Research Article | Open Access
Sheeraz Ahmed, Malik Taimur Ali, Asma A. Alothman, Asif Nawaz, M. Shahzad, Ahmed Ali Shah, Awais Ahmad, M. Yousaf Ali Khan, Zeeshan Najam, Asma Shaheen, "EH-UWSN: Improved Cooperative Routing Scheme for UWSNs Using Energy Harvesting", Journal of Sensors, vol. 2020, Article ID 8888957, 18 pages, 2020. https://doi.org/10.1155/2020/8888957
EH-UWSN: Improved Cooperative Routing Scheme for UWSNs Using Energy Harvesting
The harsh testing environments of underwater scenarios make it extremely hard to plan a reasonable routing protocol for Underwater Sensor Networks (UWSNs). The main challenge in UWSNs is energy confinement. It is needed to plan an energy effective scheme which increases the life span of the network and also reduces the energy usage in data transfer from supplier to sink. In this research, we present the design of a routing protocol known as Energy Harvesting in UWSN (EH-UWSN). EH-UWSN is a compact, energy efficient, and high throughput routing protocol, in which we present utilization of energy gaining with coordinating transfer of data packets through relay nodes. Through Energy Harvesting, the nodes are capable to recharge their batteries from the outside surrounding with the ultimate objective to improve the time span of network and proceed data through cooperation, along with restricting energy usage. At the sink node, the mixing plan applied is centered on Signal-to-Noise Ratio Combination (SNRC). Outcomes of EH-UWSN procedure reveal good results in terms of usage of energy, throughput, and network life span in comparing with our previous Cooperative Routing Scheme for UWSNs (Co-UWSN). Simulation results show that EH-UWSN has consumed considerably lesser energy when compared with Co-UWSN along with extending network lifetime and higher throughput at the destination.
Communication in Radio Frequency (RF) is not conceivable in UWSN conditions because of fast attenuating and extremely restricted wave transmissions. This is the reason that acoustic communication is ideal for UWSN environments. Because of testing underwater conditions like extensive spread delay, the dynamic nature of work, and low transmission capacity, the one real issue is energy confinement. Constrained cell control is manageable for the information transmission. In tough underwater conditions, the exchange of sensor node cells is extremely difficult and expensive [1–3]. Figure 1 features a domain of subsurface information transmission condition.
Because of this unforgiving condition, the routing procedures designed for Terrestrial WSNs does not fit on UWSN conditions. The necessity of UWSNs is to configure isolated directing procedures for subsurface. These procedures are categorized according to their working methodologies on flooding based, cluster-based, multipath-based approaches, and miscellaneous protocols  as shown in Figure 2.
1.1. Routing Protocols for UWSN
(i)Flooding Base Procedures (a)Data is communicated in a particular region in this method, to all the sensor nodes. The favorable position of this plan is that it needs little data identified with the system. Additional energy used by communicating every packet to each node is the fundamental downside of flooding-based method (ii)Multipath-Based Protocols (a)In the multipath method, few ways are made from source to goal that expands the dependability of the system. The packet conveyance proportion is additionally expanded in this procedure (iii)Cluster-Based Procedures (a)Clusters are made via gathering sensor nodes in this approach. Here, these sensor nodes are partitioned in two kinds; Cluster-head sensors and Cluster part sensors. Cluster part sensors feel the information and later communicate information packets in the direction of its own particular cluster head. The cluster head gets information as of its own particular cluster nodes and is in charge of making a timetable of transmission for its member nodes . Information is accumulated as of the side of the sea, coastal borders for sea checking frameworks. UWSNs can be conveyed to perform cooperative observing assignments in sea condition  as in Figure 3
1.2. Main Challenges in UWSNs
Few hurdles are encountered in harsh underwater conditions. These hurdles are observed upon in two perspectives; Technical and Research challenges, for useful operation of underwater sensor node. A fraction of the considerable difficulties is discussing beneath : (i)Difficult to galvanize cells and have extremely restricted cells power(ii)Accessible bandwidth is limited(iii)Channel is influenced by multipath waning(iv)Greater end-to-end delay when contrasted with TWSN(v)Error ratios of bits are high-level(vi)Astrophysical energy cannot be utilized in underwater(vii)Deterioration and Snarling might trigger to come up with brief underwater sensor(viii)Localizations(ix)Data extractions
Some prominent problem faced in UWSNs is cell control constriction, its empowering and substitution. Due to challenging underwater condition, that one is extraordinarily problematic and costly to recover or replaced sensor node cells. Based on definite problems, the supervision and organization of UWSN routing schemes is a key test for investigators .
2. Literature Review
2.1. Related Work on Routing in UWSN
In articles , authors argue that because of huge spread delay and data transmission impairments make terrestrial sensor system routing protocols unsatisfactory for UWSNs. Thinking the UWSN condition, enormous exertion has been made to outline proficient routing protocols for UWSN transmission. These methods are clustered in 04 classifications, i.e., Multipath methods, Flooding methods, Cluster, and different methods. In this article, depictions of the routing method outline for UWSN are examined in brief. Researchers in articles  argue that because of testing qualities of UWSN conditions, it is extremely tough to offer efficient routing administration in UWSN. The radios flag not operate properly in the subsurface state that is why auditory signals are used. Auditory transmission has brought down transfer speed and extended spread delay when compared with radio signals. Alongside, network topology in UWSNs in natures is lively and sensors traffic latently. Now the recommended scheme is identified as (Depth-based Routing) DBR to confront the matter of limitation ahead to several extent. Depth-based routing never need information of sensor nodes of a full-dimensional area. It needs fair zone intensity data that can be efficiently skilled by pushing a small value insight sensor to every subsurface node.
Investigators in article  tell us that a standout among the utmost crucial problem in UWSNs is energy hindrance. As of challenging underwater situation, the charging and substitution of sensors node cells is extraordinarily hard and costly. The prearrangement planned is to sketch an energy-efficient routing protocol known as Energy Efficient DBR (EEDBR) to take on the attention of the supposed difficulty up to a certain amount in UWSN. The planned protocol establishes the perspicacity of the sensor nodes through by his enduring energy, to shape the life period of the systems. Investigators in paper  evaluate various routing protocols and then centered on constraint systems, minimizations of energy, and determine the standing time in UWSN. Every routing protocol has various aims as a reduction in accomplishment of strength, energy consumption etc. That article for the maximum parts focuses on the features and hurdles encountered in the plan of routing protocols for UWSN.
