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Exploiting Energy Efficient Routing protocols for Void Hole Alleviation in IoT enabled Underwater WSN

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In recent times, different routing protocols have been proposed in the Internet of Things enabled Underwater Wireless Sensor Networks (IoT-UWSNs) to explore the underwater environment for different purposes, i.e., scientific and military purposes. However, high Energy Consumption (EC), End to End (E2E) delay, low Packet Delivery Ratio (PDR) and minimum network lifetime make the energy efficient communication a challenging task in Underwater Wireless Sensor Network (UWSN). The high E2E delay, EC and reliable data delivery are the critical issues, which play an important role to enhance the network throughput. So, this paper presents two energy efficient routing protocols namely: Shortest PathCollision avoidance Based Energy Efficient Routing (SP-CBE2R) protocol and Improved-Collision avoidance Based Energy Efficient Routing (Im-CBE2R) protocol. At this end, both routing protocols minimize the probability of void hole occurrence and in return minimizes the EC and E2E delay. In both routing protocols, courier nodes are positioned at different strategic locations to keep the greedy forwarding continuous. The proposed routing protocols are also analyzed by varying the Packet Size (PS) and Data Rate (DR). Additionally, various simulations have been performed to authenticate the proposed routing protocols. Simulation results show that the proposed routing protocols outperform the baseline routing protocols in counterparts.
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Exploiting Energy Efficient Routing protocols for
Void Hole Alleviation in IoT enabled Underwater
WSN
Muhammad Awais1, Nadeem Javaid1,, Nidal Naseer2, Muhammad Imran3
1Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan;
amawais@hotmail.com, nadeemjavaidqau@gmail.com
2College of Engineering, Alfaisal University, Saudi Arabia; nnidal@gmail.com
3College of Applied Computer Science, King Saud University 11451, Saudi Arabia; dr.m.imran@ieee.org
Corresponding author: www.njavaid.com, nadeemjavaidqau@gmail.com
Abstract—In recent times, different routing protocols have
been proposed in the Internet of Things enabled Underwater
Wireless Sensor Networks (IoT-UWSNs) to explore the under-
water environment for different purposes, i.e., scientific and
military purposes. However, high Energy Consumption (EC),
End to End (E2E) delay, low Packet Delivery Ratio (PDR)
and minimum network lifetime make the energy efficient com-
munication a challenging task in Underwater Wireless Sensor
Network (UWSN). The high E2E delay, EC and reliable data
delivery are the critical issues, which play an important role
to enhance the network throughput. So, this paper presents
two energy efficient routing protocols namely: Shortest Path-
Collision avoidance Based Energy Efficient Routing (SP-CBE2R)
protocol and Improved-Collision avoidance Based Energy Effi-
cient Routing (Im-CBE2R) protocol. At this end, both routing
protocols minimize the probability of void hole occurrence and
in return minimizes the EC and E2E delay. In both routing
protocols, courier nodes are positioned at different strategic
locations to keep the greedy forwarding continuous. The proposed
routing protocols are also analyzed by varying the Packet Size
(PS) and Data Rate (DR). Additionally, various simulations have
been performed to authenticate the proposed routing protocols.
Simulation results show that the proposed routing protocols
outperform the baseline routing protocols in counterparts.
Index Terms—Energy efficient, Void hole, Reliable data deliv-
ery, Shortest path based routing, EC, Depth
I. INTRODUCTION
In the last decade, Underwater Wireless Sensor Networks
(UWSNs) have gained a lot of attention from researchers
because of their potential to monitor the underwater envi-
ronment. UWSNs have an extensive variety of applications
such as military defense, monitoring the aquatic environment,
disaster prevention, oil/gas extraction, offshore exploration,
commercial and scientific purposes, etc. [1] [2].
