Underwater Acoustic Sensor Network (UASN)

Underwater Acoustic Sensor Network (UASN) CHAPTER1: Introduction Most of the earth surface is composed of water including fresh water from river, lakes etc and salt water from the sea. There are still many un-explored areas for such places. This needs significant research efforts and good communication systems. Wireless sensor network in aqueous medium has the ability to explore the underwater environment in details. For all applications of underwater, a good communication system as well as an effective routing protocol is needed. This will enable the underwater devices to communicate precisely. Underwater propagation speed varies with temperature, salinity and depth. By varying the underwater propagation speed at different depth, two scenarios can be achieved accurately namely: shallow and deep water. Shallow water consists of depth less than 200m and cylinder spreading. Deep water consists of depth greater or equal to 200 m and spherical spreading. In both shallow and deep water, different ambient noise and different spreading factor is applied. CHAPTER 2: Study of Underwater Acoustic Sensor Network (UASN) Application of UASN Wireless sensor network in aqueous medium also known as underwater sensor network has enabled a broad range of applications including: Environmental Monitoring Underwater sensor network can be used to monitor pollution like chemical, biological such as tracking of fish or micro-organisms, nuclear and oil leakage pollutions in bays, lakes or rivers [1]. Underwater sensor network can also be used to improve weather forecast, detect climate change, predict the effect of human activities on marine ecosystems, ocean currents and temperature change e.g. the global warming effect to ocean. Under Ocean Exploration Exploring minerals, oilfields or reservoir, determine routes for laying undersea cables and exploration valuable minerals can be done with such underwater sensor network. Disaster Prevention Sensor network that measure seismic activity from remote locations can provide tsunami warning to coastal areas, or study the effects of submarine earthquakes (seaquakes) [2] Equipment Monitoring Long-term equipment monitoring may be done with pre-installed infrastructure. Short-term equipment monitoring shares many requirements of long-term seismic monitoring, including the need for wireless (acoustic) communication, automatic configuration into a multihop network, localization (and hence time synchronization), and energy efficient operation Mine Reconnaissance By using acoustic sensors and optical sensors together, mine detection can be accomplished quickly and effectively. Assisted Monitoring Sensor can be used to discover danger on the seabed, locate dangerous rocks or shoals in shallow waters, mooring position, submerged wrecks and to perform bathymetry profiling. Information collection The main goal of communication network is the exchange of information inside the network and outside the network via a gateway or switch center. This application is used to share information among nodes and autonomous underwater vehicles. Characteristic of UASN Underwater Acoustic Networks (UANs), including but not limited to, Underwater Acoustic Sensor Networks (UASNs) and Autonomous Underwater Vehicle Networks (AUVNs) , are defined as networks composed of more than two nodes, using acoustic signals to communicate, for the purpose of underwater applications. UASNs and AUVNs are two important kinds of UANs. The former is composed of many sensor nodes, mostly for a monitoring purpose. The nodes are usually without or with limited capacity to move. The latter is composed of autonomous or unmanned vehicles with high mobility, deployed for applications that need mobility, e.g., exploration. An UAN can be an UASN, or an AUVN, or a combination of both. Acoustic communications, on the other hands, is defined as communication methods from one point to another by using acoustic signals. Network structure is not formed in acoustic point-to-point communications. Sound travels best through the water in comparison with electromagnetic waves and optical signals. Acoustic signal is sound signal waveform, usually produced by sonar for underwater applications. Acoustic signal processing extracts information from acoustic signals in the presence of noise and uncertainty. Underwater acoustic communications are mainly influenced by path loss, noise, multi-path, Doppler spread, and high and variable propagation delay. All these factors determine the temporal and spatial variability of the acoustic channel, and make the available bandwidth of the Underwater Acoustic channel (UW-A) limited and dramatically dependent on both range and frequency. Long-range systems that operate over several tens of kilometers may have a bandwidth of only a few kHz, while a short-range system operating over several tens of meters may have more than a hundred kHz bandwidth. These factors lead to low bit rate. Underwater acoustic communication links can be classified according to their range as very long, long, medium, short, and very short links. Acoustic links are also roughly classified as vertical and horizontal, according to the direction of the sound ray. Their propagation characteristics differ consistently, especially with respect to time dispersion, multi-path spreads, and delay variance. Acoustic signal is the only physical feasible tool that works in underwater environment. Compared with it, electromagnetic wave can only travel in water with short distance due to the high attenuation and absorption effect in underwater environment. It is found that the absorption of electromagnetic energy in sea water is about 45Ãâ€" ?f dB per kilometer, where f is frequency in Hertz; In contrast, the absorption of acoustic signal over most frequencies of interest is about three orders of magnitude lower [40]. Hereafter the factors that influence acoustic communications is analyzed in order to state the challenges posed by the underwater channels for underwater sensor networking. These include: Path loss Attenuation is mainly provoked by absorption due to conversion of acoustic energy into heat, which increases with distance and frequency. It is also caused by scattering a reverberation (on rough ocean surface and bottom), refraction, and dispersion (due to the displacement of the reflection point caused by wind on the surface). Water depth plays a key role in determining the attenuation. Geometric Spreading is the spreading of sound energy as a result of the expansion of the wavefronts. It increases with the propagation distance and is independent of frequency. There are two common kinds of geometric spreading: spherical (omni-directional point source), and cylindrical (horizontal radiation only). Noise Man made noise is mainly caused by machinery noise (pumps, reduction gears, power plants, etc.), and shipping activity (hull fouling, animal life on hull, cavitations), especially in areas encumbered with heavy vessel traffic. Ambient Noise is related to hydrodynamics (movement of water including tides, current, storms, wind, rain, etc.), seismic and biological phenomena. Multi-path Multi-path propagation may be responsible for severe degradation of the acoustic communication signal, since it generates Inter-Symbol Interference (ISI). The multi-path geometry depends on the link configuration. Vertical channels are characterized by little time dispersion, whereas horizontal channels may have extremely long multi-path spreads. The extent of the spreading is a strong function of depth and the distance between transmitter and receiver. High delay and delay variance The propagation speed in the UW-A channel is five orders of magnitude lower than in the