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Improved Adaptive Cooperative Routing Protocol for Underwater Wireless Sensor Networks

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Improved Adaptive Cooperative Routing in
Underwater Wireless Sensor Networks
Sheraz Hussain, Nadeem Javaid, Syed Zarar, Muhammad Zain-ul-Abidin, Mudassir Ejaz,Taimur Hafeez
Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan
nadeemjavaidqau@gmail.com, www.njavaid.com
Abstract—In Underwater Wireless Sensor Networks (UWSNs),
reliability is an important factor which effects the overall
performance of the network. As the underwater environment
is noisy and due to multipath fading and poor link quality, the
reliability of the network and data integrity is affected. With
cooperative routing, the reliability and the integrity of the data
is improved. In this paper two relay nodes and a master node
is selected for the transmission of data from source to the sink.
Master node is selected among the neighbouring nodes which
has low depth, high residual energy and must lie outside the
threshold defined. On the basis of depth threshold of source
node and the master node, two relay nodes are selected for the
retransmission mechanism. Simulation results show that IACR
achieves better results with respect to packet acceptance ratio,
throughput, network lifetime and packet drop as compared to
ACE.
I. INTRODUCTION
Underwater Wireless Sensor Networks (UWSNs) consists
of sensor nodes that are deployed over a given region to
perform monitoring tasks. UWSNs have gained popularity
because these networks offer many applications including
environmental monitoring, resource investigation and disaster
prevention [1].
UWSNs have different characteristics than terrestrial networks.
The main difference is the usage of acoustic signals over radio
signals,which are used in terrestrial sensor networks. Acoustic
signals have long end to end delay and have limited bandwidth
due to attenuation so the efficient and quality routing in
UWSNs is one of the major problem. [2].
In underwater environment, due to the use of acoustic signals,
the data signal suffers fading and path loss. Most of the packets
do not successfully reach the destination. Some packets are
received at destination but due to multipath fading, the error
rate is high and the data is not received in its original form.
Forward Error Correction (FEC) is an excellent technique to
improve the error rate performance and also a way to obtain
reliable data transmission. In this technique, the source node
sends the same data through multiple paths and the destination
node receives the data packet that contains no apparent errors
[3].
Cooperation is defined as the act of working together for a
common purpose [4]. Cooperative routing can be implemented
in UWSNs as it makes the routing process more efficient than
other approaches such as multi-hoping. In cooperative routing,
the data signal is forwarded from source node to destination
node and is also over-headed by relay nodes. The relay nodes
send the data signals to the destination by relaying process.
The relaying process schemes that are used at relay nodes are
Amplify and Forward (AF) and Decode and Forward (DF). In
AF, the relay node amplifies the given signal and transmits it
to the destination. In DF, the relay node corrects the signal and
transmits it to the destination. Equal Gain Combining (EGC)
technique is the diversity combining technique which is used at
the destination node to improve the quality of the data signal.
[5]
In this paper, we proposed a new protocol named as Improved
Adaptive Cooperative Routing (IACR). IACR is introduced as
a successor of an already existing protocol called Adaptive
Cooperation in EEDBR (ACE). IACR improves the reliability
and the network lifetime which was previously achieved in
ACE.
In IACR relay nodes are selected for the retransmission of the
data to the destination which is sent by the source node. The
relay nodes forwards data in case the destination node does
not receive the original data from the source node. The benefit
of using relay nodes is that the destination node receives the
original data with no errors and in case the destination node
receives erroneous data from the source node, the source node
does not have to retransmit the same data because relay nodes
do this job so the overall energy of the network is balanced
and the lifetime of the network is improved. The idea of this
cooperative routing is taken from [6].
The rest of the paper is organized as follows: related work and
motivation is discussed in section II and III respectively. Sec-
tion IV gives the network model for the energy consumption.
Section V has details about the working of proposed scheme.
Simulation results are presented in section VI. Finally, this
paper is concluded on section VII.
II. RE LATE D WORK
Nowadays, a lot of research has been carried out on the
cooperative routing protocols of UWSNs.