In an underwater atmosphere, protocols premeditated for
Terrestrial Wireless Sensor Networks (TWSNs) cannot work
perfectly. TWSNs and UWSNs differ in various aspects, i.e.,
use of acoustic waves instead of radio waves, topological
behavior (more dynamic in UWSNs), difficult localization and
deployment problem. In addition, limited energy resources also
affects the network performance and it is difficult to remove
or recharge the battery again. Moreover, low bandwidth, high
energy cost and propagation delay induces serious challenges
in UWSNs [3].
Various routing protocols are proposed to enhance the
Packet Delivery Ratio (PDR) with minimum Energy Consump-
tion (EC) and low End to End (E2E) delay in UWSNs [4]- [6].
Geographic routing uses greedy forwarding strategy. However,
in the greedy forwarding strategy, there is a chance of void
hole occurrence. Therefore, an efficient protocol is required
which has a mechanism to avoid the void hole with minimum
packets collision.
Geographic routing is simple and scalable routing technique
because it does not need to form or maintain the whole routing
table from source to destination [3]. In opportunistic routing,
each Data Packet (DP) is sent to a forwarding set that consists
of neighbors. This set consists of nodes that are aligned with
respect to certain priorities. Only the node with the highest
priority is able to forward the DP. Other nodes will cancel
their transmissions when they hear the transmission of DP
from a node with high priority. Therefore, by combining both
geographic and opportunistic PDR improves and minimizes
the EC as it reduces the retransmissions of DPs.
However, geographic and opportunistic routing causes void
hole problems. The void hole occurs, when a forwarder node
does not find the next forwarder in its transmission range
and closer to sink [7]. Each time a packet gets jammed at
a node that is in a void region, the routing protocol ought
to direct the data packet by using some retrieval technique;
otherwise, the packet ought to be dropped. Motivated by
the above consideration, we propose two routing protocols
namely: Shortest Path-Collision avoidance Based Energy Effi-
cient Routing (SP-CBE2R) and Improved-Collision avoidance
Based Energy Efficient Routing (Im-CBE2R).
The contributions of the proposed work are as follows:
Using anycast geo-opportunistic based routing practice,
the SP-CBE2R protocol is proposed in which it selects
the next forwarder node using Dijkstra algorithm (from
current source node towards the destined courier node)
with minimum neighbor nodes to avoid collision.
978-1-5386-7747-6/19/$31.00 ©2019 IEEE 1797
The Im-CBE2R protocol is proposed that selects the next
forwarder node on the bases of distance from the current
source node towards the courier node, number of hop
count, number of neighbors and EC during transmission
and reception of DPs.
both proposed routing protocols alleviate the void holes
by using the static courier nodes at different strategic
locations (using the concept of layering).
These routing protocols distribute the UWSN into layers,
where courier nodes help the ordinary sensor nodes for
reliable data delivery and improve the network lifetime,
minimize the EC and E2E delay.
Comparative analysis of the proposed routing protocols
is performed with other baseline routing protocol in
the counterparts. Additionally, extensive simulations are
also performed to validate the efficiency of the proposed
routing protocols.
II. LITERATURE REVIEW
In this section, the related work of the routing protocols in
UWSNs is presented with their features and limitations.
Authors in [8] proposed two schemes namely: GEographic
and opportunistic routing with Depth and Power Adjustment
Routing (GEDPAR) and E2E Void Hole Recovery (E2EVHR)
routing techniques. These routing protocols alleviate the void
hole problem and preserve the energy of the sensor nodes in
UWSNs. The proposed protocols minimized EC at the cost of
affordable E2E delay.
An improved Adaptive Mobility of Courier nodes in
Threshold-optimized DBR (iAMCTD) [9] comes in the cat-
egory of location-free routing protocols specially designed for
time-dependent applications. This provides improved network
lifetime, minimized E2E delay due to the efficient movement
of courier nodes. However, this scheme results in low through-
put, because of avoidance of unnecessary transmission.
Balanced Load Distribution (BLOAD) [10] is a two-
dimensional network protocol. The BLOAD tackles the prob-
lem of energy holes. In this scheme, data is distributed into
three subparts. These portions of data are then forwarded
using direct and multi-hop transmission to the destination. This
scheme results in improved network stability and lifetime. The
limitation of BLOAD has increased consumption of energy as
it transmits the DPs using different transmission ranges.