radio channel. This large propagation delay (0.67 s/km) can reduce the throughput of the system considerably. The very high delay variance is even more harmful for efficient protocol design, as it prevents from accurately estimating the round trip time (RTT), which is the key parameter for many common communication protocols. Doppler spread The Doppler frequency spread can be significant in UW-A channels, causing degradation in the performance of digital communications: transmissions at a high data rate because many adjacent symbols to interfere at the receiver, requiring sophisticated signal processing to deal with the generated ISI. The Doppler spreading generates: a simple frequency translation, which is relatively easy for a receiver to compensate for a continuous spreading of frequencies, which constitutes a non-shifted signal, which is more difficult for a receiver to compensate for. If a channel has a Doppler spread with bandwidth B and a signal has symbol duration T, then there are approximately BT uncorrelated samples of its complex envelope. When BT is much less than unity, the channel is said to be under spread and the effects of the Doppler fading can be ignored, while, if greater than unity, it is overspread. Most of the described factors are caused by the chemical-physical properties of the water medium such as temperature, salinity and density, and by their spatio-temporal variations. These variations, together with the wave guide nature of the channel, because the acoustic channel to be temporally and spatially variable. In particular, the horizontal channel is by far more rapidly varying than the vertical channel, in both deep and shallow water. CHAPTER 3: Network Architecture Underwater sensor nodes: The underwater sensor nodes are deployed on the sea floor anchored to the ocean bottom [32]. The sensors are equipped with floating buoys to push the nodes upwards, thus they are relatively stationary nodes [3]. Using acoustic links, they relay data to underwater sink directly or via multi-hop path. Underwater sink nodes: Underwater sink nodes take charge of collecting data of underwater sensors deployed on the ocean bottom and then send to the surface sink node. They may be equipped with vertical and horizontal acoustic transducers. The horizontal transceiver is used to collect the sensors data and the vertical transceiver provides transmitting link between underwater sink and the surface sink node. Surface sink node: Surface sink node is attached on a floating buoy with satellite, radio frequency (RF) or cell phone technology to transmit data to shore in real time. 2D Model A reference architecture for two-dimensional underwater networks is shown in Figure. 1. A group of sensor nodes are anchored to the deep of the ocean. Underwater sensor nodes are interconnected to one or more underwater gateways by means of wireless acoustic links. Underwater-gateways are network devices in charge of relaying data from the ocean bottom network to a surface station. To achieve this objective, they are equipped with two acoustic transceivers, namely a vertical and a horizontal transceiver. The horizontal transceiver is used by the underwater-gateway to communicate with the sensor nodes in order to: send commands and configuration data to the sensors (underwater -gateway to sensors); collect monitored data (sensors to underwater -gateway). The vertical link is used by the underwater -gateways to relay data to a surface station. In deep water applications, vertical transceivers must be long range transceivers. The surface station is equipped with an acoustic transceiver that is able to handle multiple parallel communications with the deployed underwater -gateways. It is also endowed with a long range RF and/or satellite transmitter to communicate with the onshore sink (os-sink) and/or to a surface sink (s-sink). In shallow water, bottom-deployed sensors/modems may directly communicate with the surface buoy, with no specialized bottom node (underwater -gateway). 3D Model Three-dimensional underwater networks are used to detect and observe phenomena that cannot be adequately observed by means of ocean bottom sensor nodes, i.e., to perform cooperative sampling of the 3D ocean environment. In three-dimensional underwater networks, sensor nodes float at different depths to observe a phenomenon. In this architecture, given in Figure 2, each sensor is anchored to the ocean bottom and equipped with a floating buoy that can be inflated by a pump. The buoy pushes the sensor towards the ocean surface. The depth of the sensor can then be regulated by adjusting the length of the wire that connects the sensor to the anchor, by means of an electronically controlled engine that resides on the sensor. Sensing and communication coverage in a 3D environment are rigorously investigated in [8]. The diameter, minimum and maximum degree of the reachability graph that describes the network are derived as a function of the communication range, while different degrees of cov erage for the 3D environment are characterized as a function of the sensing range. 3D Model with AUV The above figure represents the third type of network architecture which consist of sensor nodes and Autonomous Underwater Vehicles (AUV) which act as mobile sensor nodes for ocean monitoring, underwater resource study, etc. CHAPTER 4: Differences between underwater and terrestrial Sensor Network An underwater acoustic channel is different from a ground-based radio channel from many aspects, including: Bandwidth is extremely limited. The attenuation of acoustic signal increases with frequency and range [6] [10]. Consequently, the feasible band is extremely small. For example, a short range system operating over several tens of meters may have available bandwidth of a hundred kHz; a medium-range system operating over several kilometers has a bandwidth on the order of ten kHz; and a long-range system operating over several tens of kilometers is limited to only a few kHz of bandwidth [11]. Propagation delay is long. The transmission speed of acoustic signals in salty water is around 1500 meter/s [22], which is a difference of five orders of magnitude lower than the speed of electromagnetic wave in free space. Correspondently, propagation delay in an underwater channel becomes significant. This is one of the essential characteristics of underwater channels and has profound implications on localization and time synchronization. The channel impulse response is not only spatially varied but also temporarily varied. The channel characteristics vary with time and highly depend on the location of the transmitter and receiver. The fluctuation nature of the channel causes the received signals easily distorted. There are two types of propagation paths: macro-multipaths, which are the deterministic propagation paths; and micro-multipath, which is a random signal fluctuation. The macro-multipaths are caused by both reflection at the boundaries (bottom, surface and any object in the water) and bending. Inter- Symbol Interference (ISI) thus occurs. Compared with the spread of its ground-based counterpart, which is on the order of several symbol intervals, ISI spreading in an underwater acoustic channel is several tens or hundred of symbol intervals for moderate to high data rate in the horizontal channel. Micro-multipath fluctuations are mainly caused by surface wave, which contributes the most to the time variability of shallow water channel. In deep water, internal waves impact the single-path random fluctuations [12][13]. Probability of bit error is much higher and temporary loss of connectivity (shadow zone) sometimes occurs, due to the extreme characteristics of the channel. Cost. While terrestrial sensor nodes are