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Effect of mesoscale eddies on ..... underwater

acoustic network

Sudip Misra1 Amit Kumar Mandal2 Mihir Dash3 Tamoghna Ojha4

1,2,4School of Information Technology2,3Center for Oceans, Rivers, Atmospheric and Land Sciences

Indian Institute of Technology,

Kharagpur - 721302

Email: smisra@sit.iitkgp.ernet.in1, amiit.mandal@gmail.com2, mihir@coral@iitkgp.ernet.in3, tamoghna.ojha@iitkgp.

Abstract

This paper focuses on the performance evaluation ofUWASNs in the presence of mesoscale eddy. Ocean isa complex medium comprising of different physical andchemical parameters distributed in a non-uniform fashion.Spatial gradient of different parameters leads to the genesisof different static and dyanmical phenomenon. One ofthese phenomena is ocean current. When there is oceancurrent, moving fastly following meander paths, isolatedswirling bodies of water is quite likely to be generated.These swirling bodies of water are known as eddies in theocean. In deep ocean, these large scaled swirling bodies ofwater are denoted as mesoscale eddies. Mesoscale eddieshave significant impact on the propagation characteristicsof acoustics signal. In such an eddy induced environment,if sensor nodes are deployed, the transmission character-istics of sensor nodes are greatly affected by these eddies.We have evaluated the performance of UWASNs in termsof three metrics, namely, signal-to-noise-and-interference-ratio (SINR), bit error rate (BER), and delay.

I. INTRODUCTION

This paper analyzes the performance of UWASNs in the

presence of deep ocean mesoscale eddies. Wiereless sensor

networks consist of small size nodes capable of sensing,

processing and communicating, deployed over some particular

region of interest [] following some architecture.

The major challenging aspects in underwater acoustics com-

munication are summarized below:

Mobility: One of the major idealistic situations in un-

derwater environment is mobility. It is inherent nature of

oceanic environment. Relative velocity among the nodes

makes the communication nodes more complex, due tothe origination of Doppler spread. It also leads to the

perturbation in network architecture. Additionally, there

exists a limitation of available bandwidth.

Acoustic channel property: Occurrence of signal fluc-

tuation is also a major issue and it depends on the

type and strength of a particular type of phenomenon

through which signal propagation takes place. In ideal

situation, the average speed of acoustic signal in oceanic

environment is 1500 m/s. Due to speed fluctuation of

signal, there is a variation in delay from source to the

receiver.

Signal characteristics: Signal degradation results due to

propagation of acoustic signal through oceanic channel

containing different linear and non-linear phenomena Signal detection: During propagation through different

eigen paths, signal can be associated with different un-

wanted noise and it leads to the complicacy in detecting

the original signal.

Connectivity issue: Due to fluctuation in connectivity

among the nodes, there is random variation in data

communication among the nodes. It greatly affects the

performance metric BER.

Of late there has been a growing interest in the field of

acoustical oceanography in the perspective of Underwater

Wireless Acoustic Sensor Networks (UWASNs). In the physi-

cal layer perspective, the major concern in UWASNs is inter-node communication among the nodes. Performance evalua-

tion also takes care of signal perturbation during propagation

through underwater channel. Underwater oceanic channel is

dominated by different phenomena. One of the phenomena

we have considered in this work is mesoscale eddy. They are

mainly originated from ocean current flowing in a meandering

fashion. One example is gulf stream meander. Richardson et

al. [1] observed gulf stream eddy in the western sargasso sea.

On the basis of their directions of rotation, they are mainly

divided into two categories: cyclonic and anti-cyclonic [2].

Cyclonic eddies, also known as cold core eddies, are whirling

bodies of water in anti-clockwise direction in the northern

hemisphere. The centers of these eddies are cooler and lowerin height than the outer lying waters. On the other hand anti-

cyclonic eddies rotate in a clockwise manner in the northern-

hemisphere and the center is warmer and higher than outer

layer water. Dynamically the nature of these eddies can be

of two types: static and dynamic. Their dimensions are in the

order of kms. In circular form, a mature phase eddy extends in

the range of 100-200 km in diameter. Studies on ocean eddies

have revealed that, there is a significant effect of mesoscale

eddies on the sound speed structure in the ocean. The main

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reason for sound fluctuation is that there is a deviation in

temperature [3] in presence of mesoscale eddies. There exists

sound speed gradient through mesoscale eddies.

I I . RELATED WORK ANDC ONTRIBUTION

To evaluate the performance of UWASNs in the physical

layer context, there should have a proper understanding of

the channel through which inter-node communication takes

place. Variations of underwater channel characteristics are

temporal and spatial in nature. When one channel is induced

by some phenomenon, the other one is induced by some

other phenomenon. Irrespective of the type, existence of any

phenomenon in oceanic channel, make changes of the acoustic

communication characteristics. Therefore, consideration of a

real oceanic phenomenon in a sensor node deployed region is

vital. As, the performance of UWASNs is greatly affected by

this phenomenon.