An Energy-efficient Channel Aware Routing Protocol (E-
CARP) [11] is a distributed cross-layer reactive routing pro-
tocol. Moreover, this scheme covered the problems identified
from the traditional CARP scheme where the authors have
not followed the re-usability property. This offers improved
network lifetime and reduced EC by avoiding control packets.
However, this scheme results in reduced throughput and high
path loss due to the mobility of nodes.
In Hydraulic-pressure-based anyCast routing (HydroCast)
[12] authors objective is to design an effective routing al-
gorithm for consistent broadcasting to any of the sinks and
to solve the problem of the void hole. Thus, it directs the
data upward to lower depths. However, the gauge used has to
perfectly guess the depth of that node. It has improved PDR
and its limitations are its low performance and increased EC.
An Adaptive Hop-by-Hop Vector-Based forwarding routing
protocol (AHH-VBF) [13] uses a scheme that changes the
radius of pipeline adaptively. This strategy amends the for-
warding area of the DPs and helps them in minimizing the
duplicate packets. This strategy results in improved PDR, less
EC and low E2E delay. However, the probability of void hole
occurrence still exits.
An Opportunistic Routing based on Residual energy (ORR)
[14] designed for asynchronous duty-cycled wireless sensor
networks. To calculate the best forwarder, residual energy
and forwarding score calculation is considered. This protocol
addresses the problems of load balancing, losing coverage
and connectivity with residual energy for selecting forwarder
node. However, asynchronous duty cycling causes additional
E2E delay due to waiting for the next hop node to wake up.
As, in this protocol, duty cycling is not low as required and
number of forwarders can wake up simultaneously that result
in duplication of packets.
In Energy Efficient and Load Balanced distributed Routing
(ELBAR) [15], sensor nodes cooperate with each other to find
the estimated polygon of a specific hole and then the sensor
nodes update their routing table. The sensed data is forwarded
along escape route that surrounds the hole on the basis of view
angle of the hole and hole covering parallelogram. Authors
objective is to route data within the presence of those holes.
This routing scheme increases the lifetime of the network and
also minimizes the EC. However, this scheme may lead to
longer routing path, high E2E delay and high EC.
Cluster based sleep wake scheduling is proposed in [16]. In
this paper, the authors have used a technique in which some of
the nodes are assumed as initiator nodes. These initiator nodes
then selects the CHs. The CH with high energy is selected
as a head node. This CH is set to active mode while other
nodes sent to sleep mode. The transmission is then resumed
by selected head node towards the sink node. This scheme
decreases EC, enhances lifetime and PDR. However, having
the same CH throughout the network lifespan degrades the
network performance.
An Enhanced Developed Distributed Energy Efficient Clus-
tering (EDDEEC) is proposed for heterogeneous WSN in [17].
In this paper, the authors have proposed two models for mini-
mizing EC. First one is heterogeneous network model, second
one is EC model. Then authors have proposed their routing
protocol based on clusters. In proposed scheme, authors have
tried to change the probability of CH selection proficiently.
In this paper, authors have achieved improved performance
with respect to stability period, network lifetime, and PDR.
However, the clustering is imbalanced and reelection increases
the overhead.
In [18], two proactive energy efficient routing proto-
cols namely: Energy-efficient Path-based Void hole and
Interference-free Routing (EP-VIR-Three) and Bellman–Ford
Shortest Path-based Routing (BF-SPR-Three) are proposed.
Both routing protocols check three hops neighbours informa-
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tion for the next forwarder node selection and avoid the void
holes. However, both routing protocols face affordable E2E
delay.
III. PROB LE M STATEM EN T
In UWSN, the key focus of the researchers is on reliable
data transmission by efficient energy utilization of the sensor
nodes. As in [19], clustered-based energy efficient routing is
performed. CBE2R ensures reliable data delivery. However,
the avoidance of duplicate packets generation is very difficult.