Professional in article  practice that in complex subsurface condition, the important problem is the diversity in arranged topology, risky errors frequency, and other important energy use for the communication of information. Development with these number of challenges, there are several genuine main points of UWSN, suppose, subsurface administrations, oil inquiries, and a some catastrophes management problems Adaptive Mobility of Courier Nodes in Threshold Optimized DBR (AMCTD) routing approach has scheduled to achieve much important system lifetime founded on sensor perceptiveness, reducing the use of energy especially among the stability time frame. The adaptable advancement of courier nodes keeps the system throughputs in the more states of approach. In article  recommended routing protocol in light of Forwarding Function (FF) for UWSN called improves AMCTD. Differing and the current intricacy based routing procedures; established protocol mismanages the width of the system for time fundamental information. To overcome ways difficulty, spread latency, and overflowing, taking time is determined and uses routing dimensions that comprised a restraint-free signal-to-noise ratio, signal quality index, etc. Sign of FF process increases the lifetime of a system and reduces transmission adversity. The communication in delay is a fragile application to accept suspension is reduced utilizing ideal transmission by sensors utilized as a sink. Likewise, the diversity top to bottom edge level, the fundamental failure of information in delay-sensitive products is decreased by expanding the quantity of neighbors suitable for the communication.
Researchers in  say that to decrease the problems of more important disconnection, the DSRP is needed. The planned scheme known as Delay-Sensitive EEDBR (DSEEDBR) and flexibility base level getting border esteemed to empower the routing in the opinion of its profundity to reduce the three tactics are combined to design FF. In appeal to imagine the communication misfortunes and gained signal pace, ideal Weight Function (WF) is offered in these proposals. Furthermore, to confront the problem of deferral, it wants well ahead to restrict the communication postponement in such area, whereas sensors are placed in minimal profundity. In this paper, various postponement sensitive plans are compared, and each other. In Delay-Sensitive Depth-Based Routing, Weight work and Fi are used for properly forwarder selection. In Delay-Sensitive Depth-Based Routing, to assess Delay-sensitive Holding time attend dTH. The substantial explanation for high-level generating delays is minimal profundity transmissions. The decision to-ending delay is lessened by utilizing adaptable transmission sensors triggers marginally reduced the throughput of the system. Investigators in  planned Dual-Sink Efficient and Balanced Energy consumption Technique (DSEBET) for UASNs. In Audio sensor networks, unite the system life cycle crushes as of limited energy resource. The actual problem is to adapt energy in the minimum system life cycle. In this manner, to develop the system life cycle, the consumption of energy should be modified. The planned Dual sink efficient and balanced energy utilization procedure plot reduces the issue of high energy used and expanded the time of the system for a long separation. In DSEBET, edges amongst the sensors are prepared established on his little split hand-off node and are picked for data transmissions.
Investigators in  planned resistance concerned and efficient routing protocols for UWSN. Established on a developed up path from end to end, the sender has been selected for communication of data packet. According to this method, the empty spaces can be resolved off using the planned routing protocols. For reliable transmission, interfering within the redirect is also measured in routing metrics among the choosing of transmitting nodes. The planned routing practices select nearby nodes as a following sender from supplier to target, so collapse possibility can be reduced at assemble layer. The shot of channel obstruction is a minimum. To improve the unswerving quality of a system, it is essential to keep a strategic distance from crash in thick sensors region. The recommended procedures improve the dependability of the system based on keeping a strategic distance from the void gap as a following forwarder strategy by using some function. In late research, the important progress in the area of UWSN has being achieved . Some of routing procedures is set up to understand the problems that appeared in UWSN. In this program, the target is mainly centered to understand the operating requirements of such routing strategies. Three inquiry approaches are planned to do so; collaboration-based routing, limitation based, and clustering based. The examination depends on the classes in that routing protocols lie. Numerous routing protocol centers on energy productivity, security of the system, and time proficiency to diminish the postponement in time and increment the life cycle of the system. Routing protocols are ordered in various classifications in view of its profundity, bunching, restriction, and participation routing protocols. The detailed diagram for information transmission on preferences and imperfections of various protocols are given.
2.2. Related Work on Cooperation in WSN
Investigators in  recommended that in acceptable WSN state, energy competent strategy is used as a part of the quantity of sensor and degenerative nodes. Based on data gathering node, various formats are used as the Numbers of Inputs to Numbers of generate and Numbers of Inputs to One Output. In planned protocols, useful energy plan for Cooperative-Multiple-in, Multiple-Output is used, whereas inaccuracy is corrected by using LDPC. The length of Low thickness equality check depends on upon the extent of the information and fault testing bit; Thus, the amount of Low thickness equality check code altered with the amount of information and fairness bit. Experts in  said that in an energy-controlled system, assistance by using only transferal is farther fundamental as well as effective communication. For the high parts focus to study as well as choose a hand-off allowing least energy with regulate transmissions. For acceptable transmissions, relay determines his basic needed power with a particular completion target to manage cooperation. Now the greatest one hand-off is selected amid the whole to reduce the power usage. The outcome of transmission depends on the adopted way with small overheads. In the node determination process with an energy control strategy, the MAC architectures are utilized. The general energy utilization by utilizing the said architecture is limited. The said architecture has been deemed as a cross-layer plan for specific helpful interaction in WSN.
In  proposed work EH-WSN technique allowing the advantage of beneficial collaborations as well as handover choice in aspect of small energy usage. In the said architecture, a protocol is intended to expand the node productivity regarding energy by utilizing energy harvesting. The procedure is evaluated in two phases, in the first phase, the useful transmission is evaluated and then the energy of all nodes is figured. That plan describes a modest and helpful system for energy harvesting-WSNs with involvement and clearly connected in actual cases. To get energy fruitful collaboration base communications, it has also synchronized with different procedures. In article  planned to find extraordinary capacity by using a new kind of code to reshape software development, known as IoT. Since of cruel channel features, data collecting is yet challenges in EH-WSNs since of high delay, energy loss, and retransmissions. Data is communicated suitably by uplifting programming to get reliable communications. Reliability improved acceptable communication plot is planned to improve the unwavering condition of the system in multihop useful transmission not including reducing system life cycle. In WSN, devices are put at several places, so every node manage varied packet, so rough energy consumption occurred in the system. To skillfully use the lingering energy, consumption is supported by the prerequisites. Minimal power utilization is incorporated to maintain an extended system life cycle. Similarly, high power consumption is embraced to expand the unswerving condition of the system.
