Optimizing Energy using Probabilistic Routing in Underwater

Sensor Network

Sanjay K. Dhurandher

, Mohammad S. Obaidat

, Abhishek Gupta

Prateek Gupta

and Siddharth Goel

CAITFS, Division of Information Technology, Netaji Subhas Institute of Technology, University of Delhi,

New Delhi, India

Department of Computer Science & Software Engineering, Monmouth University, New Jersey, U.S.A.

Keywords: Underwater Sensor Networks, Probabilistic Routing, Simulation Analysis, Performance Evaluation.

Abstract: As the Importance of Applications, Such as Ocean Sampling, Environmental Monitoring, Disaster

Prevention, and Distributed Tactical Surveillance, Has Recently Grown, the Need for Underwater

Communication Has Become More Pronounced. unlike Terrestrial Sensor Networks, Underwater Sensor

Networks (Uwsns) Have Different Characteristics Such as a Long Propagation Delay, a Narrow Bandwidth

and High Packet Loss.Considering the Various Challenges Posed by the Underwater Environment, a

Routing Algorithm Has Been Proposed in This Paper. the Algorithm Consists of Special Features, including

Three Different Types of Nodes in the Architecture Proposed, a Mathematical Formula in Order to Select

the next Node to Be Used for Transmission. the Major Aim of the Algorithm Is to Select the next Node to

Be Used for Successful Data Delivery, and Ensure Minimum Energy Consumption. the next Node Is

Chosen With Utmost Care in Order to Increase the Probability of Successful Data Delivery. the Packet Is

Transferred from the Source to the Sub-Destination by Exploiting Minimum Energy of the Nodes. the

Simulation Studies for the Protocol Were Conducted using AQUA-GLOMO Network Simulator. the

Protocol Was Benchmarked With DSR Routing Protocol. the Matrices That Were Considered for the

Simulation Study Were Throughput, PDR, Energy Consumption and Delay and It Was Observed That Our

Proposed Model Performed Better in the Underwater Environment.

1 INTRODUCTION

Marine life is constantly being exploited by humans.

Be it leakage of oil in sea waters while extracting

crude oil from sea beds, dumping of industrial

wastes or over fishing in a particular area. All these

and several other human activities disturb the habitat

of aquatic creatures. Since, one cannot afford more

contamination of water resources, it is the need of

the hour that there is continuous monitoring of the

underwater environment of seas and oceans and

reporting of undesirable activities taking place-

whether human or natural.

Acoustic underwater ad-hoc networks need

special attention, due to the uselessness of radio

waves in water. This gives way to large propagation

delays. The diverse topology accounts for

connection impairment, high bit error rate, frequent

temporary losses of connectivity, and loss of nodes

due to erratic water currents. All the above

mentioned points hinder us from developing a

routing algorithm that ensures high probability of

successful data delivery, minimum energy

expenditure and lesser time delays.

The transmission of data packets is done in a

hop-by-hop fashion. The major focus has been on

the selection of the best suited next transmission

node. This ensures efficient data delivery with

optimized energy consumption. A mathematical

model has also been proposed in order to achieve

this goal.

The selection of the next node is done on the

basis of the relative depth, and the energy and the

distance of the nearby neighbouring nodes. The

concept of VBR is also being applied in order to

incorporate the variable “distance” (distance

between sender nodes and other relaying nodes) in

the protocol.

409

Dhurandher S., Obaidat M., Gupta A., Gupta P. and Goel S..

Optimizing Energy using Probabilistic Routing in Underwater Sensor Network.

DOI: 10.5220/0004168004090416

In Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2012),

pages 409-416

ISBN: 978-989-8565-20-4

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

The proposed algorithm is free of any table

maintenance or time synchronization techniques.

Hence, these features help in saving energy of the

nodes up to some extent.

2 RELATED WORK

Underwater environment poses many problems for

efficient routing in the underwater sensor networks.

The routing procedures proposed for terrestrial

sensor networks cannot be directly applied in the

underwater scenario. Acoustic wavesare used for

communication instead of radio waves which are

used in terrestrial sensor networks. Acoustic

wavesare better than radio waves in underwater

environment due to its much lower attenuation as

compared to radio waves in water. But acoustic

waves have their disadvantages as well. They are

characterized by low bandwidth, high propagation

delay and high bit error rate. Energy efficiency is the

major concern in underwater environment due to the

use of acoustic signals and harsh conditions in

underwater environment. This makes node

replacement a difficult task and also results in a very

unpredictable and dynamic topology of the network.