Moreover, simultaneous transmissions lead to channel interfer-
ence. Further, it causes the packets collision, which results in
maximum EC (due to retransmissions), high packets drop with
high E2E delay. The above analysis shows that this strategy
can be further optimized to improve the performance of IoT-
UWSN. Therefore, the aforementioned problems motivate us
to design two new energy efficient routing protocols.
IV. SYS TE M MOD EL A ND DESCRIPTION OF THE
PROP OS ED PROTOCOLS
In this section, we have discussed the system model of the
proposed routing protocols. In addition, the basic assumptions
of the proposed routing protocols are also discussed. The detail
is given the following subsections.
A. Basic Assumptions
Our proposed routing protocols have the following assump-
tions.
Sink nodes are deployed at the surface of the sea water.
Source nodes are deployed in the bottom-most layer of
the network.
Network is divided into seven equal layers with the depth
difference of 150 m each.
Seven courier nodes are deployed on these layers at
different strategic locations.
Ordinary sensor nodes are deployed randomly in between
the layers to help the courier nodes (deployed at strategic
locations).
In SP-CBE2R, the shortest path between source to nearest
courier node is selected using the Dijkstra algorithm.
Meanwhile, in Im-CBE2R, the route is selected using the
highest CF value.
Courier nodes collect the data from the ordinary sensor
nodes and using the same scenario destined the data to
the respective sink.
As the data reaches the destined sink it means that data
is successfully reached the base station.
Both proposed routing protocols control the depth using
the layering concept which also helps them to control the
mobility of the sensor nodes. The shortest path selection
strategy overcomes the problem of high energy dissipation of
the courier nodes (in IoT-UWSN) and enhances the network
lifetime.
B. Network Architecture
Figure 1 focuses on the network architecture of the proposed
routing protocols. Proposed protocols consist of ordinary
nodes, courier nodes and source nodes. Multiple sinks are also
deployed on the surface of the water. These sinks are con-
nected with onshore base stations using radio waves. Mean-
while, these sinks are also linked within range courier nodes
and ordinary sensor nodes through acoustic links. Furthermore,
the IoT-UWSN is divided into seven layers to control the
mobility of the nodes at depth d. Whereas, seven static courier
nodes are deployed on each layer at strategic locations. The
randomly deployed ordinary nodes (between these layers) help
the courier nodes for reliable data forwarding towards the sink.
C. Beaconing Mechanism
In these routing protocols, a beacon message is generated
from sink including Euclidean distance from the sink. After-
ward, every node broadcasts a message to find the neighbor
nodes in its transmission range. This message helps the sensor
nodes to find the neighbor nodes and the number of hop count.
In addition, we have implemented reactive beaconing in our
proposed system model. At this end, every sensor node has
the information of their neighbor nodes, distance from the
nearest sink and the number of hop count from that sink.
Therefore, a hello packet message is sent from each sensor
node to share this information with its neighbor nodes. In
return, every neighbor node maintains a routing table at its
end including a number of neighbor nodes in their transmission
range, distance from each neighbor node and hop count from
the sink. When a sender node sends its DP, it includes a hello
packet. On the other side, upon data reception, if the depth
of the receiver node is higher than the sender node than the
receiver node updates its routing table.
D. Route establishment in SP-CBE2R
In SP-CBE2R, the route is established from the source node
to the nearest courier node using ordinary sensor nodes (using
the Dijkstra algorithm).
[Dist, P ath] = Dijkstra (N, Seg, S I D, D I D).(1)
Here, Nshows nodes, seg shows segments and SID, D
ID represents the source and destination ID, respectively.
Whereas, nodes are the matrix with node ID (N-ID) and its
coordinates (X, Y). Meanwhile, segments include the matrix
including node ID and its neighbor nodes (Node1 and Node2).
