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Cluster-Based Routing Protocols
with Adaptive Transmission Range
Adjustment in UWSNs
Muhammad Awais1, Zahoor Ali Khan2, Nadeem Javaid1(B
), Abdul Mateen1,
Aymen Rasul1, and Farooq Hassan3
1COMSATS University Islamabad, Islamabad 44000, Pakistan
nadeemjavaidqau@gmail.com
2Computer Information Science, Higher Colleges of Technology,
Fujairah 4114, UAE
3University of Lahore, Islamabad Campus, Islamabad 44000, Pakistan
www.njavaid.com
Abstract. Nowadays, limited battery lifespan in Underwater Wireless
Sensor Networks (UWSNs) is one of the key concerns for reliable data
delivery. Traditional transmission approaches increase the transmission
overhead, i.e., packet collision and congestion, which affects the reliable
data delivery. Additionally, replacement of the sensors battery in the
harsh aquatic environment is a challenging task. To save the network
from sudden failure and to prolong the lifespan of the network, efficient
routing protocols are needed to control the excessive energy dissipation.
Therefore, this paper proposes two cluster-based routing protocols. The
proposed protocols adaptively adjust their transmission range to keep
maximum neighbors in their transmission range. This transmission range
adjustment helps the routing protocols to retain their transmission pro-
cess continuous by removing void holes from the network. Clusters forma-
tion in both proposed protocols makes the data transmission successful,
which enhances the Packet Delivery Ratio (PDR). A comparative analy-
sis is also performed with two state-of-the-art protocols named: Weight-
ing Depth Forwarding Area Division, Depth Based Routing (WDFAD-
DBR) and Cluster-Based WDFAD-DB (CB-WDFAD-DBR). Simulation
results show the effectiveness of the proposed protocols in terms of PDR,
Energy Consumption (EC) and End to End (E2E) delay.
Keywords: Energy efficient ·Void hole ·Shortest path approach ·
Reliable data delivery ·Clustering
1 Introduction
Nowadays, recent advances in Underwater Wireless Sensor Network (UWSN)
motivated many researchers for the development of various applications in the
scientific and environmental era, i.e., data collection, monitoring of underwater
c
Springer Nature Switzerland AG 2019
L. Barolli et al. (Eds.): EIDWT 2019, LNDECT 29, pp. 528–539, 2019.
https://doi.org/10.1007/978-3-030-12839-5_49
Cluster-Based Adoptive Routing Protocols in UWSNs 529
equipment and disasters prevention [1,2]. In UWSNs, during long-term commu-
nication acoustic waves are preferred instead of radio waves because of their low
absorption rate and scattering. Moreover, dynamic environmental changes, lim-
ited lifespan of the battery and high End to End (E2E) delay with high Energy
Consumption (EC) are the adverse characteristics of UWSN [3,4]. To enhance
the lifetime of the network, some of the researchers focus on multi-hopping tech-
niques. To enhance the stability of the network, multi-hop techniques are pre-
ferred. These promising techniques minimize the EC with affordable E2E delay
and help many other UWSN applications, i.e., temperature collection and envi-
ronmental data collection. Some of the researchers have focused on transmission
range adjustment [5] for successful packet transmission. However, limited bat-
tery lifespan in an underwater environment is a challenging task. In UWSN, it
is really difficult for the sensors to use solar power chargers because sunlight
is unable to reach in the depth of the sea. These techniques still have to be
enhanced because sensors are vulnerable to the sea water corrosion and marine
animals activities.
The best routing path selection is also important to route the data packets
from the source node towards the destined sink. Therefore, energy limitations
play an important role in the designing of a routing protocol in UWSNs. In [17],
only two metrics are considered to efficiently utilize the nodes battery: the depth
of the nodes and next forwarder node selection on the basis of 2-hop neighbors
information. Although the probability of void holes occurrence and inefficient
EC is reduced during the nodes communication, the probability of void hole
occurrence still exists in their work. Therefore, to minimize the aforementioned
problem, cluster-based transmission range adjustment strategy is adopted in [5].