Recently, many routing protocols have been

proposed to accomplish effective routing in

underwater sensor networks in an energy efficient

way.

In VBF (Vector-Based Forwarding scheme) (Xie

et al., 2005), each of the sender nodes’ one hop

neighbour compete to be the next hop node of the

route towards thedestination. Each neighbour

computes its perpendicular distance from the virtual

vector between the sender and the destination. This

vector is known as the routing vector. A predefined

radius forms the routing pipe around the routing

vector. To be a candidate for next hop, a node must

lie in the routing pipe formed. Multiple candidates

compete among themselves to be the next relay node

using the desirableness factor, which tells each node

how long it must hold the packet before relaying it.

The desirableness factor favours the node nearest to

the destination. VBF has been extended to HH VBF

(Hop-by-HopVector-Based Forwarding scheme)

(Nicolaou et al., 2007) to overcome the

shortcomings in VBF such as small data delivery

ratio in sparse networks and sensitivity of the

routing radius. Instead of using a single routing pipe

between the source and the destination, HH VBF

uses routing pipes in a hop by hop fashion which

increases the packet delivery ratio.

Another location based routing procedure is the

DFR(Directional Flooding-based Routing) (Hwang

and Kim, 2008). In DFR packet transmission is

achieved through scope flooding. The flooding zone

is decided by the angles between FS vector and FD

vector, where F is the node that receives a packet

and S and D are source and destination respectively.

F decides whether to forward the packet or not by

comparing the SFD angle with the criterion angle

(Base angle) which is included in the received

packet.

In SBR-DLP (Chirdchoo et al., 2009) algorithm

the sender node tries to find the next suitable relay

node by broadcasting a check_ngb packet. All the

nodes that hear this packet respond by sending

check_ngb_reply to the sender. To reduce collisions

at the sender node each neighbour node determines

the sector in which it is in and then schedules the

sending of check_ngb_reply accordingly. The

transmission time of the check_ngb_reply depends

on the priority value associated with each sector.

Using the maximum possible relative velocity and

propagation delay associated with the transmission

of the check_ngb_reply packet the sender node

filters out those nodes that may travel out of its

range before being able to acknowledge the receipt

of the packet. This algorithm takes into account the

node mobility in undersea environments but the

overhead associated with the generation and

processing of mobility (velocity) information of the

relaying nodes along with the location information is

quite large and is not suitable in underwater

environments.

All the above mentioned solutions make use of

the location information of the nodes using the GPS.

Use of GPSand the overhead due to the location

information generated involves large energy

consumption. A significant amount of node energyis

consumed in finding its current location using the

GPS system periodically.

In DUCS (Distributed Underwater Clustering

Scheme) (Domingo and Prior, 2007), a GPS free

scheme, the nodes organize themselves into local

clusters and one node is selected as cluster head for

each cluster. Each node in the cluster transmits its

data to the cluster head and cluster head transmits it

to the sink via the relays of other cluster heads.

Cluster Head selection mechanism has a large

overhead associated with it and is not energy

efficient. Also, there will be collisions at cluster

head when the cluster members send their data.

SIMULTECH 2012 - 2nd International Conference on Simulation and Modeling Methodologies, Technologies and

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410

Another GPS free scheme for underwater sensor

networks is E-ITRC (Energy efficiency &

Innovative Time Reduction Communication)

protocol (Donghoon et al., 2007), which is based on

minimum response time between the surface station

and the underwater sink node. That is, the fastest

packet arrival time to a surface station from an

underwater sink node is the standard to select routers

among underwater relay nodes. This method also

lacks energy efficiency as the node selection

mechanism requires a large number of

transmissions. This algorithm has an on demand

element associated with it. On demand routing

protocols are not suitable in underwater

environments due to high node mobility and

dynamic topology of underwater networks.

3 PROPOSED MODEL

A. Assumptions

Basically, we have two assumptions in this work.

-General Information

All nodes know their depth, their remaining energy

and the quality of the link with their neighbors.

-Link Quality

All nodes can measure each link quality among

neighbors.

B. Protocol Description

Types of nodes to be used:

1. Relaying nodes.

2. Sensor nodes deployed at the sea bed.

3. Floating nodes (the receivers).

4. Special underwater nodes (Dhurandher et al.,

2008).

