A Review on Architecture, Issues, Challenges and Applications in Underwater Wireless Sensor Network

1. International Journal of Trend in International Open Access Journal International Open Access Journal | www.ijtsrd.com International Journal of Trend in Scientific Research and Development (IJTSRD) Research and Development (IJTSRD) www.ijtsrd.com ISSN No: 2456 ISSN No: 2456 - 6470 | Volume - 2 | Issue – 6 | Sep 6 | Sep – Oct 2018 A Review on Architecture, Issues, Underwater Wireless Sensor Network Underwater Wireless Sensor Network on Architecture, Issues, Challenges and Applications in Challenges and Applications in Gaurav Rai1, Ravi Kumar Malik2 Research Scholar, 2Assistant Professor Gaurav Rai 1Research Scholar Geeta Engineering College, Panipat Geeta Engineering College, Panipat,Haryana, India ABSTRACT Underwater Wireless Sensor Network (UWSN) is an emerging technique for applications such as marine climate observation, pollution tracking, disaster prevention, underwater surveillance etc. And, each of these applications require Sensor Nodes (SNs) to effectively provide accurate sensed data. A node must know its own location before sending data to its neighbour. The need for location arises because the number of nodes is very large and it is not possible for the base station to find the nodes’ positions, so the individual node is required to send location information along with the observed data to provide exact location to the user, which means the node must localize itself. However, due to the complex environment, it is very challenging to transmit the collected data to the base station on the surface quickly and effectively. An energy efficient routing protocol plays a vital role in data transmission. However, due to the speci characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and high latency, it is difficult to build routing protocols for UWSNs. In this article, we focus on surveying for UWSNs. In this article, we focus on surveying architecture, challenges, opportunities as well as various applications in UWSN. Keyword: UWSN, sensor nodes, application of UWSN, Acoustic signals. 1.INTRODUCTION SNs are mostly battery-powered. When depl under the water, SNs can hardly be replaced or recharged in this harsh environment, and ambient energy harvesting combined with super promising to be applied in UWSNs in the future [1]. Therefore, energy efficiency designing routing protocols for gathering sensory data and routing these data to the sink node. It is worth mentioning that most SNs drifts along with water dynamics, which makes that the task of localising SNs is very expensive and error-prone [2 that packets routing in an end be energy efficient when the network topology may change frequently and dramatically. In this paper, we will study architecture, challenges, opportunities as well as various applications in UWSN. ell as various applications in UWSN. Underwater Wireless Sensor Network (UWSN) is an emerging technique for applications such as marine climate observation, pollution tracking, disaster prevention, underwater architecture, challenges, opportunities as well as ons in UWSN. various various underwater underwater UWSN, sensor nodes, application of h of these applications require Sensor Nodes (SNs) to effectively provide accurate sensed data. A node must know its own location before sending data to its neighbour. The need for location arises because the number of nodes powered. When deplѹed under the water, SNs can hardly be replaced or recharged in this harsh environment, and ambient energy harvesting combined with super-capacitors is promising to be applied in UWSNs in the future [1]. ficiency is fundamental when designing routing protocols for gathering sensory data and routing these data to the sink node. It is worth mentioning that most SNs drifts along with water dynamics, which makes that the task of localising SNs sible for the base station find the nodes’ positions, so the individual node is required to send location information along with the observed data to provide exact location to the user, which means the node must localize itself. However, ex environment, it is very challenging to transmit the collected data to the base station on the surface quickly and effectively. An ficient routing protocol plays a vital role in data transmission. However, due to the specific SNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and ficult to build routing protocols prone [2-4]. This means that packets routing in an end-to-end manner may not ficient when the network topology may change frequently and dramatically. In this paper, we will study architecture, challenges, opportunities as Figure 1: Architecture of Underwater Sensor Network Figure 1: Architecture of Underwater Sensor Network @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Volume – 2 | Issue – 6 | Sep-Oct 2018 Oct 2018 Page: 850

2. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 2.Coverage in UWSN Coverage refers to monitoring of field in underwater through SNs[5]. Overall coverage provides you better chances to detect any event. Coverage depends on node deplѹment. There are various kinds. Various factors There are several attributes such as type of network, sensing model, node mobility, types of nodes that affect the achievable coverage in underwater. These are briefly described below i. Type of Networks Generally, two types of network has been used. first, centralized network, in which a central node directly interact with each and every node available in the network. The centralized network consumes more energy. So, overall network lifetime of the system get reduced. Second, distributed network, in which nodes form a network among themselves. These networks consumes less energy as the node can communicate with neighbour nodes for data receiving and data transmission. ii. Sensing Model Mostly, two types of sensing models used are boolean model and probabilistic model. In boolean model, after a certain distance node's are not able to sense. In 2 underwater scenario, sensing radius takes a disk shape and in 3-Dimensional scenario, it takes a spherical shape. In probabilistic model, the sensing behaviour of nodes is certain it reduces for a little time span. iii. Node Mobility In UWSN, node mobility can be of two types. One is a mobile SN and the other is a static SN, but it can move with the help of mobile medium. Nodes equipped with movability are a desired feature. iv. Types of Nodes Broadly, types of SNs are used in UWSN are of two types. first, SNs with scalar sensors (like temperature, omnidirectionality due to which the sensing locus forms a disk (2D) or a sphere (3D). And, the other kind of nodes are multimedia sensors with a directional camera. These sensors have unidirectionality and has good sensing range towards a particular direction. v. Energy Consumption The energy of the node is the central factor that affects all other performance parameters. Due to complete energy draining Due to complete energy draining if a node dies, it results in the formation of coverage holes which makes the system less efficient in dies, it results in the formation of coverage holes which makes the system less ef offering the coverage. Deplѹment Techniques SNs deplѹment is a very crucial process as it decides the achievable communication coverage in is generally of two types. First, 2D coverage in which involves SNs are depl water surface or on the seabed. But it is prone to manipulation by human intervention. Secondly, a 3D coverage in which the nodes are deplѹed in underwater 3D spaces. nderwater 3D spaces. field in underwater through SNs[5]. Overall coverage provides you better chances to detect any event. Coverage depends on ment. There are various kinds. Various factors There are several attributes such as type of network, sensing model, node mobility, types of nodes that affect the achievable coverage in vi. ment Techniques ment is a very crucial process as it decides the achievable communication coverage in UWSN [6], [7]. It is generally of two types. First, 2D coverage in are deplѹed either on the water surface or on the seabed. But it is prone to manipulation by human intervention. Secondly, a 3D coverage in which the nodes sensing sensing and and described below. Generally, two types of network has been first, centralized network, in which a irectly interact with each and every node available in the network. The centralized network consumes more energy. So, overall network lifetime of the system get reduced. Second, distributed network, in which nodes form a network among 3.Underwater Architecture On basis of design, common architectures of UWSN are as follows: i. One-dimensional Architecture of UWSN In One-dimensional UWSN communicate using acoustic, Radio Frequenc (RF), or optical communication. The nature of topology in One-dimensional refers to a network where the SNs are deplѹed autonomously and each sensor node is a stand-alone network itself which is responsible for sensing, processing, and transmitting the information to the remote station [5]. It can be an Autonomous Underwater Vehicle (AUV) which dives inside the water, sense the data and transfer the information to the remote station. ii. Two-dimensional Architecture Two-dimensional UWSN architecture refers to a network where a group of SNs forms a cluster. Each cluster has a Cluster Head (CH). Each member of the cluster gathers the data