Analysts in  use that organization of WSNs give an assortment of administrations, as ecological checking, military administrations, and so on. The data communicated by WSNs is used for different functions in various parts. Some fundamental problems such as security, organized topology, as well as transmission protocols, take place in the delivery of WSN. Unique protocols are utilized by the prerequisite of the use, suchlike, certification, eliminate, numbers of packet transferred among specific time frames. In paper , planned work a Wireless Powered Cooperative Network (WPCN) as well as the planned design contains of single supplier to target fusing and getting several Decoding Functions (DFs) and convert transfer. This strategy suggested Energy Threshold-based Multi-Relay Selection (ETMRS) for WPCN. The transmissions are forwarded randomly and are recognized by only his profundity information for turning amid Energy and Data Forwarding collecting mode. The restricted battery resource of all sensors nodes, the charging or release of nodes occurs which ETMRS needed design over blended Nakagami-m and Rayleigh blurring channels. The plan planned to accomplish close ideal execution with lessened computational unpredictability. On the off chance that the energy is not as far as the limit stage, so that nodes carry out energy collecting. The planned technique has multirelay’s alternative to beat the only one transfer determination and regular energy edge plot.
2.3. Related Work on Cooperation in UWSN
In the article , the authors planned a technique in which they extended the competence and steady excellence of the system by utilizing the sink flexibility as well as useful routing. Various protocols are designed to achieve involvement with a particular ending objective to improve connectivity by analyzing physical and MAC layer perspectives. The planned arrangements mostly concentrate to examine arranged layers with sink portability. The forwarding node is selected centered on residual energy and its intricacy data. Sink mobility by group occurrence information through several sensors in particular increments the efficacy of the system. The planned protocol operates in several phases, data acquisition phase, organize the use phase, control base data identifying, and routing phase. In the learning stage, the sensors share their attachment, residual energy, and profundity data. Each node determines his active nearest sensor to freshen profundity rim measure in establish inauguration stage. In routing and edge stage, the node sense limits level and forwards the information in like manner within his reach with agreeable way. Researchers in the article  custom these to look out of numerous issues that happened in UWSN. Better routing plan is needed for useful information delivery. That article planned an increased affable strategy to create the life cycle and unswerving value of the UWSN. The planned design gets involvement on organize tier within current nonacceptable routing strategy, DBR, to enhance the accuracy, as well as throughputs. The purpose of the hand-off node depends on his complexity and information is delivered as of supplier to target effectively by developing a transmission sensor.
In article  scholars found such the hard underwater situation for the reason that of distorting and obvious sounds makes it difficult to do error free communication of data. The possibility of move depends on node complexity and his extra power. Expert in  make usage of that to improve the transmission feature; acceptable transmission is obtained in UWSN by utilizing transferal sensors node. To enhance the implementation of the system, they planned a useful strategy recognized as the Investigative method for Reliabilities with Collaboration for UWSN (ARCUN). The planned protocol holds high-level output and power capable routing strategy for UWSN. Transfer decided through a grouping of hand-off sensors node, determine the split, as well as SNR proportion of the underwater network. Portion delivery proportion and unswerving feature of the system increased by adapting load up, using acceptable hand over-off sensors. The planned design works cooperatively and SNR for delay-delicate product to improve the parcel conveyance ratios and reliability period of the system. In communication of data except cooperation indicates data is communicated by using immediate connection from supplier to target. Therefore, in case that network is affected because of hard condition, information cannot find well at target. Thus, involvement by utilizing hand-off nodes is essential to build up the unwavering property and parcel conveyance ratios for UWSN. The amount of neighbor sensors improves, while immensity variety occurred in sensor nodes, in this way reducing basic data catastrophe.
In the article , Scholars utilize the two main problems exist; radio wave cannot perform very well in underwater conditions, and the next one is the sound transmission is modest. The planned strategy centers across region-based cooperation. The field is split in many sections and later that cooperation amid sensor arises. The planned architecture called EACE achieved extensive system duration and a smaller amount of use of energy with involvement amid sensors. Expert in  utilize that dependability’s is the main important issues to improve the overall implementation of UWSN. Uproarious condition and bad network excellence decreasing the reliability and impact the system implementation by affecting the reliability of data. Useful routing in UWSN improves the unwavering condition as well as the reliability of the data. The planned design known as IACR consists of two transmission nodes, and one top node is selected amongst the available sensors through supplier to sink node for the transfer of data. The choice of ace node depends on some condition such as having low profundity, more noteworthy remaining energy, and lies out of the edge level. Form on profundity edge level of supplier and ace node, two hand-off sensors are chosen for the reason of retransmission.
In the article , Scholars proposed such Cooperative conditions increase the duration of the system in analyzing conditions. The nearest sensor is used for the communication of data usefully as transfers’ sensor. The organized design known as Co-UWSN, which develops the system lifetime by increasing unwavering value, energy efficiency, and increasing throughputs in UWSN. To defeat obscuring, satisfying various multiplicities is produced. A decrease in the use of energy and expanding the system lifetime is done by utilizing helpful plan and SNR. Choosing of hand-off node considering network quality’s and split amid the nearest nodes results in effective information packet transfer. Failure of data packet is reduced by occurring different form inner and outside limits amount. The system reliability period and loads adapting are done by using perfect weights computation and useful condition. Researchers in  argue that limitation is one of the major viewpoints in UWSNs. The thing is important to get the correct place for various applications of sensor nodes. Be that as it may, GPS does not perform admirably in UWSN condition, therefore which is extremely hard to place a node at the correct place when contrasted with earthbound systems. To unravel the problem of restriction upward to various degrees, two routing protocols are planned and to enhance the signal amongst supplier and goal, Amplify-and-Forward instrument is utilized.
Specialists in  address to plan protocols for UWSN to improve the execution known as SPARCO. In planned design, to lessen energy utilization, every node is related along through one all directions receiving wire and quantity of helpful sensors forwards information by getting the benefit of spatial decent variety. Ways hurdles introduce in the network are lessened by utilizing both multijump and single-bounce plots in information sending. The planned architecture does better with respect to end-to-end delays; arrange life cycle and energy utilization relative to nonhelpful routing protocol (iAMCTD). In the article , researchers planned to utilize physical layer participation that makes sure energy effectiveness. To spare energy, all directions reception apparatus is utilized to forwards information helpfully for the target. On physical layer different participation and at arrange layer bounce to jump routing diminishing the routing energy because of consolidated advancement.
DBR as well as EEDBR is capable of plans but it may only some problems in adapting of loads up in sensor taking lesser profundity. Huge energy is consumed by that lesser profundity sensor while transferring data that produce extent gap in a system. This gap is effectively established for load administration including the active sensors nodes. If the profundity rises, the use of energy amidst communication is moreover improved.
In the majority of applications, the communication depends upon the battery control. So, in this concentrate, wherever lesser battery control is available, involvement communications are perfect for the transfer of data. In this cooperation, sensors convey information by presenting those holdings to each other. Now, while a collecting of elements are met, all collectively with a definite ending target to make a common goal called cooperation’s. At that time as information is transferred through the source to the recipient using outsiders is communications utilizing involvement. The system consists of a battery-control sensor.