The void hole occurrence problem is minimized in this work. However, the extra
power is needed for the transmission range adjustment. In this paper, to tackle
the problem of extra energy dissipation and void hole avoidance, we have per-
formed clusters formation using shortest and efficient path selection and also
proposed two routing protocols named: Shortest Path-based Weighting Depth
Forwarding Area Division and Depth Based Routing (SPB-WDFAD-DBR) and
Breadth First Shortest Path-based WDFAD-DBR (BFSPB-WDFAD-DBR). The
proposed clustering protocols make clusters and improve PDR. Residual energy
of nodes is also taken into account for efficient data forwarding and transmis-
sion range adjustment. Proposed protocols perform reliable data delivery with
affordable E2E delay and enhance the lifespan of node’s battery in UWSNs. The
main contributions, features, and achievements of this paper are summarized as
follows:
– In order to avoid the void hole problem two efficient routing protocols named:
SPB-WDFAD-DBR and BFSPB-WDFAD-DBR are proposed.
– The concept of adaptive transmission range adjustment is implemented to
avoid the void holes.
– The proposed protocols are compared with state-of-the-art protocols named:
WDFAD-DBR and CB-WDFAD-DBR.
530 M. Awais et al.
The rest of the paper is organized as follows: Sect. 2presents the literature
review of the state of the art protocols. Section 3describes the system model of
the proposed protocols. Simulation and results are discussed in Sect. 4. Finally,
Sect. 5ends with conclusion and future work of the paper.
2 Literature Review
In this section, state of the art routing protocols are discussed for depth under-
standing of data load balancing, E2E delay and EC to maximize the throughput
of UWSN. Few of these protocols are presented as follows:
Energy-aware and energy efficient schemes are proposed in [7–12]. DAE also
balances the load per node to prolong the network lifetime, similarly, as in [8]
and [10]. Chaotic compressive sensing for secure data transmission is used to
reduce the number of retransmissions [8]. In the same way, based on random
access, the shortest retransmission based strategy is also proposed for complex
environments in UWSN.
Furthermore, a Cooperative Energy Efficient Optimal Relay Selection Pro-
tocol (Co-EEORS) is proposed in UWSN [9]. Combine information of location
and depth is used to select the destination node [7,9]. In [9], after the successful
receiving, destination node acknowledges the source node about the successful
reception of data packets at the destination. A novel routing scheme is proposed
in [10] with two mobile sinks for efficient data collection. Moreover, a new met-
ric ‘mobility sink utility ratio’ is introduced to check the usage of mobile sinks
during the collection of data. Afterward, in [11], the author proposed a Cuckoo
Optimization Algorithm (COA) which is basically the combination of three tech-
niques, i.e., geo-routing, duty-cyclic routing, and multi-path routing. The COA
protocol transmits data hop by hop and selects the route using power consump-
tion and energy content of the current node. However, the authors in [7]have
not taken the dynamic environmental changes into account [9,11]. The authors
in [8] has not considered the EC on compression and during the selection of next
forwarder node. Delay in packet transmission at the sink and their recombining
cost is not considered in [10].
Khan et al. and Wang et al. proposed Energy Efficient Routing and Void Hole
Avoidance (E2RV) scheme, Energy-aware and Void Hole Avoidable Routing pro-
tocol(EAVARP)in[12] and [13]. The 2-hops information is used to cover the
void hole region in [12]. E2RV and EAVARP maintain the energy depletion of the
network to prolong the network lifetime. Furthermore, opportunistic directional
forwarding strategy is used for aforementioned parameters in EAVARP. In addi-
tion, cyclic transmission is avoided in EAVARP. E2RV performed well in terms
of PDR and minimum energy depletion [12,13]. Additionally, avoiding the void
holes, looping, and energy efficacy EAVARP outperformed [13]. However, dis-
tance dependency on energy and communication overhead is not focused [12,13].
Spare regions affect the processing time of network is not considered in [13].
In [14–16] novel approach named: Clustered based Energy Efficient Routing
(CBEER) protocol, Energy balanced unequal layering clustering (EULC) and
Cluster-Based Adoptive Routing Protocols in UWSNs 531
Clustered-based energy efficient routing(CBE2R) protocol are proposed to pro-
long the network lifetime. These are energy efficient and cluster-based schemes
in UWSNs. CBEER finds the shortest path [14], EULC and CBE2R use lay-
ering concept based on cluster formation to transmit the data packets [15,16].
Furthermore, all above-mentioned schemes are evaluated using extensive simu-
lations and it is noticed that these protocols performed out in terms of enhanced
PDR with minimum EC [14–16]. However, sparse regions overhead and commu-
nication overhead is not discussed in [14] and [15].
In [17], weighting depth and forwarding area division depth based routing
WDFAD-DBR is proposed. Weighting sum of depth difference of 2-hops is used
for the selection of next forwarding hop in WDFAD-DBR. WDFAD-DBR not
only consider the current depth but also considered the expected next hop.
Proposed protocol reduces the EC and E2E delay efficiently.