Relaying Nodes - These are the data forwarders and

do the simple relaying function. These simply float

underwater in the water column between the sensor

and the floating receiver nodes .They Communicate

using the acoustic channel.

Sensor Nodes - These are deployed at the seabed and

are the data generators. These nodes perform the

function of gathering information from the sea bed.

They communicate with the relaying nodes using the

acoustic channel.

Floating Nodes - These are deployed at the sea

surface and are the data collectors. These are the

destination nodes for the data generated at the sea

bed in the sensor nodes. While communicating with

another floating receivers these use radio waves and

acoustic waves for communication with the relaying

nodes.

Special Nodes(Dhurandher et al., 2008) - These are

deployed along with the relaying nodes but are less

in number as compared to them. Their function is to

do all the processing on behalf of the relaying nodes

regarding the selection of the next hop for data

transmission. These have much more battery life

than there laying nodes. They can deploy themselves

according to pressure and come to surface when

their power is low (Dhurandher et al., 2008) and

hence are easy to replace.

Now our basic aim is to make acoustic routing more

energy efficient, robust and efficient. To achieve the

above we propose the following:

• There should be no on demand element in the

routing protocol. We don’t have any route

request and route reply phases in our routing as

these are not desirable in highly dynamic

underwater environments.

• Special nodes are deployed along with the

underwater relaying nodes which do the

processing involved in the selection of the next

hop on behalf of the relaying nodes.

• The parameters used for the selection of next

node are depths of the neighbour nodes, their

respective energies and the route quality between

them after assigning each parameter proper

weight age.

Figure 1: The architecture of the proposed model

(Dhurandher et al., 2011).

 The next hop candidate nodes must lie in a

virtual routing pipe of some predefined radius as

decided by the special node and centered around

it. This filters out those nodes that have the

possibility of travelling out of the range of the

sender node before the sender is able to

acknowledge the receipt of the packet.

 Due to dynamic topology and node mobility due

to the undersea currents we are bound to have

link failures .To counter these and to achieve a

near 100% data delivery, we have designed an

efficient acknowledgement process. If the

acknowledgement for a particular packet

transmitted is not received in specific amount of

Optimizing Energy using Probabilistic Routing in Underwater Sensor Network

411

time then another transmission of the same

packet is tried forwarding it to another node.

This gives the element of multiple routing in our

scheme.

 Multiple routing is done on the basis of priority

of the information as decided by the sensor

nodes.

The following packets are used in the protocol:

 Request_next_nodepacket (request packet to

get the address of the next node)–The nodes on

receiving this packet will shift them to the

active mode. It will also contain the depth and

energy of the node.

 Info_node packet (contains the node’s

information)– This packet will contain the data

about the depth and energy of the relaying

node sending it.

 Data_packet (contains the information that is

to be transferred) – The data that is to be

transferred is contained in this packet.

 Transmission_confirmed packet- Acts as a

message to the sender node that the

transmission has been done successfully and it

can delete the data.

C. Algorithm

Step 1: Information (inf) is being collected by the

sensor node. On the basis of the importance of the

information the sensor node assigns a priority level

to the data (pri). Node containing the data transmits

request_next_node packet (request packet to get the

address of the next node). Relaying nodes in the

transmission area and the nearest special node

receive the request_next_node signal. The Special

Node on receiving this packet will send a packet to

each node that it is the node acting on behalf of the

sender node.

Step 2: The relaying nodes which hear the signal and

are above the depth of node transmitting the

request_next_node packet send info_node packet

(contains the information about the depth and energy

of the node) to the special node.

Step 3: A virtual pipe is created by the special node

whose radius depends onk (number of relaying

nodes sending the info_node packet to the special

node) and depth of the special node from the surface

due to currents. The nodes lying outside this virtual

pipe are eliminated (i.e. not considered for

transmission).

Step 4: The route quality (RQ)of the remaining

relaying nodes is calculated on the basis of the

formula. Now this RQ is compared for the relaying

nodes and the best node(R) is calculated by this

method for further transmission. The data_packet

(the packet containing the information) is now

transferred to the selected relaying node(R). The

special node will now shift to promiscuous mode.

S – Source Node, N – Special Node, R – Relaying Nodes.

Figure 2: The construction of the virtual pipe to eliminate

the nodes lying outside it.

Step 5: Thebest node(R) will now transmit

request_next_node packet which will be heard by

the special node that was involved in its

selection .This acts as acknowledgement (ack) for

the delivered data_packet. If the acknowledgement

(ack) is not received up to a certain time limit then

depending on the priority (pri) of the information

(inf) the algorithm will either repeat itself by making

S1 select the second best node or the data_packet

will be dropped.