and communicates it to the CH. After collecting data , the CH relays it to the sin For the cluster of nodes, the network arrangement can be dynamic (star, mesh, or ring) depending requirement [6]. iii. 3D-UWSN Architecture. the sensors are deplѹ form of clusters and are anchored depths. Different communication scenarios in this architecture communication of nodes, (ii) intracluster (sensor-anchor node) communication, and (iii) CH-sink communication. Acoustic, optical, and RF links for communicati and RF links for communication can be used. Underwater Wireless Wireless Sensor Sensor Network Network On basis of design, common architectures of UWSN works consumes less Architecture of UWSN UWSN the nodes can energy as the node can communicate with neighbour nodes for data receiving and data communicate using acoustic, Radio Frequency (RF), or optical communication. The nature of dimensional UWSN is star. It refers to a network where the SNs are ed autonomously and each sensor node alone network itself which is responsible for sensing, processing, and transmitting the information to the remote station [5]. It can be an Autonomous Underwater Vehicle (AUV) which dives inside the water, sense the data and transfer the information to the remote station. Architecture of UWSN. dimensional UWSN architecture refers to a network where a group of SNs forms a cluster. Each cluster has a Cluster Head (CH). Each member of the cluster gathers the data and communicates it to the CH. After collecting data , the CH relays it to the sink. For the cluster of nodes, the network arrangement can be dynamic (star, mesh, or ring) depending Mostly, two types of sensing models used are boolean model and probabilistic model. In distance node's are not able to sense. In 2-Dimensional underwater scenario, sensing radius takes a Dimensional scenario, it takes a spherical shape. In probabilistic model, the sensing behaviour of nodes is certain it In UWSN, node mobility can be of two types. One is a mobile SN and the other is a static SN, but it can move with the help of mobile medium. Nodes equipped with movability are SNs are used in UWSN are first, SNs with scalar sensors temperature, omnidirectionality due to which the sensing locus forms a disk (2D) or a sphere (3D). And, the other kind of nodes are multimedia sensors rectional camera. These sensors have unidirectionality and has good sensing range (like pressure pressure etc.) etc.) have have on on the the application application UWSN Architecture. In this architecture, ѹed underwater in the form of clusters and are anchored at different depths. Different communication scenarios in this architecture communication of nodes, (ii) intracluster anchor node) communication, and (iii) sink communication. Acoustic, optical, are: are: (i) (i) intercluster intercluster The energy of the node is the central factor that affects all other performance parameters. @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Volume – 2 | Issue – 6 | Sep-Oct 2018 Oct 2018 Page: 851

3. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 iv. 4D-UWSN Architecture It is a combination of fixed UWSN and mobile UWSNs. The mobile UWSN consists of underwater vehicles (ROVs) to collect data from the anchor nodes and relay the data to the remote station. ROVs can be autonomous submersible robots, vehicles, ships, and even submarines. Each underwater sensor node can be autonomous in relaying the data directly to ROVs depending on how close that particular sensor node is to communication scenario between ROV and underwater sensor node depends on distance and data between them and either acoustic or radio can be used. As the transmission is to be directly relayed to ROV, the sensors which have large data and are close to ROVs can use radio links while the sensors which have small data to trans are far from ROV can use acoustics links [7, 8]. It is a combination of hus locating nodes underwater becomes much more crucial. Traditional positioning and localization systems do not work underwater. Therefore, underwater conditions dismantle the location of the nodes and the network topology which ultimately mation transmission unreliable. Requirement of Novel Protocols for UWSNs. In underwater communication, the medium of communication is water, unlike air as in terrestrial sensor networks. terrestrial sensor network communication d underwater. Mostly, acoustic signals are used for underwater communication over large distances, while radios are considered for short-distance, water surface communication. But radio signals transmit for long distances at extra low quires large antennas and high transmission power [1], which can decrease the overall network lifetime of