In [7], cooperative transmission mechanisms are presented
to improve energy consumption and packet acceptance ratio.
Relay nodes are selected on the basis of distance from the
sink and on the basis of signal-to-noise ratio.
Authors in [8], proposed a new scheme Cooperative Hybrid
Automatic Repeat Request (C-HARQ) to improve the packet
acceptance ration and maximize the energy efficiency and
throughput of the network.
A multi-hop cooperative transmission protocol is proposed
in [9] for the transmission of data packets from cooperative
nodes. In this protocol, each hop is arranged into two time
slots (inter-cluster slot and intra-cluster slot) to construct the
cooperative transmission. An optimization model is developed
to find the minimum number of cooperative nodes.
In [10], authors proposed different techniques for the
determination of minimum density and optimal location of
relay nodes to ensure the connectivity.
Energy Efficient Depth Based Routing (EEDBR) in [11],
is proposed which is the improved version of DBR. This
scheme uses the local depth information of nodes along with
their residual energy to forward data towards the destination
node
In [12], author propose superior path planning mechanism
named as Z-curve. This scheme helps to localize the sensor
nodes.
A scheme for the selection of relay nodes for cooperative
underwater network is proposed in [13]. In this scheme, relay
nodes are selected on the basis of propagation delay.
In [14], the relay nodes are selected on the basis of depth and
residual energy information. In the presence of Mobile Sink
(MS) source node forwards data directly to the MS. However,
in the absence of MS source node forward data to the relay
nodes which the forward data to the destination.
In Cooperative Best Relay Assessment (COBRA) [15], a
best algorithm is used for the selection of relay nodes. This
scheme requires statistical information of the link instead
of link state and improves the overall performance of the
network in terms of throughput and lifetime on the cost of
average end to end delay.
In [16], a scheme is presented in order to improve the
efficiency of the link by cooperative retransmission. Some
forwarding techniques are also presented in this scheme.
In [17], Depth Based Routing (DBR) protocol is proposed
which uses the depth information of the nodes to forward data
from source node to the destination node and uses greedy
algorithm approach.
Redi et al. introduce the concept of multi path routing in
[18]. In this scheme the data packet is forwarded to the
destination from multiple paths and in this way the throughput
is achieved.
MUAP in [19] investigates the losses in acoustic channels
and proposes an energy model for the channel losses in
underwater environment.
Authors in [20], proposed the distortion performance of
multi-hop UWSNs that experience te fading between the
channels of neighboring nodes.
III. MOTI VAT IO N
ACE is a cooperative routing protocol for UWSNs. In this
protocol, the selection of the path is based on the local depth
information and residual energy of the neighboring nodes. The
node with the low depth and high residual energy among the
neighboring nodes qualifies for the next forwarder. In ACE,
data packet during transmission suffer propagation delay and
due to the poor quality of the link, data may not reach to
the destination in its original form. Due to fading, poor link
quality, transmission loss and path loss, Bit Error Rate (BER)
is introduced and packet drop occurs, throughput performance
is degraded and network lifetime is reduced. These deficiencies
in ACE becomes our motivation to propose IACR. If a depth
threshold and retransmission for limited time is defined in ACE
then the problem of throughput performance, network lifetime
and packet drop is solved.
IV. ENERGY CONSUMPTION MOD EL
For analyzation of energy consumption model, we have used
passive sonar equation to calculate signal to noise ratio.
SN R =SL T L NL +DI DT (1)
In equation 1, SL denotes Source Level, T L is Transmission
Loss, NL is Noise Loss, DI is the Directive Index and DT
is the Detection Threshold. Transmission loss is calculated by
using Thorp model. The formula for calculating transmission
loss is as follows:
T L = 10log(d) + α(d)×103(2)
In equation 2, αis the absorption coefficient and dis the
distance between the source and destination node. Noise loss
is calculated by using equation 3:
NL =Nt(f) + Ns(f) + Nw(f) + Nth(f)(3)
Equation 3 shows the sum of noises produced due to turbu-
lence,shipping,wind and thermal activities.
