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EEHR: Energy Efficient Hybrid Routing Protocol for Underwater WSNs

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EEHR: Energy Efficient Hybrid Routing
Protocol for Underwater WSNs
Muhammad, Nadeem Javaid, Sheraz Hussain, Taimur Hafeez, Hammad Maqsood, Syed Zarar
Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan
nadeemjavaidqau@gmail.com, www.njavaid.com
Abstract—Energy is a main issue in Underwater Wireless
Sensor Networks (UWSNs). The wireless sensor nodes in un-
derwater network have limited source of energy (batteries) and
replacement of their batteries is very difficult and costly. Hence,
energy efficiency has always remained as a major concern in
UWSNs. Moreover the variation in energy consumption of nodes
reduces the network lifetime and creates network holes. Com-
bination of multi-hop transmission and direct communication
were proposed before to balance the energy consumption between
nodes. Direct transmission of data packets to sink depletes more
energy of sensor node as compared to multi-hop transmission.
When The nodes which reside at a greater distance from the sink
opt for direct communication, their energy rapidly decreases.
Thus resulting in shorter network lifetime. This paper presents
Energy Efficient Hybrid Routing Protocol (EEHR). This protocol
is a hybrid between multi-hop and direct transmission to the
neighbors residing in the sub neighbor region. In this paper the
direct transmission distance is decreased and it is refined to a
sub neighbor region, which increases the network lifetime and
reduces the energy consumption of the network. There are 4
regions of different radii from the sink created in our proposed
protocol. The regions are in the form of semi circles beneath the
sink node. Equal number of nodes are deployed randomly in each
region. Neighboring lists are created by the nodes on the basis
of their optimum distance to the sink. Simulation results show
improvement in the network lifetime and energy consumption of
the network.
I. INTRODUCTION
Water is the lifeblood of earth and human. About 50% of
the worlds population lives in coastal area, yet only 5% of
underwater world is explored while the rest of 95% remains
unexplored. Recently with the advancement of technologies
and awareness of the underwater importance, underwater re-
search has attracted attention from both academia and industry
due to its importance to humankind. Food, mines, business,
security, transportation, communication, all are related with
the oceans that flow over nearly three quarters of the earth.
For exploration of underwater world, Underwater Wireless
Sensor Networks (UWSNs) are created in order to monitor
and gather information continuously from the deep underwater
areas where human cannot go there because of high cost beside
other reasons. Radio waves are used for communication in
terrestrial networks, but due to harsh environment of underwa-
ter, the techniques used for terrestrial networks are not suited
for underwater atmosphere. Also radio waves cannot travel
for long distance in underwater. Underwater Acoustic Sensor
Network is a subclass of UWSN in which acoustic signals are
used. Acoustic signal have relatively low absorption rate in
underwater and have frequency range between 10 kHz and 1
MHz. It can travel to longer distance in underwater because
of its lower frequency than radio waves which have frequency
range between 3 kHz and 300 GHz, however due to low speed
of acoustic signal (1500 m/s) it causes high delay in data
communication.
UWSNs are used for various purposes including pollution
control, prediction of natural disasters, exploration of under-
water life, search and extraction of natural resources, military
applications, monitoring water traits (salinity, temperature,
oxygen levels, etc). One of the major constraints in UWSNs
is the limited energy (battery) of sensor node. Charging
or replacement of underwater sensor node’s battery is very
difficult operation and costly. Energy efficiency in UWSNs
is the basic requirement to achieve longer network lifetime.
Energy Balanced Hybrid Protocol[1] and DBEBH protocol[2]
combines multi-hop communication and direct transmission,
due to which the energy is balanced to some extent between
sensor nodes. But because of direct transmission of data from
sensor nodes to sink node (especially from the farthest nodes),
the energy consumption of the network is increased which
effects the network lifetime and creates network holes.