UWSNs. Moreover, the propagation delay of acoustic communication compared to RF communication; hence many algorithms and protocols for terrestrial WSN cannot be adapted directly to UWSN. . Radio frequency (RF) communications are underwater communication due to medium effect on communication. Water absorbs much of the RF energy and hence only very short ommunication is allowable using RF [4]. Instead, acoustic communication is being used to transmit pulse signals and low fidelity information underwater due to its low bandwidth. Potential UWSN applications such as measuring the amount of pollution from a hing farm at the seabed [9] require transmitting lots of data. However, with such low frequencies, it requires a lot of time to send such dynamic data. Physical Damage to Equipment. The sensors used in underwater devices are susceptible to ter challenges, for example, algae collection on camera lens [10] and salt accumulation, decreasing the effectiveness of currents; thus locating nodes underwater becomes much more crucial. Traditional positioning and localization systems do not work underwater. Therefore, underwater conditions dismantle the location of the nodes and the network topology which ultimately makes the information transmission unreliable. Requirement of Novel Protocols for UWSNs In underwater communication, the medium of communication is water, unlike air as in terrestrial sensor networks. terrestrial sensor network communication protocols get void underwater. Mostly, acoustic signals are used for underwater communication over large distances, while radios are considered for short surface communication. But radio signals transmit for long distances at extra low frequencies, which requires large antennas and high transmission power [1], which can decrease the overall network lifetime of UWSNs. Moreover, the propagation delay of acoustic communication compared to RF communication; hence many algorithms and protocols for te cannot be adapted directly to UWSN. Low Data Rates. Radio frequency (RF) communications are underwater communication due to medium effect on communication. Water absorbs much of the RF energy and hence only very short range communication is allowable using RF [4]. Instead, acoustic communication is being used to transmit pulse signals and low information underwater due to its low bandwidth. Potential UWSN applications such as measuring the amount of pollution from a fishing farm at the seabed [9] require transmitting lots of data. However, with such low frequencies, it requires a lot of time to send such dynamic data. Physical Damage to Equipment used in underwater devices are susceptible to routine underwater challenges, for example, algae collection on camera lens [10] and salt accumulation, decreasing the effectiveness of sensors and so forth. Cost. Finally, the energy requirements and cost of UASNs are high compared to higher power and regular battery re techniques are quite costly. The amount of challenges in designing of UWSNs makes it challenges in designing of UWSNs makes it fixed UWSN and mobile UWSNs. The mobile UWSN consists of underwater vehicles (ROVs) to collect data from the anchor nodes and relay the data to the remote station. ROVs can be autonomous remotely remotely operative operative , ships, and even v. submarines. Each underwater sensor node can be autonomous in relaying the data directly to ROVs depending on how close that particular sensor node is to communication scenario between ROV and underwater sensor node depends on the distance and data between them and either acoustic or radio can be used. As the transmission is to be directly relayed to ROV, the sensors which have large data and are close to ROVs can use radio links while the sensors which have small data to transmit or are far from ROV can use acoustics links [7, the the ROV. ROV. The The Therefore, Therefore, 4.Challenges and Opportunities in UWSN UWSN is a promising new field and may help in exploring the unexplored world that lies underwater Still there are many challenges and opportunities that are as follows: i. Unpredictable Environment. conditions are extremely unpredictable. The anonymous high water pressure, unpredictable underwater activities, and uneven depths of the underwater surface make it dif design and deplѹ UWSNs. ii. Design and Deplѹment. unpredictable underwater environment, it is extremely difficult to deplѹ the network underwater which wirelessly. The current tethered technology allows constrained communication but it incurs significant maintenance, and device recovery to cope with volatile undersea conditions. iii. Unscalability. Traditional exploration relies on either a single high underwater device or a small-scale underwater