The amount of energy in transmitting and receiving a data
packet by a node is given by equation 4 and 5 respectively.
ET X =Pt×(1/(attenuation ×bandwidth)(4)
ERX =Pr×(1/(attenuation ×bandwidth)(5)
where fis the frequency of the given signal. P t and P r are
the transmission and receiving power of nodes respectively.
V. PROP OS ED SCHEME
This section presents the system model and the working of
the proposed scheme. In this scheme, the source node sends
the data form 3 paths, i) source node to destination node, ii)
source node to relay1 to destination node and iii) source node
to relay2 to destination node. The destination nodes receive the
data packet from source node and in some conditions receive
from relay nodes. These conditions are discussed in detail in
protocol operation section.
A. System Model
System model consists of nodes that are randomly deployed
and act as either source, destination or relay nodes. Fig. 1
shows the proposed system model. The links that connect
these nodes suffer Ray Leigh Fading (RLF) and Additive white
Gaussian Noise (AWGN). The modulation scheme we used
in our scheme is Binary Phase Shift Key (BPSK). At the
destination node, the signals that are received are weighted
with respect to their signal-to-noise ratio and then summed.
This technique is based on assumption that all of the nodes are
synchronized with each other. Due to the limited transmission
range, data packet is routed from source to sink in multi-hop
fashion.
Y1
Y2 Y3
Y4 Y5
Source Node
Master Node
Relay Node
Fig. 1. IACR system model
A general mathematical model for the proposed scheme is
given by equation 6:
Yn=Xgn +Nn(6)
where n=1,2,3,4,5. Xis the original signal send from source
node, Yis the received signal at nodes, Nis the channel noise
and gis the gain of the channel.
B. Protocol Operation
This section presents the working of our proposed scheme.
IACR works in rounds and in every round each node transmits
data. Every round consists of three phases:
1) Initialization Phase
2) Route Establishment Phase
3) Data Forwarding Phase
1) Initialization Phase: In this phase, each node broadcasts
a hello packet within its transmission range. Hello packet
consists of source ID, depth and residual energy. Each node
broadcasts its depth and residual energy information to other
nodes within its transmission range. On the basis of this
information, neighbors are identified. This process is repeated
for all the nodes and a database is maintained at each node
containing information of local neighbors.
2) Route Establishment Phase: In this phase, a route is estab-
lished from source node to sink. This phase has two important
objectives: first is the identification of next destination and
second is the selection of relay nodes. Source node identifies
neighbors on the basis of depth information. Nodes that have
lower depth than the source node are the qualified forwarders
for the data forwarding. These nodes are included in the
forwarding list of the source node. Nodes that have greater
depth than source node are neglected. For the selection of
next destination, a master node is selected from the forwarding
list. In this process, the node qualifies to become master node
which has lower depth but outside the threshold defined and
has high residual energy.
After the selection of master node, next step is the selection of
cooperative nodes. Cooperative nodes are identified from the
nodes that lie in the cooperative region. From the cooperative
nodes, two best nodes (that have lower depth, high residual
energy and must lie outside the threshold of both the source
node and the master node) are selected as relay nodes as shown
in Fig 2. In order to control the number of relay nodes involved
in packet forwarding, depth threshold is defined.
TxRange
dth
Sensor Nodes
Source Node
Master Node
Co-opera ve Node
Fig. 2. Cooperative region and relay node selection
3) Data Forwarding Phase: In the data forwarding phase,
the data is forwarded from source to sink at a route that is
established in the route establishment phase. Source node
forwards data packet to master node and to the relay nodes.
Relay nodes holds the data packet for the certain amount
of time, this is known as holding time. At relay nodes,
the holding time for a packet is calculated based on the
difference between the depth of the source node and the
depth of the relay node itself. After the expiration of holding
time, the relay node discards the data packet. Each of the link
during packet forwarding suffers fading due to which BER
is introduced. The data received at master node is compared
with the original data sent from source node and BER is
calculated. A threshold T is defined for a BER. If the BER is
less than or equal to T, data packet is accepted and a control
packet is sent to both relay nodes and relay nodes drop the
data packet even if the holding time is not expired.
