Underwater Wireless Sensor Networks: A Review Of Recent Issues And .
HindawiWireless Communications and Mobile ComputingVolume 2019, Article ID 6470359, 20 pageshttps://doi.org/10.1155/2019/6470359Review ArticleUnderwater Wireless Sensor Networks: A Review of RecentIssues and ChallengesKhalid Mahmood Awan,1 Peer Azmat Shah ,1 Khalid Iqbal,2 Saira Gillani,3Waqas Ahmad,1 and Yunyoung Nam 41Internet Communication & Networks (ICNet) Research Lab, Department of Computer Science, COMSATS University Islamabad,Attock 43600, Pakistan2Pattern Recognition, Images and Data Engineering (PRIDE) Lab, Department of Computer Science, COMSATS University Islamabad,Attock 43600, Pakistan3College of computing and informatics Saudi Electronic University, Jeddah, Saudi Arabia4Department of Computer Science and Engineering, Soonchunhyang University, Asan 31538, Republic of KoreaCorrespondence should be addressed to Yunyoung Nam; ynam.sch@gmail.comReceived 29 June 2018; Revised 1 October 2018; Accepted 11 November 2018; Published 1 January 2019Guest Editor: Sungchang LeeCopyright 2019 Khalid Mahmood Awan et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Underwater Wireless Sensor Networks (UWSNs) contain several components such as vehicles and sensors that are deployedin a specific acoustic area to perform collaborative monitoring and data collection tasks. These networks are used interactivelybetween different nodes and ground-based stations. Presently, UWSNs face issues and challenges regarding limited bandwidth,high propagation delay, 3D topology, media access control, routing, resource utilization, and power constraints. In the last fewdecades, research community provided different methodologies to overcome these issues and challenges; however, some of themare still open for research due to variable characteristics of underwater environment. In this paper, a survey of UWSN regardingunderwater communication channel, environmental factors, localization, media access control, routing protocols, and effect ofpacket size on communication is conducted. We compared presently available methodologies and discussed their pros and cons tohighlight new directions of research for further improvement in underwater sensor networks.1. IntroductionTechnique of sending and receiving message under theutilization of sound propagation in underwater environmentis known as acoustic communication. Underwater sensornetworks have number of vehicles and sensors that deploy ina specific area to perform collaborative monitoring and datacollection tasks [1]. Traditionally for the monitoring of oceanbottom, oceanographic sensors are deployed for recordingdata at a fix location and recover the instruments at thecompletion of task. The major disadvantage of traditionalapproach is lack of interactive communication between different ends, recorded data can never get during any mission,and in case of any failure recorded data will be destroyed.Underwater Sensor Networks support a wide varietyof applications [2]; for example, aquatic surveillance, riverand sea pollution discovery, monitoring, oceanographic datacompilation, and commercial exploit the aquatic environment [3]. Underwater Sensor Networks can be utilized inany scenario from underwater warfare to the monitoring ofenvironmental conditions [2]. Underwater Sensor Networksface constraints like limited bandwidth, high propagationdelay, 3D topology, and power constraints. Radio and opticalwaves are not feasible for communication at each pointof ocean. Under the entire limitations underwater sensornetworks can only utilize acoustic signal that is a techniquewhich is utilized by nature from the birth of ocean [4,5]. Speed of sound is considered constant in underwaterenvironment. However, speed of sound is affected by temperature, depth, and salinity of underwater environment. Thesefactors produce variations in speed of sound in underwaterenvironment [6]. Underwater acoustic channel frequenciesspectrum, especially on mid-frequencies, is heavily shared
2Wireless Communications and Mobile ComputingSection 1 IntroductionSection 2 Underwater Sensor Network ArchitectureSection 3 Propagations of Underwater Sensor NetworkSection 3.1 Path lossSection 3.2 NoiseSection 3.3 Multi PathSection 3.4 Doppler SpreadSection 4 Related StudiesSection 5 Issues & Challenges regarding Underwater Sensor NetworkSection 5.1 Environmental EffectSection 5.2 Cognitive CommunicationSection 5.3 MAC IssuesSection 5.4 Channel UtilizationSection 5.5 LocalizationSection 5.6 Routing IssuesSection 5.7 Optimal Packet Size Selection & Energy EfficiencySection 6 Conclusion & Future WorkFigure 1: Overview of research work.by various acoustic users in underwater environment. Stillacoustic spectrum is temporally and spatially underutilizedin underwater environment [7]. Variable characteristics ofunderwater environment have become a challenge for utilizing acoustic channel. For example, multipath propagationresults in fading and phase fluctuations; Doppler Effect isobserved due to the movement of both the sender andreceiver nods. Speed of sound and underwater noise are