequency of data transmissions, especially in underwater circumstances. Some studies on data storage sought to reduce redundant data conveyance by allowing users to selectively acquire data by querying the network [15]. One of the two major approaches to data storage in sensor networks is the \"warehouse\" approach, in which all sensor data is collected into a large, central database from which users can acquire their data of interest [15]. Another approach is the distributed approach, in which each distributed devices such as sensor nodes can act like a database and users query each node for data [16]. The distributed approach effectively reduced the redundant network traffic caused by the warehousing system [17]. With recent enhancements in ubiquitous technologies, more smart devices (smart phones, smart dust, smart tabs _etc._) are expected to be utilized for real-time and user-friendly seismic monitoring, equipment monitoring and remote controlling, leak detection, and support for robot swarms through this approach [18]. However, such a query-based sensor network management strategy can only be effective when a few users are online.