On the other hand, if BER is greater than T, the master
node sends negative acknowledgement to relay nodes and
if the holding time of any of the relay node is not expired
then the data packet is forwarded to master node otherwise
the process will be continued with another source node.
The data that is sent from relay nodes to master node is
forwarded on the basis of AF technique. At master node the
signals received from source node and from relayed node are
combined using EGC technique in order to reduce fading
and BER is compared every time the signal is received. The
selection of relay nodes every time improves the performance
and lifetime of the network but as source node sends a single
data packet through three paths so the average end to end
delay increases.
Fig.3 shows the mechanism of the protocol in the form of
flow chart
VI. SIMULATION RESU LTS AND DISCUSSIONS
We perform simulations of our proposed protocol and
compare it with existing ACE protocol. The performance of
this protocol is measured in terms of throughput, packet drop,
packet acceptance ratio, network lifetime, average end-to-end
delay and energy consumption.
A. Performance Metrics
Following performance metrics are considered: 1) Energy
consumption: It is the amount of energy consumed by all the
nodes in the network including transmission energy, reception
energy and idle time sensing
2) Packet acceptance ratio: It is the ratio of number of packets
received at sink to total number of packets that are sent.
3) Throughput: It is the total number of packets that are
received successfully at sink.
4) Packet drop: It is the number of packets that are sent but
not received successfully at sink.
5) Average end-to-end delay: The average amount of time
taken by a data packet to reach the destination from source
node.
6) Network lifetime: It is the duration of time from the start
of the network till the death of the last node.
B. Simulation Setup
Nodes are randomly deployed in area of 500m x 500m.
Simulation parameters are listed in the table I. Network is
sparse and the total number of nodes are 250. Initial energy of
each node is 70J. Total 4 sinks are deployed at equal distance
of 100m. Nodes are equipped with acoustic modem and the
sinks are equipped with both acoustic and radio modems. The
transmission range of each node is 100m and depth threshold
is also defined for each node which is 60m. The acceptable
bit error rate is 0.5.
TABLE I
SIMULATION PAR AM ETE RS
Parameters value
Number of Nodes 250
Number of Sinks 4
Area 500m x 500m
Depth Threshold 60m
Transmission Range 100m
Initial Energy 70J
Control Packet 48bits
Data 1000 bits
Acceptable BER 0.5
1) Throughput: Fig 4 shows the performance of IACR in
terms of throughput. In this plot the throughput efficiency of
IACR is compared with ACE. This plot shows the number of
packets received successfully by the sink per round. In IACR,
source node forwards the packet to the sink from master node
and from the relay nodes. As the data packet is forwarded
from source node to master node and in case the data packet
does not receive at the destination, then relay nodes do their
job and forwards the same packet to the master node, hence
more packets are received successfully by the sink because if
the packet from one link is dropped then there are chances of
packet reception from other link so the throughput in case of
IACR is improved. In IACR, as the nodes starts to transmit
data packets, the energy levels of the nodes are dropped so
after some time the throughput efficiency of IACR is degraded
however, the overall throughput of IACR is better than ACE.
2) Packet Drop: Fig 5 compares IACR, with ACE in terms
of packet drop. In the simulations, the packet is dropped when
the bit error rate at the destination node is greater than 0.5 or
when a node has no neighbor to transfer data. As the source
node forwards data to master node directly and from the two
relay nodes hence the chances of packet drop are rare because
a single data packet is forwarded from three different links. It
consumes more energy but overall performance is improved.
However, due to the presence of noise, poor link quality and
multi path fading in UWSNs, the packet drop would occur
but due to the presence of relay nodes, the retransmission of
erroneous data occurs so the packet drop in IACR is very rare
as compared to ACE. In the start, the packet drop is almost
negligible but after few rounds, as the nodes start to lose their
energy levels so the packet drop would occur.