Further, starting ID represents the source node and destination
ID represents the destined courier node. These parameters can
also be represented as:
Nodes = [NID X Y ].(2)
Segments = [NID N ode1Node2].(3)
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Fig. 1. Network Architecture of SP-CBE2R and Im-CBE2R
E. Route establishment in Im-CBE2R
In Im-CBE2R, the route is established from the source node
to the nearest courier node using CF value. The probability of
the next forwarder node will be high if its CF value will be
high. This CF value is based on number of neighbor nodes,
hop count from the nearest courier node, distance from the
nearest courier node and EC rate. We have calculated the CF
value using Eq. (4).
Wi,j =ψ×(Disti,j
Hi,j ×Nneigh ×ECrate
)and ψ = 10.(4)
Whereas, Disti,j is the distance from source to the nearest
courier node, Hi,j is the number of hop count from source
to the nearest courier node, Nneigh represents the number of
neighbors and ECr ate is the EC rate of the node j. In addition,
Eq. (4) will have maximum CF value if the source node has
least Nneigh, minimum Hi,j , minimum E Crate and maximum
Disti,j .
F. Transmission Phase in Proposed Routing Protocols
When the path establishment phase is completed then data is
forwarded from the source node to the destined courier node.
Afterward, courier nodes collect this data and forward this data
to the next courier node (using the same procedure). Finally,
data reaches the destined sink and forwarded to the nearest
base station.
G. EC Model
The EC model used in the proposed routing protocols is
similar to Eq. (5) as in [19].
ET=ρL×(Dist)2×10φ(f).(5)
ETrepresents transmission energy, ρLrepresents power
level towards receiver node, (Dist)2represents distance to-
wards receiver and φ(f)represents the absorption co-efficient.
φ(f)is measured in dB/m. It is calculated using Eq. (6).
φ(f)=0.11×103f3
1 + f2+44×103f2
4100 + f2+2.75×107f2+3×106.
(6)
Whereas, fis the carrier frequency. It is measured in KHz.
V. SIMULATION RESULTS A ND DISCUSSION
In this section, simulation setup and comparative analysis
of the proposed routing protocols are discussed. Performance
of the proposed routing protocols (i.e., SP-CBE2R and Im-
CBE2R) is evaluated using the performance metrics including
EC, E2E delay, throughput and PDR. In both proposed routing
protocols, the greedy forwarding approach is used to forward
the DPs from the source node to the destined sink. Simula-
tion’s setup of the implemented routing protocols is explained
below.
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A. Simulation Setup
In this paper, two different routing protocols are imple-
mented. In both routing protocols, 350 simple sensor nodes
are deployed with 49 fixed courier nodes (special nodes having
higher energy than simple sensor nodes) in an area of (1500
x 1500) m2. Additionally, we have divided the network into
seven layers. Whereas, the average depth difference between
each layer is kept 150 m. Various simulations are performed
to evaluate the performance of proposed routing protocols
by changing the DR (10, 20 and 30 Kbps) and PS (70, 80,
90 and 100 bytes). Furthermore, we have used the real-time
parameters in UWSN, i.e., water salinity and temperature.
B. Performance Metrics
The proposed routing protocols are evaluated on the bases
of EC and E2E Delay.
C. Simulation Results
In this section, a comparative analysis of proposed routing
protocols and state-of-the-art routing protocols is discussed.
The detailed discussion on each performance parameter is
presented below:
D. EC
EC is measured by calculating the difference between the
initial and the final energy of the nodes in the network. The
EC of the proposed and state-of-the-art routing protocols is
shown in Fig. 2. This figure shows that the EC of SP-CBE2R
and Im-CBE2R is lower than CBE2R because of courier nodes
(deployed at different strategic locations) having high energy
level than simple sensor nodes. In addition, both proposed
routing protocols use the residual energy and a minimum
number of hop count for the selection of the next potential
forwarder node. The minimum number of hop and the selec-
tion of the next potential forwarder avoid the packet collision
and interference between the DPs (which results in a minimum
number of retransmissions). Moreover, route selection in SP-
CBE2R (using Dijkstra algorithm) and Im-CBE2R (using
CF defined in Eq. (4)) make the proposed routing protocols
different from the existing CBE2R routing protocol. Due to
these aforementioned reasons, EC of the routing protocols
decreases as compared to CBE2R. Furthermore, both proposed
routing protocols efficiently manage the distance between the
sink and source nodes using 49 courier nodes distributed in the
defined layers (7 layers) with the depth difference of 150 m
each. These properties affirm that proposed routing protocols
outperformed in the counterpart.