otherfactors that influences the performance of acoustic channel[8].Underwater sensor networks nodes are not static likeground-based sensor networks nodes. Instead, they move dueto different activities and circumstances of underwater environment, usually 2-3m/sec with water currents. Sensed datais meaningful only when localization is involved. Anothermajor issue that is affecting underwater sensor networks isenergy saving. Because of nodes mobility, the majority ofoffered energy competent protocols become inappropriatefor underwater sensor networks. Different protocols regarding land-based sensor networks are, for example, DirectedDiffusion, Gradient, Rumor routing, TTDD, and SPIN.However, because of mobility and rapid change in networktopology these existing grounds based routing protocolscannot perform efficiently in underwater environment [9].Optimal packet size is depending on protocol characteristiclike offered load and bit error rate. Poor packet size selection decreases the performance of the network throughputefficiency, latency, and resource utilization and energy consumption in multihop underwater networks can be greatlyimproved by a using optimum packet size [10–13].To improve the better utilization of the available resourcesin underwater environment considering the energy and lifetime of network is discussed in detail in this paper. Balancing of energy consumption is carried out in underwaterenvironment using the proposed techniques. The importantcontributions of this work are not only to highlight thedeep and shallow ocean characteristics, but also to presentthe effect of temperature in acoustic communication andeffect of temperature in noise, errors and protocols due tovariation in environmental factors. In addition, classificationof routing protocols for UWSNs and their comparison interms of bounded latency, multipath, load balancing, energyconsumption, geographic information, communication overhead, and time complexity. Similarly, data delivery ratios forsingle and multipath and the strengths and weaknesses ofMAC protocols, with the used topology, are compared [14–16].The paper is organized as illustrated in Figure 1. Section 2presents the architecture of Underwater Wireless SensorNetworks. Section 3 describes propagation phenomena of
Wireless Communications and Mobile SurfaceStationOffshore SinkSurfaceStationOffshore nk(a)(b)Figure 2: Two- and 3-dimensional networks architecture for UWSN regarding communication given in (a) and (b), respectively.Underwater Wireless Sensor Networks. Section 4 presentsprevious achievements of different researcher in the form ofrelated studies. The issues and challenges regarding underwater sensor networks are described in Section 5. Conclusionand future work are made in Section 6.2. Underwater Sensor Networks ArchitectureUnderwater network’s physical layer utilizes acoustic technology for communication. Limited bandwidth, capacity, andvariable delays are characteristics of acoustic technology.Therefore, new data communication techniques and efficientprotocols are required, for underwater acoustic networks.Designing the network topology requires significant devotionfrom designer, because underwater network performance isgenerally depending upon topology design. Network reliability should increase with efficient network topology andnetwork reliability should also decrease with less efficienttopology. Energy consumption of efficient network topologyis highly less as compared to incorrect and less efficienttopology design of underwater network. Design of topologyfor underwater sensor network is an open area for research[18, 19]. Underwater sensor networks architecture is shownin Figure 2.2.1. Underwater Sensor Networks in Two-Dimensions. Deepocean anchors are utilized for collection of sensor nodesin two-dimensional underwater sensor network architecture.Anchored underwater nodes use acoustic links to communicate with each other or underwater sinks. Underwatersinks are responsible to collect data from deep ocean sensorsand provide it to offshore command stations, using surfacestations. For this purpose, underwater sinks are provided inthe company of horizontal and vertical acoustic transceivers.Purpose of horizontal transceivers is to communicate withsensor node, to collect data or provide them commands, ashave been received by offshore command station, althoughvertical transceiver is used to send data to command station.Because ocean can be as deep as 10 km, vertical transceivershould contain enough range. Surface sink that is equippedwith acoustic transceivers has the capability to manage parallel communication, by means of multiple organized underwater sinks. Surface sink is also equipped through extensiverange radio frequency transmitters, to communicate withoffshore sinks [18–21].2.2. Underwater Sensor Networks in Three Dimensions. Activity required to present three-dimensional environmentsnew architecture which is known as underwater threedimensional networks is used. Sensor nodes float at differentdepth to monitor a specific activity in three-dimensionalunderwater networks. Traditional