network. Neither existing technology suitable for applications covering a large area. Enabling a scalable underwater sensor network technology is essential for exploring a huge underwater space. iv. Unreliable Information. Underwater nodes are in continuous motion due to the water in continuous motion due to the water Challenges and Opportunities in UWSN is is very very high high field and may help in lies underwater. Still there are many challenges and opportunities that vi. . Underwater Underwater not not effective effective in in conditions are extremely unpredictable. The anonymous high water pressure, unpredictable underwater activities, and uneven depths of the underwater surface make it difficult to . Due Due to to the the unpredictable underwater environment, it is ѹ the network underwater wirelessly. The current tethered technology allows constrained communication but it which works works reliably reliably and and cost of deplѹment, maintenance, and device recovery to cope with vii. . Traditional underwater underwater exploration relies on either a single high-cost scale underwater network. Neither existing technology is suitable for applications covering a large area. Enabling a scalable underwater sensor network technology is essential for exploring a viii. . Finally, the energy requirements and cost of UASNs are high compared to higher power and regular battery replenishing techniques are quite costly. The amount of . Underwater nodes are @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Volume – 2 | Issue – 6 | Sep-Oct 2018 Oct 2018 Page: 852

4. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 an interesting area for researchers to work on. With the advancement in sensor and wireless technologies, UWSNs have attracted a lot of researchers and have contributed signi to this field. However, the window is still wide open for upcoming research and opportunities. open for upcoming research and opportunities. an interesting area for researchers to work on. With the advancement in sensor and wireless technologies, UWSNs have attracted a lot of the total number of nodes. Less reachability refers to a situation where the number of no form a link are less; consequently the connectivity is poor. 5.Shadow Zones These are the spatial communication signal is practically void. These zones are quite common, especially when the area of coverage is very large and it ca areas where there is a high signal attenuation [10], [11]. Underwater is the medium where shadow zones can be expected because of having a wide area to cover. 6.Internodal Distance In UASN, nodes after initial depl lowered to a calculated depths. However, in doing so, increasing the distance between nodes reduces connectivity, whereas decreasing the node distance enhances the coverage overlap. Thus, there is a trade off between coverage and connectivity. However, a balance of both can achieved by keeping communication radius more than sensing radius. 6.Underwater Wireless Application Classification UWSN applications are rapidly gaining popularity for enabling advances in the area of ocean monitoring and observatory systems, deep sea surveillance, tracking of various entities of the aquatic environment, and unearthing resources [12]. UWSNs application in fields like offshore oil and gas extraction, oil spills, military surveillance and reconnaissance, mine detection, pollution monitoring, natural calamities like tsunami and hurricane forecast, coral reef and habitat monitoring of marine life, and fish farming. A comprehensive classification of potential UWSN applications is shown in Figure 2. potential UWSN applications is shown in Figure 2. the total number of nodes. Less reachability refers to a situation where the number of node pairs to form a link are less; consequently the connectivity ntributed significantly field. However, the window is still wide These communication signal is practically void. These zones are quite common, especially when the area of coverage is very large and it can be expected in areas where there is a high signal attenuation [10], [11]. Underwater is the medium where shadow zones can be expected because of having a wide are the spatial locations locations where where 5.Factors Affecting Underwater Connectivity There are several factors that affect the connectivity in any network. These factors are summarized in Fig. 10. Some of which are vividly explained in this section. 1.Sink Architecture If there are multiple sinks, then the nodes will have an alternative path to connect to the sink [11]. Further, the connectivity due to failure of any intermediate node in the connection link gets reduced. Thus, the connectivity gets enhanced. In Underwater communication, when the distance of coverage is very large, the multi sink architecture can provide very reliable connectivity. 