In this paper we emphasize on reducing the energy con-
sumption of the network by avoiding direct transmission by
far deployed sensor nodes from the sink. We created 4 regions
in semicircular shape beneath the sink node which is deployed
on the surface of water. Equal number of sensor nodes are
deployed in each region. Energy Level Number (ELN) is
maintained for every sensor node for maintaining balanced
energy consumption in the network. The energy of nodes
which are deployed in region 1 and 2 set more than energy
of nodes in region 3 and 4. Instead of depth based routing,
we calculate every nodes Euclidean distance to the sink
and establish links between them based upon their optimum
distance threshold and maintain all neighboring node’s IDs in
each link. Each link consist of IDs of 4 neighboring nodes of
different regions. Normally every node forward the data to the
neighboring node which resides in the next region toward the
sink. When the relay node ELN decreased it sends control
packet to its neighboring node of previous region (higher
radius region), the node receiving the control packet finds
another neighbor of high ELN, if it fails than it transmit the
data to sub neighboring node (e.g, from region 3 node to region
2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications
978-1-4673-8315-8/15 $31.00 © 2015 IEEE
DOI 10.1109/BWCCA.2015.86
20
2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications
978-1-4673-8315-8/15 $31.00 © 2015 IEEE
DOI 10.1109/BWCCA.2015.86
20
1 node). Communication returned to multi-hop method when
the sender node energy level number became less or equal to
the relay node ELN.
The rest of the paper is organized as following: Section 2
consist of review of some related routing protocols. In section
3 motivation is discussed. Section 4 includes description of
our proposed protocol, EEHR. In section 5 we evaluate the
performance of our proposed protocol and at the end in section
6 we state the conclusion.
II. R
ELATED WORK
Due to harsh environment of underwater, minimizing and
balancing energy consumption of sensor nodes in routing layer
becomes one of the main focus area for the researchers, as
this is considered one among the suitable possible solution for
the energy and network lifetime problem in UWSNs. In [3] a
cross-layer approach is defined where different transmission
power levels are used during the forwarding of the data
packet. Transmitter of data sends an RTS packet with some
transmission power level. If a CTS reply is reached from
a forwarder node that is near to the sink node, the data
transmitted to the forwarder node. Else, the transmission power
level is increased to a higher level. The limitation of this
protocol lies in delay and excessive energy consumption by
exchange of RTS and CTS during data forwarding.
In [4] OEB has been proposed. In this network model each
lower depth node forwards the data received from all higher
depth nodes, which is the main reason of imbalanced energy
consumption. To overcome this problem, OEB combines both
the multi-hop and direct communication method. Sensor nodes
switch between the two communication modes on the basis of
comparison between energy levels of sender nodes and their
immediate neighboring nodes.
In MTE [5] each sensor node always forwards the data
packets to its neighboring node towards the sink node. The
issue of classic multi-hop transmission is that the nodes close
to the sink dies very soon due to over burden of forwarding
data packets operation.
DBR [6] considers a localization free randomly deployed
network model. Depth of nodes only taken as a routing deci-
sion metric. Higher depth nodes forward data to lower depth
nodes that are within their transmission range. The process
continue till data reach to the surface of water. It is a receiver
based approach, where the receiving nodes decide whether to
re-forward the received data or drop it. Holding time criteria
is employed to avoid the retransmissions of same packet from
different nodes. Limitation of DBR protocol is that it only
uses the depth of nodes without considering remaining energy
of nodes. Also in DBR there is no methodology for energy
balancing between the nodes. EEDBR [7] is the improved
version of DBR protocol, in which residual energy of node
is considered along with the depth.
In [8] ultrasonic frog calling algorithm is proposed based
on the calling characteristic of ultrasonic frog. The forwarder
node selection scheme is based on calling characteristic of
ultrasonic frog. Farthest nodes of low residual energy turn to
sleep mode for reserving energy. Jiabao Cao in [9] proposed a
balance transmission mechanism. It splits the process of data
routing into two steps. In the first step, a tree of nodes (which
is routing path) is created on the basis of optimum transmission
distance. In the second step data routing algorithm is designed.
Single hop and multi-hop communication are used in order to
balance the energy consumption. Energy grades used to switch
between the two methods of communication of sensor nodes.
In [10] the authors present a novel geographic and partial
network coding based routing protocol for UWSNs called
GPNC. This protocol reduces the number of transmitting pack-
ets and collision between packets, by using partial network
coding for data delivery. GPNC can improve the network
delivery rate and reduce the energy consumption as well as
network delay.
(H2-DAB) Routing Protocol is proposed in [11]. H2-DAB
uses hop by hop data transmission method in a randomly
deployed network in which multiple sink nodes are deployed.