solution regarding underwater three-dimensional sensor networks is the use of surfacebuoys that provide ease in deploying such kind of network.But this solution is vulnerable to weather and tampering.Also, effortlessly can be discovered and disabled by enemiesin the scenario of military operation. In underwater threedimensional sensor networks architecture, ocean bottom isutilized to anchored sensor nodes. Depth of these nodes iscontrolled using wires which are attached with these anchors.Major challenge regarding such network is influenced by thecurrent properties of the oceans [18–20].3. Propagation Phenomena of UnderwaterSensor NetworksAcoustic communication regarding underwater environmentis a complex phenomenon because a lot of environmentalfactors affect acoustic communication. These factors arevariable like long propagation delays, environmental noise,
4Wireless Communications and Mobile ComputingTable 1: Deep and shallow ocean ti-path LossSpreading Factor (K)Shallow Ocean0 m to 100 mHighSurface ReflectionCylindricalpath loss, Doppler spread, and multipath effect. Underwaterenvironmental factors make acoustic channel highly variable.They also create bandwidth dependency upon both frequencyand distance between two nodes. Generally, ocean is dividedinto two parts; these are shallow and deep ocean. Shallowand deep ocean characteristics are described in the Table 1.Shallow ocean highly affects acoustic channel because ofhigh temperature gradient, multipath effect, surface noise,and large propagation delays, as compared to deep ocean.Underwater environment major propagation factors thataffect acoustic communication are described in subsequentsections.3.1. Path Loss. When sound propagates from underwaterenvironment then some of its strength converts into heat.Sound wave propagation energy loss can be categorized intothree main categories which are described below.(1) Geometric Spreading Loss. When source generates acousticsignal it propagates away from the source in the form of wavefronts. It is independent of frequency, however, dependingupon distance covered by wave front. Geometric spreading isdivided into two types: first spherical spreading that depictsdeep ocean communication; second cylindrical spreadingthat depicts shallow water communication [5, 18].(2) Attenuation. Attenuation is defined as “wave energyconverted into some other form of energy”, such as heatenergy, absorbed by the medium used. Within acousticcommunication, this phenomenon is compassionated asacoustic energy is converted into heat. The converted heat isabsorbed by underwater environment. Attenuation is directlyproportional to frequency and distance [5, 18].(3) Scattering Loss. Deviation regarding the line of sight ofa signal or change in angle is generally a physical property.Underwater channel also contains this property that effectsacoustic channel data transmission during communication.Surface roughness increases due to increase in the windspeed. That raises the end product of scattering surface.Scattering surface not only affects delays but also affectspower loss [5, 18].3.2. Noise. Noise can be defined as a quality of communication system that degrades signal strength of any communication system. In case of underwater acoustic channelthere exist different kinds of noises. Underwater noises canbe divided into two major categories. These are ambientDeep Ocean100 m to 10000 mLowBoth Surface and Bottom ReflectionSphericalnoise and noises by human beings. Both kinds of noises aredescribed in detail in the following sections.(1) Noise by Human Beings. These noises are due to heavymachinery utilization, shipping activities, fishing activities,military activities, sonar activities, and aircraft activities andbecause of heavy data traffic sending and receiving activitiescause different kind of disturbance and interference duringacoustic communication. Sometime noises due to humanbeings also disturb natural acoustic communication [18].(2) Ambient Noise. Ambient noise is a complex phenomenonregarding underwater communication. It can also be definedas a combination of different sources that cannot uniquelyidentify [22]. Ambient noise is also called background noisethat occurs as a result of unidentified sources [5]. These noisesare divided into four major categories which are knownas wind, shipping, thermal, and the turbulence [1]. Windnoise is due to breakage of wave or because of bubblescreated by air. Noise can be simply predicted and forecastfrom weather forecasts because of dependence of noise uponwind speed. Large number of ships present at large distancefrom communication system in ocean produce high trafficnoise in acoustic communication, if sound propagation isgood enough. Ships consider main source of anthropogenicambient noise [22]. Turbulence can be defined as surfacedisturbance due to waves or tides that generates low frequencies that results continuous noise in acoustic communication.Underlying noise is considered as thermal noise in theabsence of all other sources of noise, including self-noise.Thermal noise is directly proportional to