2.Topology Proper choice of topology makes the connectivity more reliable. For example, in case star topology, there is only single hop communication, in case of mesh topology, multi-hop is possible and clustering topology is a combination of multimesh networks [9]. 3.Signal Propagation Loss The loss of connectivity is proportional to the loss of signal. The signal loss is due to signal traversing a significant distance, or due to absorption of particles or molecules in the medium, or due to weather conditions. 4.Reachability It is a sensitive metric that quantifies the ability of the network to communicate (especially in sparse networks) [8], [9].It is the fraction of node pairs in networks) [8], [9].It is the fraction of node pairs in Factors Affecting Underwater Connectivity There are several factors that affect the connectivity in summarized in Fig. 10. Some of which are vividly explained in this section. If there are multiple sinks, then the nodes will have an alternative path to connect to the sink [11]. Further, the probability probability failure of any intermediate of of loosing loosing In UASN, nodes after initial deplѹment are ulated depths. However, in doing so, increasing the distance between nodes reduces connectivity, whereas decreasing the node distance enhances the coverage overlap. Thus, off between coverage and connectivity. However, a balance of both can be achieved by keeping communication radius more node in the connection link gets reduced. Thus, the connectivity gets enhanced. In Underwater communication, when the distance of coverage is very large, the multi sink architecture can provide Proper choice of topology makes the connectivity more reliable. For example, in case star topology, there is only single hop communication, in case of Underwater Wireless fication Sensor Sensor Network Network hop is possible and clustering topology is a combination of multimesh UWSN applications are rapidly gaining popularity for enabling advances in the area of ocean monitoring and ems, deep sea surveillance, tracking of various entities of the aquatic environment, and unearthing resources [12]. UWSNs find their fields like offshore oil and gas extraction, oil spills, military surveillance and The loss of connectivity is proportional to the loss of signal. The signal loss is due to signal ficant distance, or due to absorption of particles or molecules in the medium, or due to weather conditions. ion, pollution monitoring, natural calamities like tsunami and hurricane forecast, coral reef and habitat monitoring of marine life, and fish farming. A comprehensive classification of fies the ability of the network to communicate (especially in sparse Figure 2: Various Applications of UWSN Figure 2: Various Applications of UWSN @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Volume – 2 | Issue – 6 | Sep-Oct 2018 Oct 2018 Page: 853

5. International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456 International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 7.CONCLUSION When deplѹed under the water, SNs can hardly be replaced or recharged in this harsh environment, and ambient energy harvesting combined with super capacitors is promising to be applied in UWSNs. Therefore, energy efficiency is fundamental when designing routing protocols for gathering sensory data and routing these data to the sink node. However, due to the complex environment, it is very challenging to transmit the collected data to the base station on the surface quickly and effectively. An energy ef routing protocol plays a vital role in data transmission. However, characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and high latency, it is difficult to build routing protocols for UWSNs. In future, we will propose a routing protocol which will enhance the lifetime of the network. REFERENCES 1.X. Feng, Z. Wang, G. Han, W. Qu and A. Chen, "Distributed Receiver-Oriented Multichannel MAC for Underwater Sensor Networks," in IEEE Access, vol. 6, pp. 11666 11675, 2018. 2.P. Gjanci, C. Petrioli, S. Basagni, C. A. Phillips, L. Bölöni and D. Turgut, "Path Finding for Maximum Value of Information in Multi Underwater Wireless Sensor Networks," in IEEE Transactions on Mobile Computing, vol. 1 pp. 404-418, 1 Feb. 2018. 3.H. Yang, Y. Zhou, Y. Hu, B. Wang and S. Kung, "Cross-Layer Design for Network Lifetime Maximization in Underwater Wireless Sensor Networks," 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018, pp. 1-6. 