3) Packet Acceptance Ratio: Fig 6 compares IACR with
ACE in terms of packet acceptance ratio. This plot shows the
ratio of number of packets received at the sink to the number
of packets sent. As in case of IACR, the retransmission of
erroneous data occurs and source node finds cooperative region
outside the depth threshold so this would increase average end-
to-end delay but the packet acceptance ratio is improved. In
the start the packet acceptance ratio is almost 100”%” but after
few rounds, the nodes loses their energy level and the packet
acceptance ratio decreses. In the last few rounds, as the less
nodes remain alive, so the packet acceptance ratio is 30”%”
to 40”%”, but this plot shows that the overall performance
of IACR in terms of packet acceptance ratio is improved as
YES
NO
YES NO
NO
YES
YES
NO
NO
YES
Next Itera
on
Fig. 3. IACR data transmission
0 500 1000 1500 2000 2500 3000 3500
0
50
100
150
200
250
No. of rounds
Throughput (No. of packets)
IACR
ACE
Fig. 4. Comparison of packets received at sink
compared to ACE.
4) Energy Consumption: Fig 7 shows the energy consump-
tion of IACR and ACE. Energy consumption is the amount
of energy required by a node to sense, transmit and receive
control packets and data packets. As in IACR there is a holding
time defined for the relay nodes after which they drop the data
packet and do not send data packet every time to master node
due to which the energy consumed in case of IACR is more
0 500 1000 1500 2000 2500 3000 3500
0
50
100
150
No. of rounds
No. of dropped packets
IACR
ACE
Fig. 5. Comparison of packet drop in IACR and ACE
better than ACE, but due to the retransmission of erroneous
data the more energy is consumed but as compared to ACE,
the performance of IACR is more better. Moreover in ACE,
the relay nodes sends acknowledgements due to which more
energy is consumed and in case of IACR only a control packet
is sent to relay nodes.
5) Average End to End Delay: Fig 8 compares IACR and
ACE in terms of average end-to-end delay. As the source node
0 500 1000 1500 2000 2500 3000 3500
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
No.of rounds
Packets received at sink/Packets sent to sink
IACR
ACE
Fig. 6. Packet acceptance ratio in IACR and ACE
0 500 1000 1500 2000 2500 3000 3500
0
2000
4000
6000
8000
10000
12000
14000
No. of rounds
Energy consumption(J)
IACR
ACE
Fig. 7. Energy consumed in sensing,transmitting and receiving data
forward data through three different links and the process of
BER calculation is also performed at master node. So it takes
more time to reach the packet towards the sink, so the end-
to-end delay of IACR is high as compared to ACE. As the
source node sends the data packet towards the destination
node and in case the packet drop occurs the retransmission
is performed from the relay nodes. It means the same data
packet is forwarded more than one time so it takes more time
to reach towards the sink hence average end to end delay
increases but due to retransmission the throughput and packet
acceptance ratio of IACR as comapres to ACE is increased.
Fig 9 and 10 shows the network lifetime of IACR and ACE.
The dead nodes in case of ACE increases sharply as there is
more load on the cooperative nodes and the nodes with lower
depth die earlier as well. In case of IACR, the cooperative
nodes holds the data packet for the certain amount of time
0 500 1000 1500 2000 2500 3000 3500
0
0.5
1
1.5
2
2.5
3
3.5
No. of rounds
Average end−to−end Delay per round of network
IACR
ACE
Fig. 8. Comparison of average end-to-end delay
after which they drop the data packet hence there is less load
on the cooperative nodes in IACR as compared to ACE,so the
the network life time in IACR increases.