the frequency whichis used for acoustic communication [23].3.3. Multipath. Sound propagation in shallow water is influenced by surface reflections while deep water propagation isaffected by bottom reflection that becomes cause of large andvariable communication delay in acoustic communication.A major cause that makes acoustic signal weak is calledmultipath effect that becomes cause of intersymbol interference which also makes acoustic data transmission difficultand erroneous. Vertical acoustic channel is less affected bymultipath effect as compared to horizontal acoustic channel[18, 19, 21].To address the problem of long propagation delay andhigh lite error rate a routing protocol QERP was proposedto handle end-to-end delay but this protocol still needsto address the mobility issues [14]. Mostly in deep oceansbecause of variable sound speed, refraction of sound occursthat cases of multipath effect in acoustic channel. Number
Wireless Communications and Mobile Computing5Table 2: Effect of temperature on acoustic communication.S.No01020304Sound speed Effectsdue to temperatureArea FocusedFindingsUnderwater WirelessSensor Networks: RoutingIssues and FutureChallengesProspects and Problems ofWireless Communicationfor Underwater SensorNetworksSurvey of temperaturevariation effect onunderwater acousticwireless transmissionVariability of availablecapacity because of depthand temperature in theunderwater acousticcommunication channelSpeed of sound increases due to increase in thetemperature of ocean and decreases in colder oceans.Approximately, the mount of 1 c can boost the speed ofsound near to 4.0 m/s.Shallow water effects acoustic communication bytemperature gradients, ambient noises regardingsurface and multi-path effect because of reflection andrefraction.Speed of sound is affected by temperature, depth andsalinity of underwater environment. These factorsproduce variations in speed of sound in underwaterenvironment.Effects communicationDetermine acoustic channel capacity on shortdistances, increasing temperature and depth as a resultgets higher channel capacity and throughput rates.Improves throughput05Underwater ChannelSimulation06Mathematical equation forsound speed in the oceansTemperature of sea surface is much higher as iscompared to the bottom temperature. Velocity of soundis also affected with increase in depth, salinity andtemperature.Temperature is a dominating factor that has effect onthe sound speed.of propagation paths, propagation delays, and its strengthare determined by acoustic channel impulse response that isinfluenced by channel reflection and geometry. Large numbers of paths exist in acoustic channel but only those pathsare considered which have less energy loss and reflections.All other paths are discarded as a result only finite number ofpaths remains for acoustic communication and data transfer[24].3.4. Doppler Spread. Because of channel flaws, wireless signals practice a diversity of degradations. For example, electromagnetic signal affects by interference, reflections, andattenuation; acoustic signals regarding underwater are alsoaffected by same kind of factors [25]. Underwater acousticchannel is complex channel due to time variation and spacevariation. The relative motion of transmitter and receiverthat causes the mean frequency shift is called Doppler shift.Although the fluctuation of frequency in the region ofthis Doppler shift is called Doppler spread [8], two typesof influences are observed on acoustic channel because ofDoppler Effect: first is pulse width that will be compressedor stretched and second is frequency offset as a result offrequency offset compressing or expending of signal timedomain occurring [26].4. Related StudiesPresently underwater communication system utilizes electromagnetic, optics, and acoustic data transmission techniquesto send data among different positions. ElectromagneticIncrease withtemperatureVariation in speedIncreases withtemperatureIncreases withtemperaturecommunication technique is affected by conducting natureof seawater while optic waves are applicable on very shortdistance because optic waves are absorbed by seawater.Acoustic communication is only one technique that has betterperformance regarding underwater communication due toless attenuation in seawater. Acoustic communication alsohas less attenuation in deep and thermally stable oceans. Shallow water affects acoustic communication by temperaturegradients, ambient noises regarding surface, and multipatheffect because of reflection and refraction [5]. Speed of soundis not constant in underwater environment instead of thisspeed of sound varies from point to point. Close to thesurface of ocean speed of sound is found to be 1500 m/sthat is four times higher than speed of sound in air but veryslow as compared to speed of optics that is 3 108 m/sand electromagnetic in air. Table 2 shows the effects oftemperature on acoustic communication and its effects withvariation in temperature.Natural acoustic systems and artificial acoustic systemsboth use acoustic channel in case of underwater environment.Both acoustic systems heavily utilize middle frequencies;because of that their communication affects each other, asthey use same frequencies. Still, acoustic channel spectrumis not utilized efficiently. High spectrum utilization andto develop an environment friendly underwater acousticnetwork (UAN), Luo et al. [7] present Cognitive Acoustic(CA) as a promising technique. This technique has thecapability to wisely sense whether any part of the spectrumis engaged by any other and also has the capability to changetheir frequency, power, or even other operation parametersto temporarily use the idle frequencies without interfering