expected to become increasingly inexpensive, underwater sensors are expensive devices. This is especially due to the more complex underwater transceivers and to the hardware protection needed in the extreme underwater environment. Also, because of the low economy of scale caused by a small relative number of suppliers, underwater sensors are characterized by high cost. Deployment. While terrestrial sensor networks are densely deployed, in underwater, the deployment is generally more sparse. Power. The power needed for acoustic underwater communications is higher than in terrestrial radio communications because of the different physical layer technology (acoustic vs. RF waves), the higher distances, and more complex signal processing techniques implemented at the receivers to compensate for the impairments of the channel. Memory. While terrestrial sensor nodes have very limited storage capacity, underwater-sensors may need to be able to do some data caching as the underwater channel may be intermittent. Spatial Correlation. While the readings from terrestrial sensors are often correlated, this is more unlikely to happen in underwater networks due to the higher distance among sensors. CHAPTER 5: Layered of UASN The underwater architecture network consists of five layers, application, transport, network, data link and physical layer as shown in the figure below. As typical underwater systems have limited processing capability, the protocol has been kept as simple as possible without significantly compromising performance. The underwater sensor network specifications currently do not include any recommendations for authentication and encryption. These may be easily implemented at the application layer or via a spreading scheme at the physical layer. Each layer is described by a SAPI. The SAPI is defined in terms of messages being passed to and from the layer. The clients (usually higher layers) of a layer invoke the layer via a request (REQ). The layer responds to each REQ by a response (RSP). Errors are reported via an ERR RSP with error codes. If the layer needs to send unsolicited messages to the client, it does so via a notification (NTF). A layer communicates logically with its peer layer via protocol data units (PDU). As the peer-to-peer communication is symmetric, a layer may send a REQ PDU to its peer layer at any time. It would optionally respond to such a PDU with a RSP PDU. This is logically depicted in Figure below It may be desirable in some cases, that non-neighboring layers communicate with each other to achieve cross-layer optimization. This may be implemented by allowing REQ and RSP PDUs between any two layers in the protocol stack. The underwater sensor network specifications define detailed message structures for all SAPI messages. These message structures include message identifiers, data formats to be used, parameters and their possible values Physical layer The physical layer provides framing, modulation and error correction capability (via FEC). It provides primitives for sending and receiving packets. It may also provide additional functionality such as parameter settings, parameter recommendation, carrier sensing, etc. At first underwater channel development was based on non-coherent frequency shift keying (FSK) modulation, since it relies on energy detection. Thus, it does not require phase tracking, which is a very difficult task mainly because of the Doppler-spread in the underwater acoustic channel. Although non-coherent modulation schemes are characterized by high power efficiency, their low bandwidth efficiency makes them unsuitable for high data rate multiuser networks. Hence, coherent modulation techniques have been developed for long-range, high-throughput systems. In the last years, fully coherent modulation techniques, such as phase shift keying (PSK) and quadrature amplitude modulation (QAM), have become practical due to the availability of powerful digital processing. Channel equalization techniques are exploited to leverage the effect of the inter-symbol interference (ISI), instead of trying to avoid or suppress it. Decision-feedback equalizers (DFEs) track the complex, relatively slowly varying channel response and thus provide high throughput when the channel is slowly varying. Conversely, when the channel varies faster, it is necessary to combine the DFE with a Phase Locked Loop (PLL) [9], which estimates and compensates for the phase offset in a rapid, stable manner. The use of decision feedback equalization and phase-locked loops is driven by the complexity and time variability of ocean channel impulse responses. Differential phase shift keying (DPSK) serves as an intermediate solution between incoherent and fully coherent systems in terms of bandwidth efficiency. DPSK encodes information relative to the previous symbol rather than to an arbitrary fixed reference in the signal phase and may be referred to as a partially coherent modulation. While this strategy substantially alleviates carrier phase-tracking requirements, the penalty is an increased error probability over PSK at an equivalent data rate. Another promising solution for underwater communications is the orthogonal frequency division multiplexing (OFDM) spread spectrum technique, which is particularly efficient when noise is spread over a large portion of the available bandwidth. OFDM is frequently referred to as multicarrier modulation because it transmits signals over multiple sub-carriers simultaneously. In particular, sub-carriers that experience higher SNR, are allotted with a higher number of bits, whereas less bits are allotted to sub-carriers experiencing attenuation, according to the concept of bit loading, which requires channel estimation. Since the symbol duration for each individual carrier increases, OFDM systems perform robustly in severe multi-path environments, and achieve a high spectral efficiency. Many of the techniques discussed above require underwater channel estimation, which can be achieved by means of probe packets [17]. An accurate estimate of the channel can be obtained with a high probing rate and/or with a large probe packet size, which however result in high overhead, and in the consequent drain of channel capacity and energy. Data link layer (MAC layer) The data link layer provides single hop data transmission capability; it will not be able to transmit a packet successfully if the destination node is not directly accessible from the source node. It may include some degree of reliability. It may also provide error detection capability (e.g. CRC check). In case of a shared medium, the data link layer must include the medium access control (MAC) sub-layer. Frequency division multiple access (FDMA) is not suitable for underwater sensor network due to the narrow bandwidth in underwater acoustic channels and the vulnerability of limited band systems to fading and multipath. Time division multiple access (TDMA) shows limited bandwidth efficiency because of the long time guards required in the underwater acoustic channel. In fact, long time guards must be designed to account for the large propagation delay and delay variance of the underwater channel in order to minimize packet collisions from adjacent time slots. Moreover, the variable delay makes it very challenging to realize a precise synchronization, with a common timing reference, which is required for TDMA. Carrier sense multiple access (CSMA) prevents collisions with the ongoing transmission at the transmitter side. To prevent collisions at the receiver side, however, it is necessary to add a guard time between transmissions dimensioned according to the maximum propagation delay in the network. This makes the protocol dramatically inefficient for underwater