Source nodes transfer its data to the receiver as well as the hand-off sensor. The hand-off node improves the gained signal to final close as an instant copy repeat of the delivered data. Essential idea is to transfer copies of data on various methods. That is moreover called as useful mixed assortment. That cooperatives arrangement increases the ability as well as the unswerving condition of the system. Remain such as its might, in the mean but here is a problem of providing further weight on transmission node. It reduces the lifetime of the hand-off node, which in a circuitous way reduces the system lifetime. Presently a day, another procedure identified as Energy Harvesting is used as a part of a larger portion of study territories. In this examination, we require to introduce EH make in UWSN to watchful of the thought problem.
4. Flow-Chart and Methodology of EH-UWSN
The planned view towards the system is instantly simplified over the AST. In Figure 4, the accompanying flow diagram on the starting all one of the sensors is explained. Improper forwarding of 250 sensors underwater by five falls on the water exterior in an area of . Every sensor will start to get its nearest sensor. That is get the sensor to identify the greatest choice of nearest that be able to select for information transmission depend on leftover energy as well as expected amount operation. That is necessary on the ground as all nodes which is covered by various sensor which is varied by several sensor for the reason that of nodes stiffness. In the concentrated-on region, sensors are spread randomly.
Thenceforth assessment of the nearest sensor, in consequent phase, we determine the RE of the significant numbers of sensors conveyed. There we split the sensor on rim energy stage 1 and 2. If the residual energy of the node is more important or the same to edge energy level 1, at these time that nodes be picked as transmission nodes. In the result such the Residual energy is non as considerably as limit energy point 1, at such time hand-off node again process its Residual energy, if the Residual energy is much important then rim stage 2 and not as enough as rim stage 1, so this gets the ability to utilize as distinctive sensors nodes. As the possibility this, if residual energy is not as significant as rim stage 2 so it starts its EH to improve energy levels.
In the arouse of accumulating energy, one more time examine the Residual energy point of the nodes. At the possibility that at this time the energy point is further eminent or equal to utmost stage 1, at that time that nodes can be taken as a hand-off nodes for delivering data through supplier to target. If again the nodes do not improve sufficient energy to achieve rim stage 1 form, so it can be used as a normal sensor node.
Thenceforth to examine the residual energy of all the delivered sensors and doing EH, in the resulting phase, two sensors exist taken as transmission sensors that accomplish the weight job conditions. Currently form on weight works conditions, two transmission paths are selected from supplier to target shown in Figure 5. Currently, useful form has been produced from supplier to target.
With the determinedness of relay sensor nodes and cooperation level, the consequent phase is to figure out the residual energy of the supplier and that of the transmission sensor node. A possibility such the Residual energy of selected sensor is much important than the supplier nodes, in this time transmission nodes paths are carried afterward as the transfer of data through the supplier to target. A possibility that the Residual energy of the transmission sensor is not as considerable as the Residual energy of supplier nodes, in this time, the immediate way is take afterward for the transfer of information as a supplier to target.
Now the arouse of working involvement, routing phase fulfill the transfer of information tossed chosen channels from starting position (sender) to final position (receiver). The target nodes select the safest one way accessible including everything, as well as get information through that great way, and leftover path/paths are discords.
5. EH-UWSN Planned Protocol
In this section, we represent our approximate energy useful and collaboration based protocols EH-UWSNs that assurances to improve the Networks Lifetime, Packet Decreased Ratios of the systems, and reduced energy utilize with sensor.
5.1. Absorption and Scattering Models
Dual important causes of contraction in underwater conditions are scrambling and absorption problems. In propagating, the electromagnetics signal is deflected faraway through its single producing, and in integration, the electromagnetics signal energy is altered on opening with one formation and into the next form like warmness or matter. Subsequently,
Here, as well as describes to absorption and dispersing individually, expected in m-1, and is the wavelengths of signal in (nm). Using the productive of weakening’s Beer’s Principle determines the constriction of an acoustics signal for a splitting is presented by : wherever is a normalizing’s constant. The normalization esteems is not negative esteems, depend over the occurrence to accomplish the modification exactly equal to 1. is coproficient of decreasing, is a partition.
5.2. Ambient Noise
Surrounding commotion is considered as one of the most significant determinants in aquatic acoustic conditions. Commotions is basically the relationship among the quantity of data concerned with sea air conditions, oceanic conditions, air speed, and effects of aquatic biology. The four essential parameters showing the distinct great level of surroundings noises are turbulence noise (NLtb), shipping noise (NLsh), wave noise (NLwv), and thermal noise (NLth). The Power Spectral Density (PSD) of these noises are modelled in dB re μ Pa per Hz as a frequency function in kilo Hz and total noise level is the cumulative sum of these noises represented by NL : where log f, (s -0.5) +26 log f–60 log (), (w –0.5) +20 log f–40 log (), and log f, where in kHz, is wind speed (m/s), and as the shipping factor which lies between 0 and 1 for low and high activities, respectively.
5.3. Signal-to-Noise Ratio (SNR)
The signal-to-noise ratio of an underwater acoustics signals on reception sides be able to compute in dB by asdic calculation  as keep: here, NL is ambient noise point in sea (dB), TL is transmissions failure (dB), DI is the directivity index and is put to zero, and SL is of transmission (dB) is provided by
here, Pit is the transmissions power intensities.
In shallows sea, the Intensity, Pit is provided in watt/m2 such as
In deep-sea waters, , is presented in watts/m2 such as here, is the transferred power (watts) and is the profundity (m).
5.4. Network Topology
Networks limits, energy use, as well as the unwavering condition of a system depend over organize topologies. The best range of a sensor node shall not sufficient to cover the whole structure, thus multihop communication is utilized. Information get through the supplier node at base station nodes is accrued. It might study such a sink node has not any energy requirements which might tell by any of the sensors with no collaborations. Systems is separated about several layer bases on profundities as well as prepared of different sensor.
The less intensity sensor deliver data to a greater intensity sensor then the process going forwards of tills the data goes to on the surface of the sea. The transmission sensors are impelled nodes, then that should a dual responsibility of conveying his specific data and transmitting of neighbor sensor. In Figure 6, if here would be an existence of own data communication, the supplier nodes transmit data roll two hand-off sensor in a collaborations method, on the ground that if hand-off sensor shall not available or might gone, thus here would be other hand-off and a direct linking available as the data exchanging.