0 500 1000 1500 2000 2500 3000 3500
120
140
160
180
200
220
240
260
No. of rounds
No. of alive nodes
IACR
ACE
Fig. 9. Number of alive nodes
C. Performance Trade-Offs
In our scheme of IACR, the throughput, lifetime and
packet acceptance ratio of the network is achieved at the
cost of energy consumption and average end-to-end delay
as shown in Table 2. The throughput and packet acceptance
ratio of our scheme is increased as compared to ACE
because of the two reasons. i)The cooperative region lies
outside the depth threshold. ii) The selection of best nodes
from a cooperative region for retransmission of erroneous data.
The throughput in ACE is achieved at the cost of average
end to end delay and energy consumption. Due to retransmis-
TABLE II
PERFORMANCE TRA DE- OFFS
Protocol Achieved parameter Figure Compromised parameter Figure
IACR Packet Acceptance Ratio Fig 7 Energy Consumption Fig 8
ACE Throughput Fig 5 End-to-End Delay Fig 9
IACR Less Packet Drop Fig 6 End to End Delay Fig 9
IACR Throughput Fig 5 Energy Consumption Fig 8
ACE Packet Acceptance Ratio Fig 7 Energy Consumption Fig 8
IACR Network Lifetime Fig 10,11 End to End Delay Fig 9
0 500 1000 1500 2000 2500 3000 3500
0
20
40
60
80
100
120
140
No. of rounds
No. of dead nodes
IACR
ACE
Fig. 10. Number of dead nodes
sion in ACE the throughput increases but on the cost of total
energy consumption.
The network lifetime of our scheme is improved on the cost
of average end to end delay. The network lifetime increases
because, as the source node transmit data to the destination
from multi paths and retransmission also occurs in case of
erroneous data so the average end to end delay increases but
the lifetime of the network is much improved.
In our scheme there are less chances of packet drop, which
is achieved on the cost of end to end delay. As the delay
increases the same packet is transmitted from multiple paths
and the chances of packet drop are very rare in our scheme
as compared to ACE.
VII. CONCLUSION AND FUTURE WOR K
In this paper a new cooperative adoptive routing protocol
(IACR) is proposed to improve the performance, reliability,
throughput efficiency and lifetime of the network in a poor link
quality and in noisy underwater environment. The proposed
protocol has been evaluated in MATLAB and the simulation
results shows that IACR has better performance in terms of
reliability and throughput as compared to ACE.
As a future direction we are interested in implementing several
other criteria for the selection of relay nodes and cooperative
region to enhance the performance of cooperative routing.
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Owing to the harsh and unpredictable behavior of the sea channel, network protocols that combat the undesirable and challenging properties of the channel are of critical significance. Protocols addressing such challenges exist in literature. However, these protocols consume an excessive amount of energy due to redundant packets transmission or have computational complexity by being dependent on the geographical positions of nodes. To address these challenges, this article designs two protocols for underwater wireless sensor networks (UWSNs). The first protocol, depth and noise-aware routing (DNAR), incorporates the extent of link noise in combination with the depth of a node to decide the next information forwarding candidate. However, it sends data over a single link and is, therefore, vulnerable to the harshness of the channel. Therefore, routing in a cooperative fashion is added to it that makes another scheme called cooperative DNAR (Co-DNAR), which uses source-relay-destination triplets in information advancement. This reduces the probability of information corruption that would otherwise be sent over a single source-destination link. Simulations-backed results reveal the superior performance of the proposed schemes over some competitive schemes in consumed energy, packet advancement to destination, and network stability.
... In [13], a cooperative routing protocol is proposed. The source node transmits the sensed signal towards the destination and the relay nodes. ...
... .13 shows the voltage for the input current for MFC. The output voltage is calculated by ...