6with other networks. The CA technique makes communication environment friendly and erroneous free by avoidinginterference with marine mammals. An important issue inunderwater environment is use of low frequencies whichresults in low data rate. Other problems like energy dispersionand reflection also degrade the performance of devices. Inthis study the author proposed a model for underwatercommunication which monitors the performance of thewireless sensor nodes based on different frequencies andachieved high data rate [27].Acoustic channel is highly variant because of uniquechallenges, e.g., narrow bandwidth, long propagation delays,variable speed of sound, reflection, refraction, and largepropagation losses. These unique challenges also create problems regarding media access control protocols. Media AccessControl protocols have two main categories these are scheduled protocols and contention-based protocols. Scheduledprotocols avoid collision among transmission nodes, whilein contention-based protocols nodes compete each otherfor sharing a single channel. Scheduled based protocols, forexample, Time Division Multiple Access (TDMA), are notefficient due to large propagation delays; frequency divisionmultiple access (FDMA) is not suitable due to the narrowbandwidth; and Code Division Multiple Access (CDMA) issuitable for underwater acoustic networks. While contentionbased protocols are not appropriate for underwater communications [9], Lv et al. [28] propose TDMA based UnderwaterAcoustic Channel Access Control method (UA-MAC), toimprove channel utilization in dense Mobile UnderwaterWireless Sensor Networks (MUWSN). Aim is to solve thedifficulties like, time schedule to access the channel, hiddenterminal problem, and end-to-end delay. Underwater acoustic channel access method puts into practice the piggybackscheme and as a result fewer packets are exchanged. Usingthat kind of methodology, collision decreases and saves a lotof energy. Shahab-u-deen et al. [29] combine different mediaaccess control protocols in a suite called Adaptive MultimodeMedium Access Control for Underwater Acoustic Networks,because no single protocol can complete the requirements ofunderwater sensor network media access control. AdaptiveMultimode Medium Access Control for Underwater AcousticNetworks aims to improve the performance regarding trafficintensity. This suite switches from one protocol to the otherbased on network requirements, traffic intensity, and qualityof-service requirements.Channel capacity is affected by temperature, depth, propagation loss, and ambient noise of underwater environmentwhere sensor nodes are deployed. Path loss is the function ofdistance (between pair of nodes) and frequency utilized forcommunication. These factors affect acoustic channel capacity. However, bandwidth increases with increase in depthand temperature and decreases with increase in distance.Sehgal et al. [30] determine acoustic channel capacity onshort distances, increasing temperature and depth as a resultgets higher channel capacity and throughput rates. Large biterror rates and large delays are characteristics of acousticchannel. Harris et al. [31] compare three different techniquesadaptation of packet size, forward error correction, andadaptation of packet train size to overcome long delays andWireless Communications and Mobile Computinglarge bit error rates and also to improve channel utilization.Packet train length overcomes long propagation delays inaddition of time wastage while packet size adaptation andforward error correction overcome both large propagationdelays and bit error rates. Acoustic channel utilization alsoincreases under the utilization of packet size adaptationand forward error correction. Harris’s analysis providesguidelines for creation of media access control and routingprotocols.Information regarding sensor nodes is useful only whenlocalization is involved in it. Large numbers of terrestriallocalization schemes are available but because of uniquechallenges (sensor nodes movement with ocean currents,high cost of senor nodes, global position system inapplicability, and limited battery power) of underwater sensornetworks they cannot be utilized directly. Guo et al. [32]provide a mechanism of localization which is known asAnchor-Free Localization Algorithm (AFLA). This algorithmhas ability of self-localization for anchor-free sensor nodes.AFLA uses anchor nodes and cables to restrict sensor nodein underwater environment. AFLA’s goal is to create