5.5. Initialization Phase
Three distinctive tasks have been accomplished in that stage. Each sensors have information concerning his neighbor, base station nodes on the sea rim is identified, then each possible way about several base station node is measured. Sensors connect a packet, which includes information of the nodes as his profundities, nodes identifier, and energy position. That packet was made by the nearest nodes and uses this as further communications. The base station node presents at the water edge delivers a Hello packet for his entire linked sensor. Using big packet transferred, through in the assumed transfer enhance, every node separate his nearest node and freely kept up a line of the nearest node under profundities bound to identify the greatest deliver nodes for which are data transferred; that node figures his weights using the way specified beneath  as in equation (8); here, SNR(dSiR1,f), SNR(dSiR2,f), SNR(dSiD1,f) remain the SNR of the equivalent connections through Si to Di individually, R.E is known residual energy of the equal sensor; dSiR1, dSiR2, and dSiDi exist the distance through the equal supplier to its conveys as well as direct target correspondingly.
5.6. Cooperation Phase
The two-stage method in that entire information is transferred with no overlap from the supplier to the wanted goal. In the first stage, the supplier Si conveys the data to pair transfers R1 and R2 as well as target D all the while, wherever in stage two, the transfers R1 and R2 transfer information to goal D. The separations amid the supplier nodes and the transfer sensors are d1 and d2, as well as the separation amid the supplier node then the goal is d3.In stage 1, the data got at hand-off sensors R1 and R2 as well as goal D through supplier is composed as . whereas the transferred power at the supplier is P1, XSi is the sign of transferred data through one of the th supplier nodes Si, hSiR1, hSiR2, and hSiDi are the feature of WM through supplier Si to R1, R2 and through supplier Si to Di individually. The coefficient is modelled as a complex Gaussian variable. The variation of the channel is shown such as;
Whereas dij represents the distances amid dual sensors and , failure arises due to transmission element , and is a continual that value depends on environments of propagations.
In the second stage, the relays decode as well as forwards sign with power P2 to the goal. The signals got on goal in the second stage are shown as .
is equal to in case the image got by Relays are accurately gotten, generally , is the signals got by “” nodes in the wake of going through S-R joins, that may be equal to , are blurred as well as hR1Di, hR2Di is the channels effective through , to Di individually. Goal nodes Di consolidates the signals got clearly through supplier Si nodes then through Ri node and utilizes the FRC system. The overall power transferred is by the ending target this .
5.7. Relay Operation
Several useful ideas have been formed up till that stage. Adopted space-time coded for acceptable structures were proposed in Selective participation plot while of late , wherever a single transfers or different transfer are select to cooperate on data transferred. Various transfers involvement, dual transfer away of a get-together of transfer is facilitated by the communication method, whereas the purpose of transfer depends on independent information or channels addition or energy levels of the transfer.
In UWSN, the hurdles at several phases are much important when compared with earth bound WSN communication. Thus, by a particular end target to find good quality information at the target, we require to choose two separate methods through supplier to target utilizing useful transfers and between the amounts of available transfer. The choice of and is performed created on the selection conditions. The determination condition depends on Distances, Channel conditions, as well as Energy levels of transfer. These two sensors are named founded on (1)Minimum separation from source to goal(2)Better channel selection(3)Maximum Energy utilization of transfers
When the determinations of two transfers, nodes are selected which are best for collecting of information. Currently, a supplier node makes two copies of the information, as well as transmits that copy to the two selected transfer and all along. Following to obtaining that data by hand-off sensor and , first sending for the target , initial decode at , as well as then afterward sent to the target.
5.8. Utility of Decode and Forward Technique
In the result, such routing protocols utilize just one transfers useful communication, on this time its inclined to Amplify and Forward technique. As on that position, only just one transfers link is reachable through supplier to target as well as the whole transmissions is done by using that only hand-off. Beside that rules, maintaining in care the ending target to achieve clearer data on the target, the Amplify and Forward technique is used. Currently in our investigation, we planned to choose these two transfer that get the best channel choice, thus minimum weakening’s is occurring, as well as getting two ways (S-R1-D and S-R2-D), thus the requirement of improvement is minimum in that position.
The planned design requires creating data much reliable, so it primarily interprets the data at transfer and and later this delivered to the target . The unraveling on and is completed by using similar interpreting strategies. In the arouse of unraveling of information on and , the target gets dual duplicates of information. Currently at target, those dual duplicates of information are recreated to his distinctive format as well as then verify if each copy of information between these two is corrupted, in this time the improved one is utilized and another is discord.
5.9. Channel Detailing
With stabilizing the noise to one, and accept measure accomplishing codes on every link. , , and are speaking to the channels getting. The base needed transmissions energy to assist a data ratio (bits per image) through the supplier to the goal must fulfill :
At another side, nodes and requires to decode the supplier signal effectively, the transfer power must fulfill
This converts to
5.10. Destination Mechanism
Different approaches have been used on target to enhance the signals found on several links. The planned method uses the SNRC process as consolidating systems. In Service node routing, complex technique is opposite to containing the oncoming signals, just suppose over the Service node routing complex of signals gained through several approaches with everyone. Assuming that here would happen an existence of two-transfers sensor, Service node routing complex can be communicated as whereas speak to mixed output of signal found on target node . SNRC1, SNRC2, and SNRC3 remain the SNRs of various threesome ways took after through supplier to goal . Those examinations of SNRs depend on various form, exist: (i)Assuming that the goal of one connection is more prominent than one and the staying dual connections are short of what one, at that point the signals got at initial connection is chosen as well as staying dual are discord(ii)If SNRs of whole the threesome ways are more noteworthy then one, then pick this one signal that channel possess greatest SNRs amid the threesome ways(iii)Assuming that SNRs of every one of the threesome ways are similar, then relies upon goal nodes and which one signal they need and staying dual are discord(iv)Assuming that every one of the three ways SNRs are short of what one, then the goal node friction every one of them and illuminate supplier node to resends the information
5.11. Modes of Operation
In Figure 7, each transfer square, we meant by , that is moreover separated onto two schedules opening through measures as far as lengths . At the initial schedule opening, the supplier transfers his signal to each nearest transfer. If the getting hand-off working in the EH method, the acquired signal is delivered to the energy beneficiaries to variation around the direct current to charge the battery. Likewise, in the event receiving transferal working in the data forward (IF) technique, the acquired signal is delivered over the information accumulator to decipher the information delivered by the supplier nodes. For using a deciphering set, each transmits that at work on IF mode can convert the information efficiently.
In the 2nd schedule opening, the unraveling group each other delivered the information over the target, acquired by transfer that fall in deciphering, at that time hand-off consumed some portion of accumulated energy through his batteries. But transfers that are not getting part in deciphering set remain safely among the 2nd opening. The time summary of IF and EH are shown in Figure 7 .