Authors in [18], implemented a new strategy for data-centric communication
based on the named data network in wireless sensor networks. Efficient commu-
nication is achieved by the authors. Additionally, this paper also presents the
modification in named data network to maximize the performance of communi-
cation. Reverse path creation is specifically discussed in this paper for the next
hop node selection. Broadcast nature of the wireless channel is introduced by
the authors in this paper. Proposed protocol minimize the redundant transmis-
sions efficiently. In [19], the authors proposed an adoptive status update method.
This method minimizes the limitations of beacon messaging. A quality of service
solution is presented for real-time applications. The proposed protocols divide
the traffic into different types to make better understanding. EC is reduced by
the authors with a fair distribution of traffic.
In [20], an adoption method to aggregate the network resources of smart
devices is proposed. The resource adoption is dynamic. The trade-off between
the number of smart devices and throughput is also discussed by the Toawa et al.
In [21], an algorithm named Cooperation Forwarding Data Gathering Strategy
Based on Random Walk Backup (CFDGSBRWB) is proposed to prolong the
network lifetime in wireless sensor networks. CFDGSBRWB Consists of data
back up based random walk method and cooperating data gathering strategy.
Proposed method reduces the packet loss ratio enhance fault tolerance, signifi-
cantly. Gupta et al. formulate a dynamic mesh routing algorithm in [22]. Pro-
posed algorithm considers both static and dynamic traffic demand. Proposed
algorithm provides optimal performance for all traffic demands.
3 System Model and Description
In this section, we discussed the system models of our proposed protocols. The
system models of the proposed protocols are presented and discussed in detail.
In state-of-the-art protocols, WDFAD-DBR and CB-WDFAD-DBR are
implemented. WDFAD-DBR considers two metrics for the selection of next for-
warder: depth of the node and 2-hop neighbor’s information to find the next
forwarder [17]. However, there exits some chances of the void hole occurrence.
532 M. Awais et al.
Fig. 1. System model of SPB-WDFAD-DBR
Fig. 2. System model of BFSPB-WDFAD-DBR
Cluster-Based Adoptive Routing Protocols in UWSNs 533
In CB-WDFAD-DBR [5], cluster formation reduces the APD to reduce the colli-
sions between packets for reliable data delivery. The CB-WDFAD-DBR protocol
performs transmission range adjustment which needs extra power to adjust their
transmission range. The transmission range adjustment keeps maximum neigh-
bor relay nodes in its transmission range. Therefore, two cluster-based routing
protocols SPB-WDFAD-DBR and BFSPB-WDFAD-DBR as shown in Figs.1
and 2are proposed. Basically, both proposed protocols formulate clusters based
on ‘Dijkstra’ and ‘Breadth First Search (BFS)’ algorithm to make the routing
path shortest and efficient for reliable packet delivery. This strategy minimizes
the possible collisions due to clusters formation and reduces the probability of
void hole occurrence. The energy dissipation during transmission is minimized
which will be used later in adaptive transmission range adjustment. The trans-
mission range adjustment extends the transmission range of the current node
and makes the transmission continuous without any hindrance.
In proposed protocols, we have formed clusters to restrict the wireless chan-
nels to avoid collisions. In both protocols, the 3-dimensional network architecture
with multiple sinks is supposed [5], which is composed of relay, anchor and sink
nodes as shown in Figs. 1and 2. The relay nodes are placed at different depths,
which receives and forward the data packets towards the sink by collecting the
data packets from anchor nodes, while anchor nodes are fixed at the bottom of
the sea surface. These anchor nodes are basically used to sense the data and to
gather the data. Meanwhile sink nodes are at the surface of the sea and housed
with both radio and acoustic modems to communicate with the nodes deployed
in the water and in the terrestrial environment, respectively. Additionally, it is
supposed that sink nodes have high energy and they know the location of all
relay nodes. The relay nodes are deployed by considering the mobility capability
of sensors and assumed the initial deployment is randomly done using planes or
ships to cover the desired area. The relay nodes collect the data packets which
are then forwarded to their Cluster Head (CH) and then that CHs forwards
the data to the destined sink. The radio modems are used for communication
between the sinks and different control stations. While, acoustic waves are used
for communication between relay and anchor nodes. The transmission process is
followed by different clusters having CH and relay nodes. In each cluster, there
exists a CH which receives the data packets from the relay nodes and transmit
the packets to next forwarder CH existing in its transmission range. The CH and
simple relay nodes can directly transmit the data packets towards the respective
sink if that node or CH finds a sink directly in its transmission range. Initially,