This protocol claims the cost effectiveness because it does not
need special sensors modules for tracking depth or location of
nodes.
Random Access Compressed Sensing (RACS) is pro-
posed in [12]. The RACS scheme is a distributed energy-
efficient sensor network, suitable for long-term large under-
water networks in which saving energy is very important.
This scheme prolongs network lifetime employing distributed
scheme which eliminates the requirement of scheduling. 4-
chains, 2-chains and single chain based cylindrical network
model is discussed in [13]. Nodes connect with each other
forms a chain like network, then nodes calculate their global
optimum neighbor and connect themselves with the nodes in
other chains, that results in increasing the throughput, reducing
the end to end delay and prolonging the network lifetime.
In [14] An energy efficient routing scheme for throughput
improvement in WSN is presented. The proposed scheme
exploits multi layer cluster design for energy efficient forward-
ing node selection, cluster heads rotation and both inter and
intra cluster routing. Throughput is improved because the role
of cluster head rotates among various nodes based on two
threshold levels which reduce the number of dropped packets.
Energy Balanced Hybrid protocol (EBH) in [15] combines
both the Multi-hop and the Direct communication methods. It
targets the scattered deployed networks. In this protocol every
node transmit its sensed data along with data packets of its
higher depth neighboring nodes, due to which the nodes of
lower depth (closer to the sink) have rapid energy reduction,
which results in network hole problem. DBEBH [2] is the
improved form of EBH, in which nodes randomly deployed
and energy grades maintained to switch between multi-hop
communication and direct transmission of data. When the
energy grade of a relay node decreased, it sends control
packet to its high depth neighboring node which in turn
changes its transmission mode from multi-hop mode to direct
transmission mode. Limitation in DBEBH Protocol is that the
sensor nodes of high depth consume a lot of energy during
direct transmission of data packets to the sink.
2121
A new regional energy aware clustering method called Re-
gional Energy Aware Clustering with Isolated Nodes (REAC-
IN) is proposed in [16]. In this method, cluster heads are
selected based on weight. Weight is determined according to
the residual energy of each sensor and the regional average
energy of all sensors in each cluster. Due to improper design
of distributed clustering algorithms, nodes become isolated
from cluster heads. These isolated nodes communicate with
the sink by consuming high amount of energy. The REAC-
IN protocol improves the cluster head selection process and
minimize the node isolation issue. In [17] an energy-efficient
data transmission scheme presented, called EGRC (Energy-
efficiency Grid Routing based on 3D Cubes) in Underwater
Acoustic Sensor Networks. The network lifetime In EGRC
extended by selection of the optimal cluster heads, taking
energy and location of sensor nodes into consideration.
III. M
OTIVATION
Improving network lifetime in UWSNs is very important
due to limited energy of sensor nodes. Protocols such as
DBEBH combines multi-hop and direct transmission of data to
sink. In case of direct transmission the energy of higher depth
nodes (farthest nodes) falls rapidly, which causes increase in
energy consumption of the network and leaves the farthest
region of the network unsensed, that yields the decrease in
total number of packets received at sink. Decreasing the trans-
mission distance of data results in decrease in the transmission
energy of nodes and increase in the network lifetime.
IV. N
ETWORK MODEL
In this section we describe our proposed protocol in de-
tail. This section includes two subsections: Architecture and
Operation.
A. Architecture
The network architecture we have considered consists of
a sink node deployed on the surface of water, sensor nodes
underwater and 4 logical regions of different radii where
sensor nodes are deployed. Sink node is equipped with radio
frequency as well as acoustic modem. Data packet reached to
the sink is considered as delivered data due to fast speed of
(RF) via which sink node communicate with the base station.
4 regions in the form of semi circles reside beneath the
sink node. Region 1 resides directly beneath the sink. Region
2 beneath region 1 and so on up till region 4. Thus meaning
region 4 is the farthest region from the sink. Region 1, 2, 3,
and 4 radii are 100 m, 200 m, 300 m, and 400 m respectively
from the sink. The network dimensions are shown in figure 1.
Total 100 sensor nodes are randomly deployed equally in all
4 regions.