acoustic sensor network. The use of contention-based techniques that rely on handshaking mechanisms such as RTS/ CTS in shared medium access is impractical in underwater, for the following reasons: large delays in the propagation of RTS/CTS control packets lead to low throughput; due to the high propagation delay of underwater acoustic channels, when carrier sense is used, as in 802.11, it is more likely that the channel be sensed idle while a transmission is ongoing, since the signal may not have reached the receiver yet; the high variability of delay in handshaking packets makes it impractical to predict the start and finish time of the transmissions of other stations. Thus, collisions are highly likely to occur. Code division multiple access (CDMA) is quite robust to frequency selective fading caused by underwater multi-paths, since it distinguishes simultaneous signals transmitted by multiple devices by means of pseudo-noise codes that are used for spreading the user signal over the entire available band. CDMA allows reducing the number of packet retransmissions, which results in decreased battery consumption and increased network throughput. In conclusion, although the high delay spread which characterizes the horizontal link in underwater channels makes it difficult to maintain synchronization among the stations, especially when orthogonal code techniques are used [17], CDMA is a promising multiple access technique for underwater acoustic networks. This is particularly true in shallow water, where multi-paths and Doppler- spreading plays a key role in the communication performance. Network layer (Routing) The network layer is in charge of determining the path between a source (the sensor that samples a physical phenomenon) and a destination node (usually the surface station). In general, while many impairments of the underwater acoustic channel are adequately addressed at the physical and data link layers, some other characteristics, such as the extremely long propagation delays, are better addressed at the network layer. Basically, there are two methods of routing. The first one is virtual circuit routing and the second one is packet-switch routing. In virtual circuit routing, the networks use virtual circuits to decide on the path at the beginning of the network operation. Virtual-circuit-switch routing protocols can be a better choice for underwater acoustic networks. The reasons are: Underwater acoustic networks are typical asymmetric instead of symmetric. However, packet switched routing protocols are proposed for symmetric network architecture; Virtual-circuit-switch routing protocols work robust against link failure, which is critical in underwater environment; and Virtual-circuit-switch routing protocols have less signal overhead and low latency, which are needed for underwater acoustic channel environment. However, virtual-circuit-switch routing protocols usually lack of flexibility. In packet-switch routing, every node that is part of the transmission makes its own routing decision, i.e., decides its next hop to relay the packet. Packet-switch routing can be further classified into Proactive routing, Reactive and geographical routing protocols. Most routing protocols for ground-based wireless networks are packet-switch based. Proactive routing protocols attempt to minimize the message latency by maintaining up-to-date routing information at all times from each node to any other node. It broadcasts control packets that contain routing table information. Typical protocols include Destination Sequence Distance Vector (DSDV) [28] and Temporally Ordered Routing Algorithm (TORA). However, proactive routing protocols provoke a large signaling overhead to establish routes for the first time and each time the network topology changes. It may not be a good fit in underwater environment due to the high probability of link failure and extremely limited bandwidth there. Reactive routing protocols only initiate a route discovery process upon request. Correspondently, each node does not need to maintain a sizable look-up table for routing. This kind of routing protocols is more suitable for dynamic environment like ad hoc wireless networks. Typical protocol examples are Ad hoc On-demand Distance Vector (AODV) [23], and Dynamic Source Routing (DSR) [27]. The shortage of reactive routing protocols is its high latency to establish routing. Similar to its proactive counterpart, flooding of control packets to establish paths is needed, which brings significant signal overhead. The high latency could become much deteriorated in underwater environment because of the much slower propagation speed of acoustic signal compared with the radio wave in the air. Geographic routing (also called georouting or position-based routing) is a routing principle that relies on geographic position information. It is mainly proposed for wireless networks and based on the idea that the source sends a message to the geographic location of the destination instead of using the network address. Geographic routing requires that each node can determine its own location and that the source is aware of the location of the destination. With this information a message can be routed to the destination without knowledge of the network topology or a prior route discovery. Transport layer A transport layer protocol is needed in underwater sensor network not only to achieve reliable collective transport of event features, but also to perform flow control and congestion control. The primary objective is to save scarce sensor resources and increase the network efficiency. A reliable transport protocol should guarantee that the applications be able to correctly identify event features estimated by the sensor network. Congestion control is needed to prevent the network from being congested by excessive data with respect to the network capacity, while flow control is needed to avoid that network devices with limited memory are overwhelmed by data transmissions. Most existing TCP implementations are unsuited for the underwater environment, since the flow control functionality is based on a window- based mechanism that relies on an accurate esteem of the round trip time (RTT), which is twice the end-to-end delay from source to destination. Rate-based transport protocols seem also unsuited for this challenging environment. They still rely on feedback control messages sent back by the destination to dynamically adapt the transmission rate, i.e., to decrease the transmission rate when packet loss is experienced or to increase it otherwise. The high delay and delay variance can thus cause instability in the feedback control. Furthermore, due to the unreliability of the acoustic channel, it is necessary to distinguish between packet losses due to the high bit error rate of the acoustic channel, from those caused by packets being dropped from the queues of sensor nodes due to network congestion. In terrestrial, assume that congestion is the only cause for packet loss and the solution lies on decreasing the transmission rate, but in underwater sensor network if the packet loss is due to bad channel then the transmission rate should not be decreased to preserve throughput efficiency. Transport layer functionalities can be tightly integrated with data link layer functionalities in a cross-layer module. The purpose of such an integrated module is to make the information about the condition of the variable underwater channel available also at the transport layer. In fact, usually the state of the channel is known only at the physical and channel access sub-layers, while the design principle of layer separation makes this information transparent to the higher layers. This integration allows maximizing the