anefficient localization scheme for underwater sensor networks.Simulation results prove that AFLA is an efficient localizationscheme and it can be utilizable in both static and dynamicnetworks scenarios. Table 3 highlights the major effects ofnoise and bit error rate during acoustic communication usingdifferent protocols.Major issues, e.g., energy conservation and mobilityregarding underwater sensor networks, create unique challenges for designing of routing protocols and make all existingground-based routing protocols (proactive and reactive)inadequate. Underwater environment required such protocols that are efficient in energy consumption, manage randomvariation in topology, and consider asymmetric links andhuge propagation delay. DU et al. [33] present a protocolwhich is known as Level-Based Adaptive Geo-Routing (LBAGR) that divides communication traffic into four categories.These are upstream to sink, downstream to sensor nodes,downstream to specific nodes, and downstream to all nodes.Data forwarding is based upon density, available batterypower, and level between neighbors that is used to electnext best hop. Level-Based Adaptive Geo-Routing goal isto achieve minimum communication delay, consume lessbattery power, and improve delivery ratio as well as receivedpackets percentage. This protocol reduces communicationend-to-end delays and improves delivery ratio and efficientutilization of battery power. Efficient utilization of batterypower is the major concern of underwater sensor networksrouting protocols.Huang et al. [34] proposed a routing protocol thatutilized energy efficiently using fuzzy logic and decision treetechniques for data forwarding towards the surface sink.Routing protocol goal is to utilize battery power efficiently inthat manner that reduces the expenditures of energy duringacoustic communication. Protocol reduces traffic overloadon acoustic channel and reduces energy consumption also.Presently, for routing protocols minimum end-to-end delayand high efficiency are the major requirements for underwater sensor networks. Ali et al. [35] present an end-to-end delay
Wireless Communications and Mobile Computing7Table 3: Effect of noise, errors, and protocols.S. No. Area of researchFindingsNoise effectBit error rateProtocol usageN/A(TDMA) is notefficient;(FDMA) is notsuitable.(CDMA) issuitable01Challenges: BuildingScalable andDistributedUnderwater WirelessSensor Networks(UWSNs) for AquaticApplications,Time Division Multiple Access (TDMA) is notefficient due to large propagation delays, FrequencyDivision Multiple Access (FDMA) is not suitable dueto the narrow bandwidth and Code DivisionMultiple Access (CDMA) is suitable for underwateracoustic networks. While contention-based protocolsare not appropriate for underwater communications.02Prospects andProblems of WirelessCommunication forUnderwater SensorNetworksAcoustic communication also has less attenuation inless attenuationdeep and thermally stable oceans. Shallow waterin deep andDecreases byeffects acoustic communication by temperatureambient noises thermally stablegradients, ambient noises regarding surface andoceansmulti-path effect because of reflection and refraction.N/A03Analyzing thePerformance ofChannel inUnderwater WirelessSensor Networks(UWSN)Multi-path propagation results in fading and phasefluctuations, Doppler Effect is observed due to themovement of both the sender and receiver nods.Speed of sound and underwater noise are otherfactors that influences the performance of acousticchannel.Decreases byambient noisesFading andphasefluctuations,Doppler EffectN/A04Optimized packet sizeselection inunderwater wirelesssensor networkcommunicationsEffect of bit error rate, interference, collision,retransmission leading selection of optimal packetsize is also considered and achieves improvement inall metric e.g., throughput, energy consumption,resource utilization and packet latencyunderutilization of optimal packet size selection.N/ALess bit errors insmall packetsN/A05Data packets are large enough as compared to theCho
Underwater Sensor Network Architecture Propagations of Underwater Sensor Network Section 2 Section 3 Section 3.1 Path loss Section 3.2 Section 3.3 Section 3.4 Section 5.1 Environmental Effect Cognitive Communication MAC Issues Routing Issues Optimal Packet Size Selection & Energy Efficiency Conclusion & Future Work Channel Utilization .
summarize the associated physical layer challenges for underwater networking. In Sections 5-9 we dis-cuss physical, data link, network, transport and application layer issues in underwater sensor net-works, respectively. In Section 10 we describe some experimental implementations of underwater sensor networks while in Section 11 we draw the
ity make the acoustic networks of UWSNs distinctive and difcult to apply practically for developers. Mo-202 Alsulami, M., Elfouly, R. and Ammar, R. Underwater Wireless Sensor Networks: A Review. DOI: 10.5220/0010970700003118 In Proceedings of the 11th International Conference on Sensor Networks (SENSORNETS 2022) , pages 202-214
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