There afterward use subscript-S as well as subscript-D to specify the supplier and target separately. Transfer sensors are signified by and . Amid the accessible blurring model, Rician blurring will be the very well-known one to characterize the channel blurring of S-R joins. The for the most part inspiration driving this is observable pathway (LOS), in light of the fact that nowadays up and coming remote energy exchange procedure must be worked by in a generally shortly communications run. Rician circulation is approximatively by moreover flexible Nakagami-m blurring model. Altogether embrace an uneven situation for the blurring exists in supplier-to-transfer connections and hand-off to-goal joins. In particular, the S-R1 and S-R2 joins are expected to the subjects to Nakagami-m blurring with blurring seriousness parameter mu and normal power pick up λSR1 and λSR2, although R1-D and R2-D connect experiences Rayleigh blurring with normal power pick up λR1D and λR2D as the separation amid that is considerably moreover.
Give Pt a chance to indicate the supplier transfer power as well as X spoke to the transferred image with .
The acquired motion by the transfer node among the initial accessibility is presented by ,
Here, and are the coefficients of channel amidst and and and separately, denote the AWGN with zero signify and alter NL by the accumulator sides.
About whenever the hand-off node operates in EH mode, the signal acquired at hand-off node is delivered to his energy collectors, which alter across the direct current to charge the battery. The amount of HE at Relay node among the initial scheduling opening can be communicated as ,
Here, is the energy converting efficiencies and and is the channel power get amid source as well as relay sensor.
In equation (17), the commotions manage is minimal usually as well as underside the flexibility of energy accumulator, thus we remember the measurement of energy acquired through noise. Likewise, in case and needs to separate data in the initial schedule vacancy, it would be collected zero energy.
The current interpreting set is communicated to with . In 2nd accessibility, the two-transfer sensors transmit the supplier information equally for the goal running in interpreting set. By realizing the bar framing method .
The conveyed signal by , is shown by,
Here, and are the weight of relays nodes and and and is the transmitting power of and individually.
The optimum weight of and that increases the whole end-to-end SNRs would be defined as , as well as , here and is the complicated channel coefficient amid R1-D and R2-D individually.
We represent and for ease.
6. Simulation, Results, and Discussion
The execution as well as the viability of the planned protocols Energy harvesting-UWSNs is assessed by contrasting it and Co-UWSN protocol. System measurements utilized will , by 250 sensors is haphazardly put in underwater giving nodes energy of 0.07 J as shown in Table 1.
6.1. Network Life Cycle
System lifetime is described as the time for that the system is energetic or active. In Figure 8, the verticals nodes say to lifetime of a system and the uniform pivot says to radius. The analysis in Table 2 shows such the usual assessment of Co-UWSNs is more important when contrasting with EH-UWSNs. The reason by that is the fundamental lifetime organize assessment of Co-UWSN with span 100(m) to 400(m) is significantly moreover important while contrasting with the EH-UWSNs scheme. On range 400(m), dual of the policies get level by value all around. On the possibility such, we consider on the plot of Co-UWSNs design, it absolutely determines such its system lifetime esteem not quickly while move increment through 100 (m) to 1000 (m). In EH-UWSNs architecture, plot demonstrates that it is fundamental with a smaller system lifetime an encouragement as compare by Co-UWSNs. In analysis of the two plans, the Co-UWSNs consider stage by stage reduces while the sweeping increases, whereas the plot of Energy harvesting-UWSNs architecture shows energy collecting on several concentrates in Figure 8. About whenever the range is equal to 500(m), than Energy harvesting-UWSNs plot had small system life period esteems, thus its starts collecting energy unto some level with sweep 500(m) to 600(m) remember the final target to increase the life period of a system. Energy harvesting is remake as shown in the figure, while the energy level decreases through characterizes rim esteem. Relationship of dual the strategies proves such the typical assessment of Co-UWSNs plot is most noteworthy from EH-UWSN architecture; however, the overall implementation of EH-UWSNs is better to Co-UWSNs.
6.2. Number of Packets Dropped
Numbers of packet discarded talking for this how many numbers of packets dropped among transfer through source to destination. In Figure 9, the upright nodes talking to the numbers of packets discarded as well as the evens nodes speaking toward the sweep. In the relationship of dual the ideas, the plots clearly show such on initial at sweeps 100(m), Co-UWSNs discarded large numbers of packets while compared to Energy harvesting-UWSNs. In Table 3, in span 100(m) to 400(m), the packet discarded in Co-UWSNs is large whenever compared by Energy harvesting-UWSNs. On range 100(m), the packet dropped in Co-UWSNs is 6.35e4 as well as on the same time the packet discarded in Energy harvesting-UWSNs plot is 2.2e4. It means such in Energy harvesting-UWSNs architecture, most important numbers of the parcel is gained on goal as well as a small number of packets is discarded as compare to Co-UWSNs plot. The plot of Co-UWSN architecture rots bit by bit while the period increases with 100(m) to 1000(m).
The EH-UWSN architecture demonstrates some types at several concentrates in his plot. With sweep 500(m) to 600(m), the packets discarded esteems increases. In that section, Energy harvesting-UWSNs plot basically collect energy, by the target this is the cause the packet discarded esteems increases in that phase. As the result of collecting energy, with 600(m) to 700(m), the EH-UWSN plot once more reduces the packet discard value. That type in EH-UWSNs plot is arrived on modified concentrates. The typical parcel discard assessment of EH-UWSNs architecture is better to Co-UWSN plot.
6.3. Energy Consumption
Energy use basically shows the use of energy between the transfers of packet with supplier to target. In Figure 10, the relationship of Co-UWSN as well as EH-UWSNs shows, such Energy harvesting-UWSNs architecture consumed considerably smaller energy while compared by Co-UWSNs. Initially, with span 100(m) to 500(m), both strategies should consume over level with energy, but later 500(m) the Co-UWSNs consumed fast consumed in energy whilst compared by Energy harvesting-UWSNs architecture. In Energy harvesting-UWSNs plot, faster or after wherever energy is collected, about modest energy is spent in such a bit of the plot as 500(m) to 600(m).
The Co-UWSNs architecture is never an energy collecting concept, thus energy consumption is increased whilst range increases. The typical energy use of Energy harvesting-UWSNs architecture is nearly three times smaller from the Co-UWSNs plot. As a result, the analysis of plots, this is clear such Energy harvesting-UWSNs is a much better strategy from Co-UWSN architecture founded on energy use as well as additionally declared with Table 4 statistically.