Underwater Acoustic Sensor Network (UASN) Underwater Acoustic Sensor Network (UASN) CHAPTER1: Introduction Most of the earth surface is composed of water including fresh water from river, lakes etc and salt water from the sea. There are still many un-explored areas for such places. This needs significant research efforts and good communication systems. Wireless sensor network in aqueous medium has the ability to explore the underwater environment in details. For all applications of underwater, a good communication system as well as an effective routing protocol is needed. This will enable the underwater devices to communicate precisely. Underwater propagation speed varies with temperature, salinity and depth. By varying the underwater propagation speed at different depth, two scenarios can be achieved accurately namely: shallow and deep water. Shallow water consists of depth less than 200m and cylinder spreading. Deep water consists of depth greater or equal to 200 m and spherical spreading. In both shallow and deep water, different ambient noise and different spreading factor is applied. CHAPTER 2: Study of Underwater Acoustic Sensor Network (UASN) Application of UASN Wireless sensor network in aqueous medium also known as underwater sensor network has enabled a broad range of applications including: Environmental Monitoring Underwater sensor network can be used to monitor pollution like chemical, biological such as tracking of fish or micro-organisms, nuclear and oil leakage pollutions in bays, lakes or rivers [1]. Underwater sensor network can also be used to improve weather forecast, detect climate change, predict the effect of human activities on marine ecosystems, ocean currents and temperature change e.g. the global warming effect to ocean. Under Ocean Exploration Exploring minerals, oilfields or reservoir, determine routes for laying undersea cables and exploration valuable minerals can be done with such underwater sensor network. Disaster Prevention Sensor network that measure seismic activity from remote locations can provide tsunami warning to coastal areas, or study the effects of submarine earthquakes (seaquakes) [2] Equipment Monitoring Long-term equipment monitoring may be done with pre-installed infrastructure. Short-term equipment monitoring shares many requirements of long-term seismic monitoring, including the need for wireless (acoustic) communication, automatic configuration into a multihop network, localization (and hence time synchronization), and energy efficient operation Mine Reconnaissance By using acoustic sensors and optical sensors together, mine detection can be accomplished quickly and effectively. Assisted Monitoring Sensor can be used to discover danger on the seabed, locate dangerous rocks or shoals in shallow waters, mooring position, submerged wrecks and to perform bathymetry profiling. Information collection The main goal of communication network is the exchange of information inside the network and outside the network via a gateway or switch center. This application is used to share information among nodes and autonomous underwater vehicles. Characteristic of UASN Underwater Acoustic Networks (UANs), including but not limited to, Underwater Acoustic Sensor Networks (UASNs) and Autonomous Underwater Vehicle Networks (AUVNs) , are defined as networks composed of more than two nodes, using acoustic signals to communicate, for the purpose of underwater applications. UASNs and AUVNs are two important kinds of UANs. The former is composed of many sensor nodes, mostly for a monitoring purpose. The nodes are usually without or with limited capacity to move. The latter is composed of autonomous or unmanned vehicles with high mobility, deployed for applications that need mobility, e.g., exploration. An UAN can be an UASN, or an AUVN, or a combination of both. Acoustic communications, on the other hands, is defined as communication methods from one point to another by using acoustic signals. Network structure is not formed in acoustic point-to-point communications. Sound travels best through the water in comparison with electromagnetic waves and optical signals. Acoustic signal is sound signal waveform, usually produced by sonar for underwater applications. Acoustic signal processing extracts information from acoustic signals in the presence of noise and uncertainty. Underwater acoustic communications are mainly influenced by path loss, noise, multi-path, Doppler spread, and high and variable propagation delay. All these factors determine the temporal and spatial variability of the acoustic channel, and make the available bandwidth of the Underwater Acoustic channel (UW-A) limited and dramatically dependent on both range and frequency. Long-range systems that operate over several tens of kilometers may have a bandwidth of only a few kHz, while a short-range system operating over several tens of meters may have more than a hundred kHz bandwidth. These factors lead to low bit rate. Underwater acoustic communication links can be classified according to their range as very long, long, medium, short, and very short links. Acoustic links are also roughly classified as vertical and horizontal, according to the direction of the sound ray. Their propagation characteristics differ consistently, especially with respect to time dispersion, multi-path spreads, and delay variance. Acoustic signal is the only physical feasible tool that works in underwater environment. Compared with it, electromagnetic wave can only travel in water with short distance due to the high attenuation and absorption effect in underwater environment. It is found that the absorption of electromagnetic energy in sea water is about 45Ãâ€" ?f dB per kilometer, where f is frequency in Hertz; In contrast, the absorption of acoustic signal over most frequencies of interest is about three orders of magnitude lower [40]. Hereafter the factors that influence acoustic communications is analyzed in order to state the challenges posed by the underwater channels for underwater sensor networking. These include: Path loss Attenuation is mainly provoked by absorption due to conversion of acoustic energy into heat, which increases with distance and frequency. It is also caused by scattering a reverberation (on rough ocean surface and bottom), refraction, and dispersion (due to the displacement of the reflection point caused by wind on the surface). Water depth plays a key role in determining the attenuation. Geometric Spreading is the spreading of sound energy as a result of the expansion of the wavefronts. It increases with the propagation distance and is independent of frequency. There are two common kinds of geometric spreading: spherical (omni-directional point source), and cylindrical (horizontal radiation only). Noise Man made noise is mainly caused by machinery noise (pumps, reduction gears, power plants, etc.), and shipping activity (hull fouling, animal life on hull, cavitations), especially in areas encumbered with heavy vessel traffic. Ambient Noise is related to hydrodynamics (movement of water including tides, current, storms, wind, rain, etc.), seismic and biological phenomena. Multi-path Multi-path propagation may be responsible for severe degradation of the acoustic communication signal, since it generates Inter-Symbol Interference (ISI). The multi-path geometry depends on the link configuration. Vertical channels are characterized by little time dispersion, whereas horizontal channels may have extremely long multi-path spreads. The extent of the spreading is a strong function of depth and the distance between transmitter and receiver. High delay and delay variance The propagation speed in the UW-A channel is five orders of magnitude lower than in the