In [4], Zorzi et al. have taken linear topologies of sensor

nodes and considered noise, propagation delay, and their

impact on transmission power and bandwidth. They have notconsidered realistic dynamical phenomenon existing in the

channel. In [5] Xu et al. have evaluated the performance

on UWASNs by considering some metrics, such as, packet

delivery ratio, network throughput, energy consumption, end-

to-end delay. However, the performance evaluation was carried

out in the context of network mobility and other common

aspects relevant to underwater channel. They have not con-

sidered any mesoscale phenomena. In [6], Cui et al. have

described the physical layer performance issues by considering

mainly inherent acoustic bandwidth limitation in underwater,

time variability, i.e., fluctuation in delay. So, they have only

given the priority on oceanic channel itself. In addition to

considering the common problems in underwater, such as,delay, path loss, Doppler spread, in [7] Ancy et al. have

also shown the technique of data transmission in the presence

of shadow zone. However, they have not considered any

dynamical phenomenon in the channel through which data

transmission takes place. In [8], Llor et al. have analyzed the

transmission loss of signal for UWASNs by considering the

environmental factors, such as, surface waves. However, they

have not considered any phenomenon governing the volume

of water. n [9], Ping et al. have analyzed the performance of

underwater channel for UWASNs by taking into consideration

only of propagation delay, multipath fading, and Doppler ef-

fect. However, they have not incorporated any realistic dynam-

ical oceanic phenomenon governing the underwater channelproperties. In [10], Xie et al. have physically model the path

loss between tow sensor nodes at a particular frequency and

time on the basis of statistical method. In predicting path loss

of acoustic signal in underwater, they have only considered

the surface wave activity on the movement of sensor node.

From all the works stated above, it is confirmed that realistic

oceanic phenomenon has been considered in some papers,

however no author or author groups have considered any

kind of mesoscale phanomenon like mesoscale eddies. In our

work we have considered the existence of mesoscale eddy

in the volume of oceanic underwater and its effect on the

performance of UWASNs.

III. NETWORK ENVIRONMENT

from the paper "PerformanceNetworkEnvironmentMulti-

pathRouting"

IV. SIGNAL PROPAGATION THROUGH MESOSCALE EDDIES

A. Physical structure

B. Calculation of acoustic field

During propagation through the eddy field, sound speed

as well as pressure distribution of acoustic signal field get

modified. Fluctuation in temperature speed profile is mainly

due to the deviation of ocean temperature in presence of

mesoscale eddy. Experiments show that cyclonic eddies are

responsible for uplifting of isothermal about a height of 500

m [2]. In this work we have considered the acoustic signal

to be propagating through a Gaussian eddy. Firstly, we have

calculated the speed of acoustic signal through this eddy

and latter on we have calculated the pressure distribution ofacoustic field.

1) Calculation of acoustic speed:

2) Calculation of acoustic pressure:

V. PROBLEM FORMULATION

Let us consider a fluid to be rotating with constant angular

velocity . The basic fluid equations of motion associated arefunctions of tangential velocity V = (u,v,w) and[?] scalarquantities (, ,P,T,c ,t)1 The body-force potential canbe written as:

= gz (1)

In Equation (1), g is the gravitational acceleration.

REFERENCES

[1] P. L. Richardson, A. E. Strong, J. A. Knauss, Gulf stream eddies:recent observations in the western srgasso sea, Journal of PhysicalOceanography , vol. 3, pp. 297301, July 1973.

[2] R. F. Henrick, W. L. Siegmann, M. J. Jacobson, General analysisof ocean eddy effect for sound transmission applications, Journal of

Acoustical Society of America, vol. 62, no. 4, pp. 860870, July 1977.[3] I. Frenger, N. Gruber, R. Knutti, M. Mnnich , Imprint of southern

ocean eddies on winds, clouds and rainfall, Nature Geoscience, vol. 6,pp. 608612, August 2013.

[4] M. Zorzi, N. Baldo, Energy-efficient routing schemes for underwateracoustic networks,IEEE Journal On Selected Areas In Communication,vol. 26, no. 9, pp. 17541766, December 2008.

[5] M.Xu, G. Liu, H. Wu, W. Sun, Towards robust routing in three-

dimensional underwater wireless sensor networks, International Jour-nal of Distributed Sensor Networks, vol. 2013, pp. 115, 1st October2013.

[6] J. H. Cui, J. kong, M. Gerla, S. Zhou, The challenges of buildingscalable mobile underwater wireless sensor networks for aquatic appli-cations, IEEE Network, vol. 20, no. 3, pp. 1218, June 2006.

[7] S. B. Ancy, S. S. Hammed, Energy efficient and reliable communica-tion in underwater acoustic sensor networks, International Journal of

Advanced Research in Computer Engineering & Technology (IJARCET),vol. 2, no. 1, pp. 169173, January 2013.

1These quantities are respectively known as body-force potential, density,pressure, temperature, sound velocity, and time.

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[8] J. Llor, M. P. Malumbres, Statistical modeling of large-scale signal pathloss in underwater acoustic networks, Journal of Sensors, vol. 13, pp.22792294, 7th February 2013.

[9] G. X. Ping, Y. Yan, H. R. Lin, Analyzing the performance of channel inunderwater wireless sensor networks,Advanced in Control Engineeringand Information Science, vol. 15, pp. 9599, 2011.

[10] G. Xie, J. Gibson, L. D. Gonzalez, Incorporating realistic acousticpropagation modelsin simulation of underwater acoustic networks: astatistical approach, in Proceedings of MTS/IEEE Oceans, Boston, 18-21th September 2006, pp. 19.