6.4. Number of Packets Received
Throughput for a network is defined as the total number of packets successfully received at the destination. Numbers of packets gained converging upon destination show that how many packets are efficiently gained for each one loop on destination. In Figure 11, the two strategies are analysed founded on his plot. The typical assessment of Co-UWSNs plots is better to Energy harvesting-UWSNs. The reason by that is the core assessment of Co-UWSNs is the most important then Energy harvesting-UWSNs. If we consider the two strategies on the range 200(m), the Co-UWSNs get hold of 6.626e4 packet, but Energy harvesting-UWSNs get hold of 2.6e4 packet. With span 400(m) to 1000(m), dual of the strategies almost gained the same numbers of packet as well as moreover appeared in Table 5. In the even that we centre on Energy harvesting-UWSNs plots, a little bit of variation is viewed on a limited concentrate. That varieties occurred is for the reason that of energy accumulating on such concentrates.
6.5. Network Stability Period
The time with the initial opening point unto the principal node is dead, called the dependability time of the systems. That is clear with the results in Figure 12 such stability cycle for Energy harvesting-UWSNs is better to Co-UWSNs. The plan shows this for the starting, the two strategies starting by measures unto esteems approximately. The point whenever range increases with 100(m) to 1000(m), bit by bit diminishes occurred in the dependability time of dual of the strategies. Through 100(m) to 400(m), quick diminish are noticed in the two strategies. The typical assessment of Energy harvesting-UWSNs architecture is better to the Co-UWSN plot then moreover declared in Table 6.
In this examination, present another plan called EH-UWSN to stop the thought problems unto a certain level. Later, the audit of recreation comes about, it demonstrates that such Energy harvesting-UWSNs indicated extremely improved implementation in connections compared to current protocols, i.e., Co-UWSN about System Lifetime, Packet Dropped Ratio, Energy Consumption, Packet Delivery Ratio, as well as Stabilization Time of the systems.
EH-UWSN has consumed significantly a smaller amount of energy unto 3 times while compared to Co-UWSN between the transfers of data. In Figure 10, initially with sweep 100(m) to 500(m), both strategies keep consumed approximately levels by energy, but when 500(m) the Co-UWSN devoured quickly expanded in energy as compared by Energy harvesting-UWSNs architecture. A great difference is seemed in the typical assessments of Co-UWSN as well as Energy harvesting-UWSNs strategies. In the EH-UWSN plot, faster, or afterward wherever energy is accumulated, then small energy is consumed in this section of the plot as 500(m) to 600(m).
Moreover, EH-UWSN increased the system lifetime by collecting energy to the earth to create sensors survives for an extended time. In Figure 8, the core lifetime arrange assessment of Co-UWSN with span 100(m) to 400(m) is significantly most important whenever compared with Energy harvesting-UWSNs architecture. On sweep 400(m), the two strategies get grown to values all over. On the possibility such, we examine the plot of Co-UWSN architecture, it clearly shows that this it system lifetime esteem rot quickly such ranges increases with 100 (m) to 1000 (m). The Co-UWSN esteems bit by bit reduces while the sweep increases, while the plot of EH-UWSN architecture shows energy gathering at several concentrates in Figure 8. The point whenever sweep is equal to 500(m). Then, EH-UWSN architecture contains not enough system lifetime esteems, thus, it starts gathering energy over various levels with span 500(m) to 600(m) from a particular ending target to increase the lifetime of a system. Energy collecting is rearranged as shown in Figure 12, whenever the energy level decreases with the describe limit esteems. The replication arises around indicates the increase in Stable time of the Networks in EH-UWSN between the analysis with current strategy Co-UWSN in Figure 12. The typical assessment of EH-UWSN architecture is 106% increased whenever compared with UWSN. As the energy production, as well as dependability of a system depends upon the parameter in thinking, hereafter obviously EH-UWSN is most energy capable as well as Trustworthy from Co-UWSN protocols.
8. Future Work
In the future, the Energy Harvesting plan can be stretched out in various different zones as Wireless sensors systems, Body Area Networks, Multimedia Wireless sensor systems, Vehicle Adhoc systems, and so forth. Energy Harvesting is another strategy and expansive quantities of specialists use this method in various regions. By utilizing this procedure, the proposed plan can furthermore improve arrange lifetime by increasing further developed protocols. In that Given plot, we utilize the Decode-and-Forward procedure for information transmissions. In upcoming, the Energy Harvesting plan can be utilized on various different strategies as Amplify-and-Forward (AF) and so on; to dissect as well as contrast the outcomes and the exhibited plot Energy Harvesting-UWSNs to additionally enhance the Trustworthiness as well as Lifetime of the Networks.
In our proposal, utilize SNRC at goal to combine the signal got through several ways. In the future, it may use individual various methodologies as, FRC, MRC, as well as SC on goal to watched and compare the outcomes and the proposed architecture such that to define additional productive Routing Scheme for several WSN Environment. By using that technique, the analyst can moreover improve organize lifetime by increasing more developed protocols.
Data will be available upon request.
Conflicts of Interest
The authors declare no conflicts of interest.
Dr. Sheeraz did the basic idea of the research, research activity, and overall supervision. Taimur Ali and M. Shahzad did the data acquisition, paper write-up of Introduction and Related work. Ahmed Ali Shah and Yousaf Ali Khan did the Simulations and Results section write-up. Asif Nawaz and Zeeshan Najam did the mathematical modelling of the paper. Asma A. ALOthman did the data handling, administrative, and financial support. Awais Ahmed and Asma Shaheen did the revisions of English corrections and grammatical errors.
This work was funded by the Researchers Supporting Project Number (RSP-2020/243) King Saud University, Riyadh, Saudi Arabia.
- N. Kaur and S. Monga, “Comparisons of wired and wireless networks: a review,” International Journal of Advanced Engineering Technology, vol. 5, no. 2, pp. 34-35, 2014.
- Z. Kuang, G. Li, L. Zhang, H. Zhou, C. Li, and A. Liu, “Energy efficient mode selection, base station selection and resource allocation algorithm in D2D heterogeneous networks,” Peer-to-Peer Networking and Applications, vol. 1, pp. 1–16, 2020.
- M. Faheem, R. A. Butt, B. Raza et al., “QoSRP: A cross-layer QoS channel-aware routing protocol for the Internet of underwater acoustic sensor networks,” Sensors, vol. 19, no. 21, 2019.
- H. Alasarpanahi, V. Ayatollahitafti, and A. Gandomi, “Energy-efficient void avoidance geographic routing protocol for underwater sensor networks,” International Journal of Communication Systems, vol. 33, no. 6, 2020.
- Y. Su, R. Fan, F. Xiaomei, and Z. Jin, “DQELR: an adaptive deep Q-network-based energy-and latency-aware routing protocol design for underwater acoustic sensor networks,” IEEE Access, vol. 7, pp. 9091–9104, 2019.