radio channel. This large propagation delay (0.67 s/km) can reduce the throughput of the system considerably. The very high delay variance is even more harmful for efficient protocol design, as it prevents from accurately estimating the round trip time (RTT), which is the key parameter for many common communication protocols. Doppler spread The Doppler frequency spread can be significant in UW-A channels, causing degradation in the performance of digital communications: transmissions at a high data rate because many adjacent symbols to interfere at the receiver, requiring sophisticated signal processing to deal with the generated ISI. The Doppler spreading generates: a simple frequency translation, which is relatively easy for a receiver to compensate for a continuous spreading of frequencies, which constitutes a non-shifted signal, which is more difficult for a receiver to compensate for. If a channel has a Doppler spread with bandwidth B and a signal has symbol duration T, then there are approximately BT uncorrelated samples of its complex envelope. When BT is much less than unity, the channel is said to be under spread and the effects of the Doppler fading can be ignored, while, if greater than unity, it is overspread. Most of the described factors are caused by the chemical-physical properties of the water medium such as temperature, salinity and density, and by their spatio-temporal variations. These variations, together with the wave guide nature of the channel, because the acoustic channel to be temporally and spatially variable. In particular, the horizontal channel is by far more rapidly varying than the vertical channel, in both deep and shallow water. CHAPTER 3: Network Architecture Underwater sensor nodes: The underwater sensor nodes are deployed on the sea floor anchored to the ocean bottom [32]. The sensors are equipped with floating buoys to push the nodes upwards, thus they are relatively stationary nodes [3]. Using acoustic links, they relay data to underwater sink directly or via multi-hop path. Underwater sink nodes: Underwater sink nodes take charge of collecting data of underwater sensors deployed on the ocean bottom and then send to the surface sink node. They may be equipped with vertical and horizontal acoustic transducers. The horizontal transceiver is used to collect the sensors data and the vertical transceiver provides transmitting link between underwater sink and the surface sink node. Surface sink node: Surface sink node is attached on a floating buoy with satellite, radio frequency (RF) or cell phone technology to transmit data to shore in real time. 2D Model A reference architecture for two-dimensional underwater networks is shown in Figure. 1. A group of sensor nodes are anchored to the deep of the ocean. Underwater sensor nodes are interconnected to one or more underwater gateways by means of wireless acoustic links. Underwater-gateways are network devices in charge of relaying data from the ocean bottom network to a surface station. To achieve this objective, they are equipped with two acoustic transceivers, namely a vertical and a horizontal transceiver. The horizontal transceiver is used by the underwater-gateway to communicate with the sensor nodes in order to: send commands and configuration data to the sensors (underwater -gateway to sensors); collect monitored data (sensors to underwater -gateway). The vertical link is used by the underwater -gateways to relay data to a surface station. In deep water applications, vertical transceivers must be long range transceivers. The surface station is equipped with an acoustic transceiver that is able to handle multiple parallel communications with the deployed underwater -gateways. It is also endowed with a long range RF and/or satellite transmitter to communicate with the onshore sink (os-sink) and/or to a surface sink (s-sink). In shallow water, bottom-deployed sensors/modems may directly communicate with the surface buoy, with no specialized bottom node (underwater -gateway). 3D Model Three-dimensional underwater networks are used to detect and observe phenomena that cannot be adequately observed by means of ocean bottom sensor nodes, i.e., to perform cooperative sampling of the 3D ocean environment. In three-dimensional underwater networks, sensor nodes float at different depths to observe a phenomenon. In this architecture, given in Figure 2, each sensor is anchored to the ocean bottom and equipped with a floating buoy that can be inflated by a pump. The buoy pushes the sensor towards the ocean surface. The depth of the sensor can then be regulated by adjusting the length of the wire that connects the sensor to the anchor, by means of an electronically controlled engine that resides on the sensor. Sensing and communication coverage in a 3D environment are rigorously investigated in [8]. The diameter, minimum and maximum degree of the reachability graph that describes the network are derived as a function of the communication range, while different degrees of cov erage for the 3D environment are characterized as a function of the sensing range. 3D Model with AUV The above figure represents the third type of network architecture which consist of sensor nodes and Autonomous Underwater Vehicles (AUV) which act as mobile sensor nodes for ocean monitoring, underwater resource study, etc. CHAPTER 4: Differences between underwater and terrestrial Sensor Network An underwater acoustic channel is different from a ground-based radio channel from many aspects, including: Bandwidth is extremely limited. The attenuation of acoustic signal increases with frequency and range [6] [10]. Consequently, the feasible band is extremely small. For example, a short range system operating over several tens of meters may have available bandwidth of a hundred kHz; a medium-range system operating over several kilometers has a bandwidth on the order of ten kHz; and a long-range system operating over several tens of kilometers is limited to only a few kHz of bandwidth [11]. Propagation delay is long. The transmission speed of acoustic signals in salty water is around 1500 meter/s [22], which is a difference of five orders of magnitude lower than the speed of electromagnetic wave in free space. Correspondently, propagation delay in an underwater channel becomes significant. This is one of the essential characteristics of underwater channels and has profound implications on localization and time synchronization. The channel impulse response is not only spatially varied but also temporarily varied. The channel characteristics vary with time and highly depend on the location of the transmitter and receiver. The fluctuation nature of the channel causes the received signals easily distorted. There are two types of propagation paths: macro-multipaths, which are the deterministic propagation paths; and micro-multipath, which is a random signal fluctuation. The macro-multipaths are caused by both reflection at the boundaries (bottom, surface and any object in the water) and bending. Inter- Symbol Interference (ISI) thus occurs. Compared with the spread of its ground-based counterpart, which is on the order of several symbol intervals, ISI spreading in an underwater acoustic channel is several tens or hundred of symbol intervals for moderate to high data rate in the horizontal channel. Micro-multipath fluctuations are mainly caused by surface wave, which contributes the most to the time variability of shallow water channel. In deep water, internal waves impact the single-path random fluctuations [12][13]. Probability of bit error is much higher and temporary loss of connectivity (shadow zone) sometimes occurs, due to the extreme characteristics of the channel. Cost. While terrestrial sensor nodes are