Step 6: Steps 1 to 5 will be repeated until the data is

received by the floating receiver node. In order to

remove ambiguity when two special nodes act on

behalf of sender node they first send a packet to

sender node asking for confirmation. If the sender

node receives one such request then it does not send

any packet to the special node. Otherwise, it sends a

packet to the node that is farther than the sender

node asking it not further transmit any packet. The

special node will wait for some time before sending

the packet that it is acting on the sender’s behalf. If

it receives no packet for a time it transmits the

packet assuming it has to act. Else, if it receives a

packet it will shift to promiscuous mode.

This is the basic pseudo code of the routing

protocol. It has the following terminologies:-

inf(information),pri(priority level to the

data),request_next_node packet(request packet to get

the address of the next node), info_node packet

(contains the information about the depth and energy

of the node), transmission_confirmed packet(Acts as

a message to the sender node that the transmission

has been done successfully and it can delete the

data), k (number of relaying nodes sending the

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info_node packet to the special node),RQ (route

quality), R(best node), promiscuous mode(where the

node can only listen),ack (acknowledgement), ptr (is

a pointer variable that stores the address of the

current node).

Each node stores its own depth and energy (refer

subsection A of section III). The special nodes in

addition to this store the route quality (RQ[r] based

on the previous transmissions) between the nodes

lying in its transmission area. Information (inf) is

being gathered by sensor nodes. After a certain

period of time routing procedure initiates. Figure 3

contains the pseudo code which explains the

working of the algorithm.

4 PERFORMANCE

EVALUATION USING

SIMULATION ANALYSIS

To compare the routing protocol, and in order to

replicate the underwater environment, acoustic

communication based AQUA-GLOMO (Dhurandher

et al., 2012) simulation tool for underwater

networks, is used. AQUA-GLOMO is a simulation

tool based on Glomosim for large wireless networks

in the underwater scenario. Dynamic Source Routing

(DSR) (Johnson et al., 2001) protocol is taken as

benchmark and the results are compared to it

A. Simulation Setup

We focused on three performance measurements to

compare the routing protocol: Packet Delivery Rate

(PDR), Energy consumed by the network and

average end-to-end delay for a packet. The

comparison has been done for both static and mobile

scenarios, with and without the acknowledgement

process.

The three parameters in the experiments are defined

as follows:

I.) Packet Delivery Rate: Packet delivery rate is the

ratio of the number of user packets successfully

delivered to a destination to the total number of user

packets transmitted by source nodes.

II.) End-to-end Delay: The average time from the

beginning of a packet transmission at a source node

until packet delivery to a destination node. The time

when the last packet is delivered is recorded. The

average end-to-end delay is found by dividing the

above recorded time by the number of packets

received.

III.) Energy Consumed: The total energy consumed

by the network in transferring 100 packets from

source to the

Priority (pri) of the information (inf) is calculated by the

sensor node.

 Do(while ptr!= address of the floating node)

 Let the node which has data be A.

 Declare ptr = address of A.

 Request_next_node packet is transmitted by node A.

 Relaying nodes in the transmission area and the nearest

special node (S1) receive the request_next_node

packet.

 The relaying node which receives the

request_next_node packet and are above the depth d of

the node having the inf. (i.e. A) send info_node packet

to the special node (S1).

 Now the virtual pipe is created whose radius depends

on k and height of S1 from the surface (it is taken due

to the effect of current).

R = Tr/k + s. (H – H

) + D

n1-s1

(1)

R: Radius of the virtual pipe

Tr: Transmission radius of the nodes involved.

H: Depth of the sea bed

Hn1: Depth of node n1

S: Constant factor which brings down the value of H

comparable to Tr

 The nodes outside this virtual pipe are not considered

for transmission. The nodes left after this elimination

are (r1, r2,……..rk).

 Declare depth of each node as d[k] and energy of each

node as E[k]in the memory of the special node (S1).

 The route quality (RQ[r]) between each two node is

already stored in the special node S1.

 Quality of each node Q is calculated for the selection of

the best node depending on the formula:-

P[r] =

n-k

(2)

= {[(dep

)

. (en

)

] / summation of[(dep

)

. (en

)

]}

: probability of selection of relaying node r in one

trial.

= (1-p

)

P[r]: probability that a particular node will be

selected exactly k times in n trials.