E. E2E Delay
E2E delay is the time taken by the DPs to reach the
destined sink from different source nodes. Fig. 3 shows the
comparison graph of E2E delay of the proposed and existing
routing protocols. This figure shows that the E2E delay of
SP-CBE2R and Im-CBE2R is lower than CBE2R because of
courier nodes deployed at different strategic locations. The
minimum number of hop and the selection of the next potential
PS (70-bytes) PS (80-bytes) PS (90-bytes) PS (100-bytes)
PS (byte)
0
500
1000
1500
EC (J)
DR= 10Kbps (CBE2R)
DR= 20Kbps (CBE2R)
DR= 30Kbps (CBE2R)
DR= 10Kbps (SP-CBE2R)
DR= 20Kbps (SP-CBE2R)
DR= 30Kbps (SP-CBE2R)
DR= 10Kbps (Im-CBE2R)
DR= 20Kbps (Im-CBE2R)
DR= 30Kbps (Im-CBE2R)
Fig. 2. EC
forwarder node avoid the packet collision and interference
between the DPs. This strategy results in a minimum number
of retransmissions which ultimately minimizes the E2E delay
in the network. Moreover, the route selection in SP-CBE2R
using Dijkstra algorithm and Im-CBE2R using CF defined in
Eq. (4) make the proposed routing protocols different from
the benchmark routing protocol. Due to these aforementioned
reasons, E2E delay of the proposed routing protocols decreases
as compared to CBE2R. Furthermore, both proposed routing
protocols efficiently manage the distance between the sink and
source nodes using courier nodes. These properties show that
proposed routing protocols outperformed in minimizing the
E2E delay.
PS (70-bytes) PS (80-bytes) PS (90-bytes) PS (100-bytes)
PS (byte)
0
2
4
6
8
10
12
14
16
18
E2E Delay (Sec)
DR= 10Kbps (CBE2R)
DR= 20Kbps (CBE2R)
DR= 30Kbps (CBE2R)
DR= 10Kbps (SP-CBE2R)
DR= 20Kbps (SP-CBE2R)
DR= 30Kbps (SP-CBE2R)
DR= 10Kbps (Im-CBE2R)
DR= 20Kbps (Im-CBE2R)
DR= 30Kbps (Im-CBE2R)
Fig. 3. E2E Delay
VI. CONCLUSION
In this paper, two energy efficient routing protocols: SP-
CBE2R and Im-CBE2R are proposed. The proposed routing
protocols avoid the void hole problem using deployment of
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static strategic courier nodes (high energy nodes). At this end,
these routing protocols minimize the EC and E2E delay and
enhance the PDR and throughput of the network. In both
routing protocols, forwarder nodes are elected to continue
the greedy forwarding. In SP-CBE2R, the route is selected
using the Dijkstra algorithm. Meanwhile, Im-CBE2R uses the
CF value to find the next potential forwarder node. Proposed
routing protocols are also analyzed by varying the PSs and
DRs. Moreover, various simulations have been performed
to evaluate the performance of proposed routing protocols.
Results show the efficacy of the proposed routing protocols in
counterparts. In the future, we will further exploit the proposed
routing protocols to get a quick response during the topological
changes during transmission. In addition, scalability of the
proposed routing protocols will be analyzed by varying the
number of nodes.
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1916-1930.