their exits no CH in the network. Meanwhile, the CH is selected on the base of
the maximum residual energy node. Based on that residual energy ‘Dijkstra and
BFS’ algorithm provides the shortest possible path from source node towards
the destination sink. The shortest path nodes are then selected as CH and these
CHs collect the information from their neighbors using relay nodes, if anchor
node is not directly in the communication range of respective CH and then for-
ward aggregated data towards the next CH. In this way, data is transmitted to
the destined sink using CH to CH transmission. The process remains continuous
534 M. Awais et al.
until all packets reaches the sink node. The sink nodes are positioned at the sea
surface to destine the packets to the control centers. In the proposed protocols
system model, we assumed that:
– The sinks are connected with other sinks to balance the data packets flow.
– If a packet is acknowledged at the sink, it is supposed that packet is success-
fully transmitted to the control station.
3.1 Proposed Protocols
In this subsection, the detail description of the proposed protocols and their
algorithms is presented.
SPB-WDFAD-DBR: In SPB-WDFAD-DBR, ‘Dijkstra’ algorithm is used to
find the shortest efficient path from source node to destined nearest sink. The
selected nodes using ‘Dijkstra’ algorithm are selected as CH. The CHs collect the
data packets from their neighbor nodes available in their transmission range. If
some of the nodes are out of range then protocol performs adaptive transmission
range adjustment to keep the maximum neighbors in its transmission range. In
addition, CH to CH transmission begins. Finally, the data packets reach the
destined sink. These sinks handover the data packets to the respective control
station.
BFSPB-WDFAD-DBR: In BFSPB-WDFAD-DBR, ‘BFS’ algorithm is used
to select the shortest routes in breadth vise. Then, opportunistic routing is per-
formed by our routing protocol. The route with a minimum active number of
nodes is selected as the final route. These nodes after checking their residual
energy perform the job of CH. The CHs collect the data from their neighbor
nodes and this CH communicate with their neighbor CHs and finally transmit
the packets to the destined sink. Then, sinks transmit the packet to the base
station to make the communication successful.
4 Simulations Results and Discussion
In this section, evaluation of the proposed protocols against state of the art
protocols, i.e., WDFAD-DBR [17] and CB-WDFAD-DBR [5] is evaluated. The
detailed description is given in the following subsections.
4.1 Simulations Setup
In the simulation environment, nodes are deployed randomly in UWSN environ-
ment of dimensions 10 ×10 ×10 km3with 9 sinks. We assume the transmission
range, DR and PS of nodes up to 300 m, 16 kbps, and 72 bytes [5], respectively.
The total energy of network is initialized with 100J; where the EC during recep-
tion of the data packets and transmission rate during the transmission is kept
Cluster-Based Adoptive Routing Protocols in UWSNs 535
158 mW and 50 W. During the network execution the nodes deployment varies
from 100–500, which are basically anchored with 10 relay nodes. To control
the node’s movement, node propagation speed in seawater is considered up to
2 m/s. Moreover, the propagation speed of the acoustic wave is kept 1500m/s
along with 4 kHz bandwidth. In the proposed protocols, relay nodes are placed at
different depth, which receives and forward the data packets towards the sink by
collecting the data packets from anchor nodes. Acknowledge packet size is kept
50 bits in the network along with the header size of 11bytes in data packets. The
comparative analysis is performed against the state-of-the-art protocols [5]and
[17].
4.2 Performance Metrics
In this subsection, the performance of the proposed protocols, in terms of EC,
PDR and delay.
4.3 Performance Comparison
For the performance comparison, we performed a comparative analysis of our
proposed protocol with two states of the art protocols. Comparative analysis is
performed in terms of EC, PDR and E2E delay.
100 150 200 250 300 350 400 450 500
Node Numbers
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
Residual Energy (J)
WDFAD-DBR
CB-WDFAD-DBR
SPB-WDFAD-DBR
BFSPB-WDFAD-DBR
Fig. 3. Residual energy (J)
536 M. Awais et al.
Residual Energy: The remaining energy of the nodes after the communication
is defined as the residual energy of the network. The residual energy of the pro-
posed and state of the art protocols. It is clearly demonstrated from the Fig. 3
that with the increase in a number of nodes EC also increases. Figure 3shows
that the residual energy of WDFAD-DBR is higher than CB-WDFAD-DB and
proposed protocols. The reason for least EC in WDFAD-DBR is that WDFAD-
DBR consumes energy during depth adjustment and forwarding area division
only to get the neighbors information. Meanwhile, in CB-WDFAD-DBR, the
extensive energy is consumed on adaptive transmission range adjustment and
during the communication phase. Cluster formation and participation of every
node in the transmission also results in high EC in CB-WDFAD-DBR. The pro-
posed protocols adaptively adjust their transmission range in the network, when
the current node finds no node in its transmission range. The power saved during
the shortest path based clustering and breadth-first shortest path based cluster-
ing is used as the extra power needed for this transmission range adjustment.