Q[r] = m.P[r] + n.RQ[r] (3)

 Q[k] of each node is calculated.

 Best node is calculated by comparing Q[k] let it be R.

 S1 unicasts the next_node packet containing the

address of R to A.

 Declare i=0.

 Do While(i!=pri)

 Node transmits data_packet.

 If(S1 receives a request_next_node packet from R in

time<=t_timeout)

 S1 transmits transmission_confirmed to A.

 A deletes the data.

 Break. [End of if structure]

 Else

 S1 transmits next_node packet having the address of

next best node to A.

 i++ [End of inner while]

 ptr=R [End of outer while]

Figure 3: The Pseudo Code.

Optimizing Energy using Probabilistic Routing in Underwater Sensor Network

413

destination. We have considered that the nodes

consume 1J of energy in transmitting data packets,

broadcasting Hello Packets, sending Loc and Ack

packets. It is also assumed that 0.5J of energy is

consumed by a node in doing calculations such as

calculating distance, updating table, etc.

In the analysis, one hundred (100) packets of 512

bytes each were sent from source to destination at a

time interval of 480ms.

B. Simulation Results

The simulation has been carried out in both static

and mobile scenarios.

Static Scenario

The terrain dimension was fixed to 900m x 900m.

The placement of the nodes was uniform and the

transmission power of each node was set to 3dB. All

the nodes were fixed at their respective locations.

Values for the three above mentioned performance

metrics were noted and the graph is plotted for81,

100, 169, 256, and 289 nodes. For each number of

nodes, the measurements are done with and without

the acknowledgement.

Figure 4: PDR vs. number of nodes in static scenario.

Figure 4 shows the metric PDR for the two protocols

DSR and Probabilistic Routing algorithm. In static

scenario almost all the packets are received at the

destination nodes in both cases. Hence, PDR has a

value of almost 1.0 for both the protocols.

Figure 5 shows the total energy consumed in the

network in transmitting 100 packets from source

node to destination node. It is clearly visible from

the figure that the energy consumption in PR is

much less than DSR. As the PDR is almost 1.0 for

the PR without Ackso there will be almost no

difference between the energy consumed for the

with and without Ackalgorithm as no packets will be

retransmitted.

Figure 5: Total Energy consumed in the whole network vs.

the total Number of Nodes present in the network for static

scenario.

Mobile Scenario

The results have been taken after the mobility of the

simulation is set to 2.0 m/sec.

Figure 6 shows the PDR in the mobile scenario. The

difference between DSR and PR algorithm is quite

remarkable and also when the Ack process is used

the PDR can further be improved.

Figure 6: PDR vs. number of nodes when nodes are

moving at a speed of 2 m/sec.

Figure 7: Total Energy consumed in the whole network vs.

the total Number of Nodes present in the network for static

scenario.

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Figure 7 shows the total energy consumed by the

network in mobile scenario for 100 packets it can be

clearly seen that the energy used by PR is almost

half to that used by the DSR. Also in the case of PR

with acksome packets are retransmitted depending

on their priority due to quite a difference in PDR and

hence there is a small increase in the energy

consumed as compared to PR without ack though it

is still very less as compared to DSR.

Figure 8: Avg. End to end delay vs. the total Number of

Nodes.

In Figure 8, end to end delay of the PR is recorded

for the underwater environment and is compared

with DSR. As it can be clearly seen from the graph

for small number of nodes the end to end delay is

almost same for the PR and DSR but as the number

of nodes is increased the end to end delay of PR

turns out to be almost half to that of DSR.

5 CONCLUSIONS

In this paper we have proposed a Probabilistic

Routing algorithm which is suitable for mobile

underwater acoustic sensor networks where the

nodes can move along in the network.Its design

takes into consideration the unique characteristics of

such networks, namely, long propagation delay,

node mobility, high channel error rate, and low data

rate.

The DSR protocol has been implemented and

compared with the PR protocol. It is found that the

PR has a better performance with respect to energy

consumption, end to end delay and throughput as

compared to DSR in UWSN. From the simulation

results it is concluded that the lifetime and packet

delivery ratio of the network is improved, with the

reduction in end to end delay for the proposed

protocol over the existing DSR protocol.

The algorithm also ensures quite high PDR with

low energy utilization and does not involve any

multi-path routing or time-synchronization

techniques. The PR algorithm is simple and easy to

implement. Hence, the algorithm is suitable for real-

time implementation as well.

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