Energy Efficiency of Coding Schemes for Underwater Wireless Sensor Networks

Energy Efficiency of Coding Schemes for Underwater Wireless Sensor Networks

Mark S. Leeson (University of Warwick, UK) and Sahil Patel (University of Warwick, UK)
Copyright: © 2015 |Pages: 29
DOI: 10.4018/978-1-4666-8251-1.ch002
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Underwater Wireless Sensor Networks (UWSNs) are used in applications such as mineral exploration and environmental monitoring, and must offer reliability and energy efficiency. These are related to each other in the sense that the former requires error-correction which in turn requires energy, consuming battery life in an environment where battery replacement and recharging are difficult. This chapter thus addresses the energy efficiency of three suitable error correction methods for UWSNs, namely Automatic Repeat Request (ARQ), Forward Error Correction (FEC) and Network Coding (NC). The performance of the schemes as a function of transmission distance is determined for various packet sizes by using models of attenuation and noise that represent the underwater environment. ARQ offers the lowest efficiency and NC the highest but there is a distance at which FEC becomes the best option rather than NC suggesting a hybrid FEC/NC method.
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The majority of the earth’s surface is covered with water and underwater communication applications such as oceanographic data collection, pollution detection and offshore exploration require monitoring of the different parts of the ocean (Akyildiz et al., 2005). One common method for ocean monitoring is to use oceanographic sensors, record the information and then recover the instruments (Yick et al., 2008). However this method is not efficient because it creates long lags in the recorded data, and also if by chance any problem occurs while recovering the data, they all tend to get lost (Sozer et al., 2000). The best solution to this problem is to establish a network configuration which helps in the real-time communication between the underwater devices and a control center. Two way acoustic links are established between different underwater devices such as Autonomous Underwater Vehicles (AUVs) and sensors, thus giving rise to basic Underwater Acoustic (UWA) Networks (Sozer et al., 2000). Such networks are connected to a surface station which in turn is connected to the Internet through a radio frequency (RF) link. Using this network configuration, scientists can easily extract real-time data from a number of distant underwater devices. After examining the received data, control information is sent to individual instruments and the network adapts itself to the changing situations. Thus, significant data loss does not occur because the data are transferred as soon as they become available.

UWA network design involves major challenges such as limited available bandwidth, the nature of the underwater channel and limited battery power, making them prone to failure (Akyildiz et al., 2005; Heidemann et al., 2006). The most suitable option is underwater sensor networks (UWSNs) (Cui et al., 2006) consisting of a number of sensors and vehicles which interact with each other to carry out some collaborative tasks such as detection of the target and tactical surveillance. Wireless acoustic communications have to be established in these applications so that a considerable area can be monitored with a small number of nodes. Such communications coupled with appropriate networking protocols help to overcome the limitations of underwater channels to some extent (Cherkaoui et al., 2012) but UWSNs and their design challenges are different from terrestrial sensor networks (Partan et al., 2006). One major challenge that is considered in this project is the energy efficiency in the underwater acoustic channels. The wide variety of applications of UWA communications in UWSNs and multi-AUV cooperative missions (Akyildiz et al., 2004; Akyildiz et al., 2005) ranging from simple monitoring and data collection to exploration, deployment and rescue work, highlight the significance of UWA networks. However, there has historically been little progress in developing networking topologies for the underwater acoustic medium (Harris and Zorzi, 2007). Although wireless connectivity can be achieved underwater, when using the acoustic medium for inter-device networking, the acoustic channel differs greatly from the RF channel (Stojanovic, 2006). In the underwater environment, bandwidth varies from a few kHz in a long range (typically 1000 km) system to hundreds of kHz in short-range (less than 100m) systems (Akyildiz et al., 2004). We will now briefly summarize the factors which characterize underwater acoustic propagation, indicating which ones are not included in our analysis and why. Factors that make major contributions to the transmission performance of the systems considered in this chapter are analyzed in greater depth within subsequent sections.

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