4.M. A. Yaqub, M. T. R. Khan, S. H. Ahmed and D. Kim, "Receiver-initiated dynamic duty cycle scheduling schemes for underwater wireless sensor networks," 2018 15th IEEE Annual Consumer Communications Consumer Communications Conference (CCNC), Las Vega 6. 5.R. Martin and S. Rajasekaran, "Data centric approach to analyzing security threats in Underwater Sensor Networks," OCEANS 2016 MTS/IEEE Monterey, Monterey, CA, 2016, pp. 1 6. 6.D. Das and P. M. Ameer, "Energy efficient geographic clustered multi underwater sensor networks," TENCON 2017 2017 IEEE Region 10 Conference, Penang, 2017, pp. 409-414. 7.M. Aslam et al., "Energy Efficient Cubical layered Path Planning Algorithm (EECPPA) for acoustic UWSNs," 2017 IEEE Pacific Rim C Communications, Computers Processing (PACRIM), Victoria, BC, 2017, pp. 1 6. 8.B. Zhang, Y. Wang, H. Wang, X. Guan and Z. Zhuang, "Tracking a Duty Underwater Vehicle by Underwater Wireless Sensor Networks," in IEEE Ac 18016-18032, 2017. 9.N. Javaid, S. Cheema, M. Akbar, N. Alrajeh, M. S. Alabed and N. Guizani, "Balanced Energy Consumption Based Adaptive Routing for IoT Enabling Underwater WSNs," in IEEE Access, vol. 5, pp. 10040-10051, 2017. 10.J. Kartha, A. Jabbar, A. Baburaj and L. Jacob, "Maximum lifetime routing in underwater sensor networks using mobile sink for delay applications," TENCON 2015 Region 10 Conference, Macao, 2015, pp. 1 11.G. Han, J. Jiang, N. Bao, L. Wan and M. Gui "Routing protocols for underwater wireless sensor networks," in IEEE Communications Magazine, vol. 53, no. 11, pp. 72-78, November 2015. 12.Z. Zhou, B. Yao, R. Xing, L. Shu and S. Bu, "E CARP: An Energy Efficient Routing Protocol for UWSNs in the Internet of Underwater Things," in IEEE Sensors Journal, vol. 16, no. 11, pp. 4072 4082, June1, 2016. Conference (CCNC), Las Vegas, NV, 2018, pp. 1- ed under the water, SNs can hardly be replaced or recharged in this harsh environment, and ambient energy harvesting combined with super- capacitors is promising to be applied in UWSNs. R. Martin and S. Rajasekaran, "Data centric approach to analyzing security threats in Underwater Sensor Networks," OCEANS 2016 MTS/IEEE Monterey, Monterey, CA, 2016, pp. 1- is fundamental when ting protocols for gathering sensory data and routing these data to the sink node. However, due to the complex environment, it is very challenging to transmit the collected data to the base station on the surface quickly and effectively. An energy efficient routing protocol plays a vital role in data transmission. However, characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and ficult to build routing protocols n future, we will propose a routing protocol which will enhance the lifetime of the D. Das and P. M. Ameer, "Energy efficient red multi-hop routing for underwater sensor networks," TENCON 2017 - 2017 IEEE Region 10 Conference, Penang, 2017, due due to to the the speci specific M. Aslam et al., "Energy Efficient Cubical layered Path Planning Algorithm (EECPPA) for acoustic UWSNs," 2017 IEEE Pacific Rim Conference on Communications, Computers Processing (PACRIM), Victoria, BC, 2017, pp. 1- and and Signal Signal B. Zhang, Y. Wang, H. Wang, X. Guan and Z. Zhuang, "Tracking a Duty-Cycled Autonomous Underwater Vehicle by Underwater Wireless Sensor Networks," in IEEE Access, vol. 5, pp. X. Feng, Z. Wang, G. Han, W. Qu and A. Chen, Oriented Adaptive Adaptive Multichannel MAC for Underwater Sensor vol. 6, pp. 11666- N. Javaid, S. Cheema, M. Akbar, N. Alrajeh, M. S. Alabed and N. Guizani, "Balanced Energy Consumption Based Adaptive Routing for IoT Enabling Underwater WSNs," in IEEE Access, 10051, 2017. P. Gjanci, C. Petrioli, S. Basagni, C. A. Phillips, L. Bölöni and D. Turgut, "Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks," in IEEE Transactions on Mobile Computing, vol. 17, no. 2, A. Jabbar, A. Baburaj and L. Jacob, "Maximum lifetime routing in underwater sensor networks using mobile sink for delay-tolerant applications," TENCON 2015 - 2015 IEEE Region 10 Conference, Macao, 2015, pp. 1-6. H. Yang, Y. Zhou, Y. Hu, B. Wang and S. Kung, Layer Design for Network Lifetime Maximization in Underwater Wireless Sensor Networks," 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, G. Han, J. Jiang, N. Bao, L. Wan and M. Guizani, "Routing protocols for underwater wireless sensor networks," in IEEE Communications Magazine, 78, November 2015. M. A. Yaqub, M. T. R. Khan, S. H. Ahmed and D. initiated dynamic duty cycle scheduling schemes for underwater wireless sensor networks," 2018 15th IEEE Annual Z. Zhou, B. Yao, R. Xing, L. Shu and S. Bu, "E- CARP: An Energy Efficient Routing Protocol for et of Underwater Things," in IEEE Sensors Journal, vol. 16, no. 11, pp. 4072- & & Networking Networking @ IJTSRD | Available Online @ www.ijtsrd.com www.ijtsrd.com | Volume – 2 | Issue – 6 | Sep-Oct 2018 Oct 2018 Page: 854