expected to become increasingly inexpensive, underwater sensors are expensive devices. This is especially due to the more complex underwater transceivers and to the hardware protection needed in the extreme underwater environment. Also, because of the low economy of scale caused by a small relative number of suppliers, underwater sensors are characterized by high cost. Deployment. While terrestrial sensor networks are densely deployed, in underwater, the deployment is generally more sparse. Power. The power needed for acoustic underwater communications is higher than in terrestrial radio communications because of the different physical layer technology (acoustic vs. RF waves), the higher distances, and more complex signal processing techniques implemented at the receivers to compensate for the impairments of the channel. Memory. While terrestrial sensor nodes have very limited storage capacity, underwater-sensors may need to be able to do some data caching as the underwater channel may be intermittent. Spatial Correlation. While the readings from terrestrial sensors are often correlated, this is more unlikely to happen in underwater networks due to the higher distance among sensors. CHAPTER 5: Layered of UASN The underwater architecture network consists of five layers, application, transport, network, data link and physical layer as shown in the figure below. As typical underwater systems have limited processing capability, the protocol has been kept as simple as possible without significantly compromising performance. The underwater sensor network specifications currently do not include any recommendations for authentication and encryption. These may be easily implemented at the application layer or via a spreading scheme at the physical layer. Each layer is described by a SAPI. The SAPI is defined in terms of messages being passed to and from the layer. The clients (usually higher layers) of a layer invoke the layer via a request (REQ). The layer responds to each REQ by a response (RSP). Errors are reported via an ERR RSP with error codes. If the layer needs to send unsolicited messages to the client, it does so via a notification (NTF). A layer communicates logically with its peer layer via protocol data units (PDU). As the peer-to-peer communication is symmetric, a layer may send a REQ PDU to its peer layer at any time. It would optionally respond to such a PDU with a RSP PDU. This is logically depicted in Figure below It may be desirable in some cases, that non-neighboring layers communicate with each other to achieve cross-layer optimization. This may be implemented by allowing REQ and RSP PDUs between any two layers in the protocol stack. The underwater sensor network specifications define detailed message structures for all SAPI messages. These message structures include message identifiers, data formats to be used, parameters and their possible values Physical layer The physical layer provides framing, modulation and error correction capability (via FEC). It provides primitives for sending and receiving packets. It may also provide additional functionality such as parameter settings, parameter recommendation, carrier sensing, etc. At first underwater channel development was based on non-coherent frequency shift keying (FSK) modulation, since it relies on energy detection. Thus, it does not require phase tracking, which is a very difficult task mainly because of the Doppler-spread in the underwater acoustic channel. Although non-coherent modulation schemes are characterized by high power efficiency, their low bandwidth efficiency makes them unsuitable for high data rate multiuser networks. Hence, coherent modulation techniques have been developed for long-range, high-throughput systems. In the last years, fully coherent modulation techniques, such as phase shift keying (PSK) and quadrature amplitude modulation (QAM), have become practical due to the availability of powerful digital processing. Channel equalization techniques are exploited to leverage the effect of the inter-symbol interference (ISI), instead of trying to avoid or suppress it. Decision-feedback equalizers (DFEs) track the complex, relatively slowly varying channel response and thus provide high throughput when the channel is slowly varying. Conversely, when the channel varies faster, it is necessary to combine the DFE with a Phase Locked Loop (PLL) [9], which estimates and compensates for the phase offset in a rapid, stable manner. The use of decision feedback equalization and phase-locked loops is driven by the complexity and time variability of ocean channel impulse responses. Differential phase shift keying (DPSK) serves as an intermediate solution between incoherent and fully coherent systems in terms of bandwidth efficiency. DPSK encodes information relative to the previous symbol rather than to an arbitrary fixed reference in the signal phase and may be referred to as a partially coherent modulation. While this strategy substantially alleviates carrier phase-tracking requirements, the penalty is an increased error probability over PSK at an equivalent data rate. Another promising solution for underwater communications is the orthogonal frequency division multiplexing (OFDM) spread spectrum technique, which is particularly efficient when noise is spread over a large portion of the available bandwidth. OFDM is frequently referred to as multicarrier modulation because it transmits signals over multiple sub-carriers simultaneously. In particular, sub-carriers that experience higher SNR, are allotted with a higher number of bits, whereas less bits are allotted to sub-carriers experiencing attenuation, according to the concept of bit loading, which requires channel estimation. Since the symbol duration for each individual carrier increases, OFDM systems perform robustly in severe multi-path environments, and achieve a high spectral efficiency. Many of the techniques discussed above require underwater channel estimation, which can be achieved by means of probe packets [17]. An accurate estimate of the channel can be obtained with a high probing rate and/or with a large probe packet size, which however result in high overhead, and in the consequent drain of channel capacity and energy. Data link layer (MAC layer) The data link layer provides single hop data transmission capability; it will not be able to transmit a packet successfully if the destination node is not directly accessible from the source node. It may include some degree of reliability. It may also provide error detection capability (e.g. CRC check). In case of a shared medium, the data link layer must include the medium access control (MAC) sub-layer. Frequency division multiple access (FDMA) is not suitable for underwater sensor network due to the narrow bandwidth in underwater acoustic channels and the vulnerability of limited band systems to fading and multipath. Time division multiple access (TDMA) shows limited bandwidth efficiency because of the long time guards required in the underwater acoustic channel. In fact, long time guards must be designed to account for the large propagation delay and delay variance of the underwater channel in order to minimize packet collisions from adjacent time slots. Moreover, the variable delay makes it very challenging to realize a precise synchronization, with a common timing reference, which is required for TDMA. Carrier sense multiple access (CSMA) prevents collisions with the ongoing transmission at the transmitter side. To prevent collisions at the receiver side, however, it is necessary to add a guard time between transmissions dimensioned according to the maximum propagation delay in the network. This makes the protocol dramatically inefficient for underwater