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Cooperative routing is an appealing challenge in underwater wireless sensor networks (UWSNs). In this paper, we propose a region based cooperative routing protocol (RBCRP) for amplify and forward (AF) technique over Rayleigh faded channels in UWSNs. The source node sends the sensed signal to the destination and available relay nodes. At the destination node, bit error rate (BER) is checked on the basis of which, either positive or negative acknowledgement (ACK or NACK) is sent to the source and relay nodes. We also use mobile sinks (MSs) and energy harvesting techniques to further prolong the network lifetime and maximize the throughput. Our derived mathematical equations for the SNR gain and outage probability are verified by simulations. Results show that RBCRP performs better than the existing incremental best relay technique (IBRT) in terms of throughput, network lifetime and outage probability.Cooperative routing is an appealing challenge in underwater wireless sensor networks (UWSNs). In this paper, we propose a region based cooperative routing protocol (RBCRP) for amplify and forward (AF) technique over Rayleigh faded channels in UWSNs. The source node sends the sensed signal to the destination and available relay nodes. At the destination node, bit error rate (BER) is checked on the basis of which, either positive or negative acknowledgement (ACK or NACK) is sent to the source and relay nodes. We also use mobile sinks (MSs) and energy harvesting techniques to further prolong the network lifetime and maximize the throughput. Our derived mathematical equations for the SNR gain and outage probability are verified by simulations. Results show that RBCRP performs better than the existing incremental best relay technique (IBRT) in terms of throughput, network lifetime and outage probability.
... Another cooperative routing is presented in Hussain et al. 28 The depth and remaining energy are used as the selection parameters of the next node. Three nodes are selected: one as the destination and the other two as relays. ...
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In underwater wireless sensor networks, stability and reliability of the network are of paramount importance. Stability of the network ensures persistent operation of the network that, in consequence, avoids data loss when nodes consume all the battery power and subject to death. Particularly, nodes bearing a low pressure of water die early in the usual routing approach due to being preferred choices for data routing. Reliability ensures minimization of the adverse channel effects on data packets so that the desired information is easily extracted from these packets. This article proposes two routing protocols for underwater wireless sensor networks: reliable and stability-aware routing and cooperative reliable and stability-aware routing. In reliable and stability-aware routing, energy assignment to a node is made on the basis of its depth. Sensor nodes having the lowest depth are assigned the highest amount of energy. This energy assignment is called the energy grade of a node and five energy grades are formed in the proposed network from top to bottom. The energy grade along with energy residing in a node battery and its depth decide its selection as a forwarder node. The reliable and stability-aware routing uses only a single link to forward packets. Such a link may not be reliable always. To overcome this issue, the cooperative reliable and stability-aware routing is proposed which introduces cooperative routing to reliable and stability-aware routing. Cooperative routing involves the reception of multiple copies of data symbols by destination. This minimizes the adverse channel effects on data packets and makes the information extraction convenient and less cumbersome at the final destination. Unlike the conventional approach, the proposed schemes do not take into account the coordinates of nodes for defining the routing trajectories, which is challenging in underwater medium. Simulation results reveal a better behavior of the proposed protocols than some competitive schemes in terms of providing stability to the network, packet transfer to the ultimate destination, and latency.
... Similar to DEAC protocol, an improved adaptive cooperative routing (IACR) protocol proposed in [30] allows selection one destination and two cooperative relay from the two different sets separated by a predefined D th . Accordingly, a node that has the lowest depth and the highest residual energy and lies in the out-depth threshold region of the source node is selected as a destination node. ...
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This paper sought to investigate performance of multi-hop underwater acoustic sensor networks (UW-ASNs) when they deploy cooperative routing algorithms combining the cooperative communication and routing methods. Taking into account energy efficiency, the studied schemes are discriminated by different policies of selecting next hop nodes as well as relay nodes of one-hop cooperative communications such that the transmission energy of routing paths is minimized. In order to take full advantage of broadcast nature in wireless communication, we propose to use a node exploited as a joint relay for two-hop cooperative communication. In addition, the unreliable communication of acoustic channels is addressed by incorporated channel-aware mechanism which updates the links by exploiting packet receptions. On the bases of communication, two cooperative routing protocols are developed. Simulation results show that the network employing the proposed schemes achieves an improved performance in terms of energy efficiency, throughput, and end-toend delay as compared to the related works.
... An improved adaptive cooperative routing protocol [56] has been proposed for UWSNs. In this protocol, depth and residual energy information of sensor nodes are used to select both master node and cooperative partner nodes in the network which improves the performance of network in terms of reduced energy and increased throughput. ...