The sensor nodes deployed in region 4 and 3 are homoge-
nous, while the energy of sensor nodes deployed in region
2 and 1 are respectively 2 and 3 times more than energy of
nodes deployed in other regions. The reason of increasing the
energy of nodes in region 1 and 2 is the high over burden
of forwarding data packets on nodes that are nearly deployed
from the sink.
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Fig. 1: Network Model of EEHR Protocol
B. Operation
The technique used in our proposed protocol is similar as
used in EBET [18] protocol but with different architecture. In
EBET homogeneous sensor nodes deployed in regions formed
in circular shape around the underwater sink node. In our
proposed protocol the sink node deployed on the surface of
water, 4 regions are formed in semi-circular shape around
the sink node as discussed in section 4. Homogeneous sensor
nodes are deployed in Region 3 and 4, while higher energy
sensor nodes are deployed in Region 1 and 2. Transmission
power control model is embedded in sensor nodes [19]. Data
transmission occurs by two methods: multi-hop or transmis-
sion to sub neighboring node i.e. (transmission from node in
region 4 to node in region 2 or from region 3 to region 1).
There are two phases of Operation: Route Formation and Data
Transmission.
1. Route Formation:
All nodes coordinates are known including sink node.
They share their position information with each other and
based upon their optimum distance threshold (O
t
) value, they
form links with each other. Nodes exchange their location
information along with their distance to sink. Each node find
its neighbors using N
j
= α|d(j, i) O
t
| + αd(j, s) where
α is a system parameter and its value set as 0.5, d(j, i) is
the distance between two nodes, and d(j, s) is the distance
between node j and the sink. The values of optimum distance
threshold (O
t
) for node’s transmission distance is calculated
using [20]. With the help of N
j
calculation, a sensor node
selects a relay node at optimum distance nearer to sink. as
shown in figure 3.
This phase takes place in the first round, and repeat after
every round in which a sensor node of any Region dies.
2. Data Transmission:
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Fig. 2: Data Transmission in EEHR Protocol
After route formation, we use concept of energy level
number (ELN) for balancing energy between the nodes. ELN
calculated as
ELN = E
0
/M
where E
0
is the initial energy of sensor node, and M is total
energy levels.
Initially nodes transmit data via multi-hop method. When
the ELN of a relay node decreases, it remains in multi-hop
transmission but sends only its own sensed data packets, also it
generates and sends control packet to its predecessor neighbor
node informing to stop forwarding data to it. The predecessor
node in turn tries to find another relay node of higher ELN and
forwards data to it. If there is no node of higher ELN, than
the node shifts from multi-hop transmission to the mode of
direct transmission to sub neighboring node of higher ELN in
the sub neighbor region. This process continues till the ELN
of sender node became less or equal to its successor or relay
node. After that multi-hop transmission starts again, as shown
in figure 2.
For example, in case of decrease in ELN of a relay node
locating in region 3, so its predecessor node which is locating
in region 4 transmits data directly to sub neighboring node in
region 2. Also if the ELN of the relay node locating in Region
2 decreased, its predecessor node Directly transmit data from
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)
Fig. 3: Route Formation in EEHR Protocol
region 3 to Region 1 node. In the same way if the ELN of a
relay node locating in Region 1 decreased, so its predecessor
node directly transmits data from region 2 to the sink, as shown
in figure 1.
As soon the ELN of predecessor node become less or equal
to the relay node, the transmission mode switch back to multi-
hop transmission. In case any node dies in any of the 4 regions,
the first phase of route formation takes place again. By this
way we balanced energy consumption between nodes, and
increased the network lifetime.
V. P
ERFORMANCE EVALUATION
This Section is divided into 3 sub sections which are: Per-
formance Metrics, Performance Trade-off Made by Protocols,
and Performance Discussion.
2323
TABLE I: Network Parameters
Simulation Parameters Values
Number of Nodes Deployed 100
Initial Energy of a Node 70J
Data Packet Size 1000 bits
Control Packet Size 48 bits
Total Energy Level 1870
A. Performance Metrics:
In this section we evaluate the performance of our network
by using following metrics:
Network lifetime: Network lifetime is the time till the death
of first node in a network when the node energy is fully
exhausted.
Alive nodes: The number of nodes having enough energy for
communication in a network.