Then, the current node forwards the data packets to the forwarder node with-
out any packet loss using the 2-hop neighbor’s information. In both proposed
protocols, clustering mechanism is adopted which increases the EC of the nodes
with affordable E2E delay. It is clearly demonstrated from the figure that the
EC varies directly with the increase in the number of nodes, which results in a
continuous decrease in the residual energy.
Fig. 4. Packets delivery ratio
Cluster-Based Adoptive Routing Protocols in UWSNs 537
PDR: The PDR of both existing and state of the art protocols is shown in Fig. 4.
Both proposed protocols are depicting almost similar behavior. In both protocols,
PDR is increasing as the number of relay nodes is increasing (high nodes density).
The main reason behind this enhanced PDR is that probability of void hole
occurrence decreases with the increase in nodes density. In all aforementioned
protocols, the probability of void hole occurrence is trying to be minimized. The
state of the art protocol named WDFAD-DBR considers only 2-hop neighbor’s
information for further nodes selection which does not completely eliminates the
chance of void hole occurrence. This chance of void hole occurrence results in
packet drop, and decrease in PDR. The PDR of CB-WDFAD-DBR is slightly
higher than WDFAD-DBR because of clustering. The void hole occurrence is
completely minimized in the proposed protocols which increase the lifespan of
the network with high PDR.
From the Fig. 4, it is clearly demonstrated that proposed protocols outper-
formed in terms of PDR than WDFAD-DBR and CB-WDFAD-DBR protocols.
In both proposed protocols, each CH is selected using the ‘Dijkstra and BFS’
algorithm on the basis of their residual energy. Afterward, CHs to CHs com-
munication begins to transmit the data from the source towards the destined
sink. Meanwhile, CH nodes adjust their transmission ranges adaptively as per
requirement. In both proposed protocols, packet drop ratio is lesser than both
benchmark protocols. Hence, both proposed protocols have high PDR.
Fig. 5. E2E delay (s)
538 M. Awais et al.
E2E Delay: The E2E delay of existing and proposed protocols is shown in
Fig. 5. Delay of WDFAD-DBR is less than other clustering protocols because
WDFAD-DBR finds the next forwarder on the base of the node’s depth differ-
ence, which decreases E2E delay because of depth based next forwarder node
selection. The CB-WDFAD-DBR and proposed protocols overcome the void
hole problem that results in affordable E2E delay. In SPB-WDFAD-DBR and
BFSPB-WDFAD-DBR the network forms clusters to minimize the APD which
directly affects E2E delay of the network. However, with the increase in node
density number of collisions between the packets increase and packets have to
be transmitted again. In addition, transmission range adjustment also consumes
some time during which CH holds the data packets. Therefore, it is evident from
Fig. 5that proposed protocols have high PDR by paying the cost of delay.
4.4 Performance Trade-Off
In this subsection, we review the existing and proposed protocols to discuss the
existing trade-offs. The proposed protocols outperform in adaptive transmission
range adjustment to keep maximum neighbors in its transmission range. The
extra cost needed to fulfill this adjustment is saved by minimizing the APD
in our proposed protocols. During clustering of nodes in proposed protocols, we
noticed an existing trade-off between the two performance parameters: PDR and
EC. The PDR is enhanced on the cost of EC which increases the reliable data
delivery.
5 Conclusion and Future Work
In this paper, energy efficient routing protocols are proposed for reliable data
transmission. These routing protocols enhance the network lifespan and reduce
the probability of void holes generation by adjusting the transmission range of
the nodes, adaptively. In addition network lifespan is increased. The proposed
protocols enhance the PDR with affordable E2E delay and by paying the cost of
EC. The proposed protocols use the ‘Dijkstra and BFS’ algorithm and fulfill the
need of extra power needed for adaptive transmission range adjustment. This
adjustment keeps maximum neighbors in its transmission range for maximum
data collection. Simulations show the efficacy of the proposed protocols. In the
future, we will minimize the packet drop ratio and E2E delay further by using
artificial intelligence and data science techniques.
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