- S. John, V. G. Menon, and A. Nayyar, “Simulation-based performance analysis of location-based opportunistic routing protocols in underwater sensor networks having communication voids,” in Data Management, Analytics and Innovation, vol. 1, pp. 697–711, Springer, Singapore, 2020.
- S. Ahmed, I. U. Khan, M. B. Rasheed et al., “Comparative analysis of routing protocols for under water wireless sensor networks,” 2013, https://arxiv.org/abs/1306.1148.
- M. R. Jafri, S. Ahmed, N. Javaid, Z. Ahmad, and R. J. Qureshi, “Amctd: adaptive mobility of courier sensors in threshold-optimized dbr protocol for underwater wireless sensor networks,” in 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 93–99, Compiegne, France, 2013.
- N. Javaid, M. R. Jafri, Z. A. Khan, U. Qasim, T. A. Alghamdi, and M. Ali, “Iamctd: improved adaptive mobility of courier Nodes in threshold-optimized dbr protocol for underwater wireless sensor networks,” International Journal of Distributed Sensor Networks, vol. 10, no. 11, Article ID 213012, 2014.
- N. Javaid, M. R. Jafri, S. Ahmed et al., “Delay-sensitive routing schemes for underwater acoustic sensor networks,” International Journal of Distributed Sensor Networks, vol. 11, no. 3, Article ID 532676, 2015.
- M. A. Khan, N. Javaid, A. Majid, M. Imran, and M. Alnuem, “Dual sink efficient balanced energy technique for underwater acoustic sensor networks,” in 2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 551–556, Crans-Montana, Switzerland, 2016.
- M. Peng, W. Liu, T. Wang, and Z. Zeng, “Relay selection joint consecutive packet routing scheme to improve performance for wake-up radio-enabled WSNs,” Wireless Communications and Mobile Computing, vol. 2020, Article ID 7230565, 32 pages, 2020.
- X. Liu, P. Lin, T. Liu, T. Wang, A. Liu, and X. Wenzheng, “Objective-variable tour planning for mobile data collection in partitioned sensor networks,” IEEE Transactions on Mobile Computing, vol. 1, 2020.
- M. R. Islam and Y. S. Han, “Cooperative MIMO communication at wireless sensor network: an error correcting code approach,” Sensors, vol. 11, no. 10, pp. 9887–9903, 2011.
- Z. Zhou, S. Zhou, J. H. Cui, and S. Cui, “Energy-efficient cooperative communication based on power control and selective single-relay in wireless sensor networks,” IEEE transactions on wireless communications, vol. 7, no. 8, pp. 3066–3078, 2008.
- Y. Wu, W. Liu, and K. Li, “Power allocation and relay selection for energy efficient cooperation in wireless sensor networks with energy harvesting,” EURASIP Journal on Wireless Communications and Networking, vol. 2017, no. 1, 2017.
- Z. Chen, M. Ma, X. Liu, A. Liu, and M. Zhao, “Reliability improved cooperative communication over wireless sensor networks,” Symmetry, vol. 9, no. 10, 2017.
- I. Bravo, E. Palomar, A. Gardel, and J. L. Lázaro, “Trusted and secure wireless sensor network Designs and deployments,” Sensors, vol. 17, no. 8, 2017.
- S. Hussain, M. S. Javed, S. Asim et al., “Novel gravel-like NiMoO4 nanoparticles on carbon cloth for outstanding supercapacitor applications,” Ceramics International, vol. 46, no. 5, pp. 6406–6412, 2020.
- K. Saeed, W. Khalil, S. Ahmed, I. Ahmad, and M. N. K. Khattak, “SEECR: secure energy efficient and cooperative routing protocol for underwater wireless sensor networks,” IEEE Access, vol. 8, pp. 107419–107433, 2020.
- M. Faheem, R. A. Butt, B. Raza et al., “FFRP: dynamic firefly mating optimization inspired energy efficient routing protocol for internet of underwater wireless sensor networks,” IEEE Access, vol. 8, pp. 39587–39604, 2020.
- H. Nasir, N. Javaid, M. Murtaza et al., “ACE: adaptive cooperation in EEDBR for underwater wireless sensor networks,” in 2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 8–14, Guangdong, China, 2014.
- S. Ahmed, M. Akbar, R. Ullah et al., “ARCUN: analytical approach towards reliability with cooperation for underwater WSNs,” Procedia Computer Science, vol. 52, pp. 576–583, 2015.
- T. Hafeez, N. Javaid, U. Shakeel, S. Hussain, and H. Maqsood, “An energy efficient adaptive cooperative routing protocol for underwater WSNs,” in 2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), pp. 304–310, Krakow, Poland, 2015.
- N. Javaid, H. Maqsood, A. Wadood et al., “A localization based cooperative routing protocol for underwater wireless sensor networks,” Mobile Information Systems, vol. 2017, Article ID 7954175, 16 pages, 2017.
- S. Ahmed, N. Javaid, F. A. Khan et al., “Co-UWSN: cooperative energy-efficient protocol for underwater WSNs,” International Journal of Distributed Sensor Networks, vol. 11, no. 4, Article ID 891410, 2015.
- S. Hussain, N. Javaid, S. Zarar, M. Z. Abidin, M. Ejaz, and T. Hafeez, “Improved adaptive cooperative routing in underwater wireless sensor networks,” in 2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA), pp. 99–106, Krakow, Poland, 2015.
- S. Ahmed, N. Javaid, A. Ahmad et al., “SPARCO: stochastic performance analysis with reliability and cooperation for underwater wireless sensor networks,” Journal of Sensors, vol. 2016, Article ID 7604163, 17 pages, 2016.
- S. Ahmed, N. Javaid, S. Shahid, F. Hadi, and M. Q. Azeem, “RACE: reliability and adaptive cooperation for efficient underwater sensor networks,” in 2016 International Conference on Open Source Systems & Technologies (ICOSST), pp. 122–128, Lahore, Pakistan, 2016.
- M. Faheem, M. A. Ngadi, and V. C. Gungor, “Energy efficient multi-objective evolutionary routing scheme for reliable data gathering in internet of underwater acoustic sensor networks,” Ad Hoc Networks, vol. 93, article 101912, 2019.
- S. Anandalatchoumy and G. Sivaradje, “Comprehensive study of acoustic channel models for underwater wireless communication networks,” International Journal on Cybernetics & Informatics, vol. 4, no. 2, pp. 227–240, 2015.
- S. Hussain, X. Yang, M. K. Aslam et al., “Robust TiN nanoparticles polysulfide anchor for Li-S storage and diffusion pathways using first principle calculations,” Chemical Engineering Journal, vol. 391, article 123595, 2020.
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