Energy consumption: Amount of energy that is consumed by
all deployed nodes in every complete round.
B. Performance Trade-off Made by Protocols:
Table 2 shows the performance trade off made by protocols.
DBEBH enhances the network lifetime by sacrificing the
energy consumption of the nodes. In DBEBH nodes which are
deployed far from the sink consume more energy during direct
transmission of data packets to sink. In EEHR Protocol we
increased the network lifetime as well as reduced the energy
consumption of the network by reducing the distance of direct
transmission, and increasing the initial energy of nodes which
are deployed in region 1 and 2 (near to the sink). Because the
nodes which are deployed near to the sink have high burden
of data packets forwarding. We bounded direct transmission to
sub neighboring node, due to which the energy consumption of
the network reduced, but the number of packets transmission
increased.
C. Performance Discussion:
Two networks of architecture explained in section 4 are
being considered. One perform DBEBH protocol (combination
of multi-hop and direct transmission) in routing the data,
while the other (EEHR) employ combination of multi-hop and
transmission to sub neighboring node. Basic parameters are set
same for both protocols.
In figure 4 and 5, the network life time of DBEBH and
EEHR is compared. DBEBH employs combination of multi-
hop and direct transmission technique. Because of direct trans-
mission technique, the higher depth nodes lose their energy
faster. The reason is that they transmit their data packets over
a long distance to the sink, which result in rapid decrease
in their energy. In EEHR instead of direct transmission, the
lower regions nodes forward data packets to sub neighboring
nodes in sub neighbor regions. The receiver nodes forward the
received data packets to the sink via multi-hop transmission.
By this way the distance of direct transmission of data packets
is decreased which save noticeable amount of energy of nodes
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Fig. 4: Dead Nodes per Round
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Fig. 5: Alive Nodes per Round
in lower regions and increase in the network life time as shown
in the figure 5.
The burden of data packets forwarding is high on nodes in
region 1 and 2 because of receiving and forwarding data of
lower regions nodes (region 3 and 4 nodes). In order to make
the network life time longer and balance energy consumption
between nodes, we initially increased the initial energy of
region 1 and 2 nodes. In DBEBH Once the nodes in region
3 and 4 (lower regions nodes) dies, the graph of dead nodes
become somehow smooth because of low distance difference
of remaining alive nodes from the sink, same in EEHR too.
Figure 6 shows per round energy consumption comparison
of DBEBH and EEHR. Clearly we can see that in this network
model, the energy consumption of DBEBH is more than
EEHR in early rounds. The reason is that of high energy
dissipation in case of direct transmission of data packets from
nodes that deployed far from the sink. The distance is directly
proportional to the transmission energy of data packets. In our
protocol, instead of sending data directly to sink, we reduce
the distance of direct transmission of data packets to sub
neighboring node in the sub neighbor region. Due to which
2424
TABLE II: Performance trade-off made by protocols
Protocol Achieved Parameters Figure Compromised Parameter Figure
DBEBH Network Lifetime Figure 4 and 5 Energy Consumption Figure 6
EEHR Network Lifetime Figure 4 and 5 Packet Transmission Figure 1
EEHR Network Lifetime Figure 4 and 5 Energy of Nodes Near Sink Figure 1
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#
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Fig. 6: Energy Consumption of Network
     ! " # $
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!
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#
$

%

 

Fig. 7: Packets Received at Sink
the energy consumption of nodes decreased, and the network
lifetime increased so that nodes can function for a longer time.
Figure 7 shows the total number of data packets received
at sink. In DBEBH the farthest nodes die first due to high
energy consumption in case of sending data packets over a
long distance to the sink. Total data packets received at sink
decrease by death of nodes. In EEHR the alive node ratio per
round is better than DBEBH, Which directly effect on total
number of data packets received at sink.
VI. C
ONCLUSION
Transmission of data packet by sensor node over a long dis-
tance consumes more energy. Our protocol is hybrid between
multi-hop and direct transmission but direct transmission is
bounded to sub neighboring node. By this way we reduce the
distance of direct transmission and the energy consumption of
the network. In our model the nodes in region 1 and 2 (nodes
which are deployed near to the sink) are overburdened, so we
increase their energy, hence the network lifetime extended and
energy consumption of the network reduced.
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