acoustic sensor network. The use of contention-based techniques that rely on handshaking mechanisms such as RTS/ CTS in shared medium access is impractical in underwater, for the following reasons: large delays in the propagation of RTS/CTS control packets lead to low throughput; due to the high propagation delay of underwater acoustic channels, when carrier sense is used, as in 802.11, it is more likely that the channel be sensed idle while a transmission is ongoing, since the signal may not have reached the receiver yet; the high variability of delay in handshaking packets makes it impractical to predict the start and finish time of the transmissions of other stations. Thus, collisions are highly likely to occur. Code division multiple access (CDMA) is quite robust to frequency selective fading caused by underwater multi-paths, since it distinguishes simultaneous signals transmitted by multiple devices by means of pseudo-noise codes that are used for spreading the user signal over the entire available band. CDMA allows reducing the number of packet retransmissions, which results in decreased battery consumption and increased network throughput. In conclusion, although the high delay spread which characterizes the horizontal link in underwater channels makes it difficult to maintain synchronization among the stations, especially when orthogonal code techniques are used [17], CDMA is a promising multiple access technique for underwater acoustic networks. This is particularly true in shallow water, where multi-paths and Doppler- spreading plays a key role in the communication performance. Network layer (Routing) The network layer is in charge of determining the path between a source (the sensor that samples a physical phenomenon) and a destination node (usually the surface station). In general, while many impairments of the underwater acoustic channel are adequately addressed at the physical and data link layers, some other characteristics, such as the extremely long propagation delays, are better addressed at the network layer. Basically, there are two methods of routing. The first one is virtual circuit routing and the second one is packet-switch routing. In virtual circuit routing, the networks use virtual circuits to decide on the path at the beginning of the network operation. Virtual-circuit-switch routing protocols can be a better choice for underwater acoustic networks. The reasons are: Underwater acoustic networks are typical asymmetric instead of symmetric. However, packet switched routing protocols are proposed for symmetric network architecture; Virtual-circuit-switch routing protocols work robust against link failure, which is critical in underwater environment; and Virtual-circuit-switch routing protocols have less signal overhead and low latency, which are needed for underwater acoustic channel environment. However, virtual-circuit-switch routing protocols usually lack of flexibility. In packet-switch routing, every node that is part of the transmission makes its own routing decision, i.e., decides its next hop to relay the packet. Packet-switch routing can be further classified into Proactive routing, Reactive and geographical routing protocols. Most routing protocols for ground-based wireless networks are packet-switch based. Proactive routing protocols attempt to minimize the message latency by maintaining up-to-date routing information at all times from each node to any other node. It broadcasts control packets that contain routing table information. Typical protocols include Destination Sequence Distance Vector (DSDV) [28] and Temporally Ordered Routing Algorithm (TORA). However, proactive routing protocols provoke a large signaling overhead to establish routes for the first time and each time the network topology changes. It may not be a good fit in underwater environment due to the high probability of link failure and extremely limited bandwidth there. Reactive routing protocols only initiate a route discovery process upon request. Correspondently, each node does not need to maintain a sizable look-up table for routing. This kind of routing protocols is more suitable for dynamic environment like ad hoc wireless networks. Typical protocol examples are Ad hoc On-demand Distance Vector (AODV) [23], and Dynamic Source Routing (DSR) [27]. The shortage of reactive routing protocols is its high latency to establish routing. Similar to its proactive counterpart, flooding of control packets to establish paths is needed, which brings significant signal overhead. The high latency could become much deteriorated in underwater environment because of the much slower propagation speed of acoustic signal compared with the radio wave in the air. Geographic routing (also called georouting or position-based routing) is a routing principle that relies on geographic position information. It is mainly proposed for wireless networks and based on the idea that the source sends a message to the geographic location of the destination instead of using the network address. Geographic routing requires that each node can determine its own location and that the source is aware of the location of the destination. With this information a message can be routed to the destination without knowledge of the network topology or a prior route discovery. Transport layer A transport layer protocol is needed in underwater sensor network not only to achieve reliable collective transport of event features, but also to perform flow control and congestion control. The primary objective is to save scarce sensor resources and increase the network efficiency. A reliable transport protocol should guarantee that the applications be able to correctly identify event features estimated by the sensor network. Congestion control is needed to prevent the network from being congested by excessive data with respect to the network capacity, while flow control is needed to avoid that network devices with limited memory are overwhelmed by data transmissions. Most existing TCP implementations are unsuited for the underwater environment, since the flow control functionality is based on a window- based mechanism that relies on an accurate esteem of the round trip time (RTT), which is twice the end-to-end delay from source to destination. Rate-based transport protocols seem also unsuited for this challenging environment. They still rely on feedback control messages sent back by the destination to dynamically adapt the transmission rate, i.e., to decrease the transmission rate when packet loss is experienced or to increase it otherwise. The high delay and delay variance can thus cause instability in the feedback control. Furthermore, due to the unreliability of the acoustic channel, it is necessary to distinguish between packet losses due to the high bit error rate of the acoustic channel, from those caused by packets being dropped from the queues of sensor nodes due to network congestion. In terrestrial, assume that congestion is the only cause for packet loss and the solution lies on decreasing the transmission rate, but in underwater sensor network if the packet loss is due to bad channel then the transmission rate should not be decreased to preserve throughput efficiency. Transport layer functionalities can be tightly integrated with data link layer functionalities in a cross-layer module. The purpose of such an integrated module is to make the information about the condition of the variable underwater channel available also at the transport layer. In fact, usually the state of the channel is known only at the physical and channel access sub-layers, while the design principle of layer separation makes this information transparent to the higher layers. This integration allows maximizing the