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... Coming up next are some of the principal issues identified with UWSNs. Such as Topology management, Standardization of UWSNs [12], Power management energy supervision for UWSNs [13,14], Cost, Position information [15,16], Network components [1] Modeling and simulation in UWSNs [1,5], Architecture of UWSNs [10], Energy-efficient protocols [17,18]. Inspired by the above meditations of UWSNs, we intend schemes for void hole avoidance first one is, Avoiding Void Hole-Adaptive Hop by Hop-Vector-Based Forwarding (AVH-AHH-VBF) in underwater wireless sensor network and second scheme for improving lifetime of the network and reducing consumption of energy, Sink Mobility in Adaptive Hop by Hop Vector-Based Forwarding (SM-AHH-VBF). ...
... Awais et al. [17] proposed viable, predictable, and commotion-free directing convention creators recommended two conventions, BF-SPR-Three and EP-VIR-Three. The point of creators in this examination work to decrease the use of additional energy utilization, lessening obstruction, staying away from void opening, and expanding parcel conveyance). ...
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Underwater Wireless Sensor Network (UWSN) accomplishes the consideration of a few scientists and academicians towards itself. Because of the brutality of the climate lies submerged represents various difficulties, i.e., high transmission delay, outstanding piece mistake rate, more expense in usage, sinks development and energy imperatives, unequal surface highlights of an area and low data transfer capacity, and so forth Void opening evasion is compulsory for to motivation behind limiting the utilization of energy and amplifying throughput and region inclusion. In this exploration work, the creator planned plans for void opening shirking initial one is, Avoiding Void Hole Adaptive Hop by Hop Vector-Based Forwarding (AVH-AHH-VBF) in submerged remote sensor organization and a second plan for limiting utilization of energy and expanding the lifetime of the organization, Sink Mobility-Adaptive Hop by Hop Vector-Based Forwarding (SM-AHH-VBF). Reproduction results show that our plans beat contrasted and standard arrangement as far as normal Packet Delivery Ratio (PDR), energy charge. Our reproduction confirms the effectiveness of our proposed procedure AVH-AHH-VBF equivalents to 0.17 and SM-AHH-VBF equivalents to 0.24 regarding normal PDR, AVH-AHH-VBF equivalents to 24j and SM-AHH-VBF equivalents to 5j for the normal energy charge, AVH-AHH-VBF had a tradeoff of 63% in light of considering two jumps and SM-AHH-VBF approaches 20% tradeoff for normal start to finish.
... SP-CBE2R [51]: The shortest path-collision avoidancebased energy-efficient routing (SP-CBE2R) protocol is presented to address the critical issues of high energy consumption, end to end delay, low packet delivery ratio, and minimum network lifetime for UWSNs. The next forwarder node is selected using the Dijkstra algorithm (from the current source node towards the destined courier node) with minimum neighbor nodes to avoid a collision. ...
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Underwater Wireless Sensor Networks (UWSNs) are promising and emerging frameworks having a wide range of applications. The underwater sensor deployment is beneficial; however, some factors limit the performance of the network, i.e., less reliability, high end-to-end delay and maximum energy dissipation. The provisioning of the aforementioned factors has become a challenging task for the research community. In UWSNs, battery consumption is inevitable and has a direct impact on the performance of the network. Most of the time energy dissipates due to the creation of void holes and imbalanced network deployment. In this work, two routing protocols are proposed to avoid the void hole and extra energy dissipation problems which, due to which lifespan of the network increases. To show the efficacy of the proposed routing schemes, they are compared with the state of the art protocols. Simulation results show that the proposed schemes outperform the counterparts.
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Recently, underwater wireless sensor networks (UWSNs) have emerged as a promising networking technique for various underwater applications. An energy efficient routing protocol plays a vital role in data transmission and practical applications. However, due to the specific 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 existing routing protocols in UWSNs. First, we classify existing routing protocols into two categories based on a route decision maker. Then the performance of existing routing protocols is compared in detail. Furthermore, future research issues of routing protocols in UWSNs are carefully analyzed.
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