Thesis
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In this work, we present two routing protocols for circular underwater wireless sensor networks (UWSNs); circular sparsity-aware energy efficient clustering (CSEEC) and circular depth-based sparsity-aware energy efficient clustering (CDSEEC) with sink mobility. In CSEEC, we divide circular network area into 5 concentric circular regions. We deployed sensor nodes randomly and placed a static sink at the top of the circular underwater network region. We further sub-divided the 5 concentric circles into 10 regions. Then, we identified sparse and dense regions based on the number of nodes in each region. We used cluster based routing approach in dense network regions and introduced sink mobility in least node density region to achieve balanced energy consumption in the network. In CDSEEC, circular network area is divided into upper and lower semi-circles. Sensor nodes are random uniformly deployed in upper and lower semi-circles and a static sink is placed at the surface of the network region. In upper semi-circle, each sensor node send its sensed data to surface sink using depth information of sensor nodes to achieve energy efficiency by selecting forwarder node with minimum depth. In lower semi-circle, we implement cluster based routing approach in high node density regions and used sink mobility in least density network regions to achieve balanced energy consumption. In UWSNs, uneven distribution of sensor nodes and dynamic network topology creates void holes and high collision probability due to channel interference in dense networks. For avoiding void holes and reducing collision probability, we proposed a virtual chain based routing (VCBR) protocol for UWSNs. In VCBR, we build virtual chains between sensor nodes and sinks to avoid void holes. VCBR also minimizes collision probability which is due to channel interference in the network. The proposed VCBR protocol, introduces a mechanism to forward data packet through best suitable virtual chain to manage the energy resources of sensor nodes efficiently during data communication. The shortest virtual chain between source node and destination is calculated based on the location information of sensor nodes. Furthermore, we also exploit cooperative diversity by presenting two routing protocols (i.e., fixed adaptive cooperative virtual chain based routing (FACVCBR) and incremental adaptive cooperative virtual chain based routing (IACVCBR) to achieve data reliability and prolong network lifetime. In FACVCBR, source node broadcasts data to destination and two relays to achieve diversity which results in data reliability. In IACVCBR, retransmission of data packet is done incrementally to improve data reliability and successful delivery of data packets. In proposed FACVCBR and IACVCBR protocols, we introduce adaptive power control mechanism to utilize energy of sensor nodes in an efficient manner. We validate our propositions via simulations. The results verify that our proposed routing protocols outperform baseline protocols in terms of selected performance parameters.
... In [11], a cooperative routing protocol is proposed. The source node transmits the sensed signal towards the destination and the relay nodes. ...
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In this paper, we propose a region based cooperative routing protocol (RPCRP). This protocol performs analysis of amplify and forward technique over Rayleigh fading channels. The source node sends the sensed signal to the destination and available relay nodes. At the destination node, bit error rate (BER) is checked on the basis of which, either positive or negative acknowledgement (ACK or NACK) is sent to the source and relay nodes. If the positive feedback is received from the destination node, the relay nodes drop the packet. However, in case of negative feedback, the best relay node amplifies the signal. After the signal is amplified, it is forwarded to the destination node. Moreover, the mobile sinks (MSs) change their position after some time and cover the whole network are also deployed. The nodes that lie within the transmission range of MSs forward their data directly to the sink. Also, the mathematical equations for the total SNR gain and outage probability are verified by simulations. Results show that RBCRP outperforms incremental best ralay technique (IBRT) in terms of throughput and network lifetime. Also, the mathematical analysis for outage probability shows that RBCRP is 62 % more better than IBRT.
... Thus, authors achieved reduced energy consumption and longer network lifetime even with cooperative relaying by restricting cooperation to only immediate region. In [20] authors have proposed a cooperative routing protocol in which the relay nodes and the master nodes are selected on residual energy criteria. At the destination node, Bit Error Rate (BER) is calculated on the basis of which the packet is accepted or rejected. ...
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