The Meandering Current Mobility Model and its Impact on Underwater Mobile Sensor Network November 25, 2008 TaeSeob,Yun KAIST DATABASE & MULTIMEDIA LAB.

The Meandering Current Mobility Model and its Impact on Underwater

Mobile Sensor Network

November 25, 2008

TaeSeob ,YunKAIST

DATABASE & MULTIMEDIA LAB

DATABASE & MULTIMEDIA LAB 2November 25, 2008

Contents

Introduction

Mobility Model

Network Model

Localization

Conclusion


Introduction(1/4)

Needs for Underwater Environment Monitoring Military surveillance Oceanographic data collection Ecology Public safety Industry


Introduction(2/4) Features of Underwater Envi-

ronment Immense volume of the

underwater domain Impossible to use dense

deployment Meandering currents Limitations of signal uses


Introduction(3/4)

Ways to Perform Measurements in the Oceans Eulerian

Data is taken at positions that do not change in time

LagrangianData is taken from autonomous devices that

passively follow the ocean currents

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Introduction(4/4) Recent Work with Network Capability

Data gathering[Vas05] Synchronization[Sye06] Localization[Cha06] Routing protocols[Pom05] [Xie06] Energy minimization [Chi07] MAC [Mak06]

This paper study Underwater mobile acoustic sensor networks that consist

of free floating sensors with network capability

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Mobility Model(1/6) Mobility Model

Description of the fluid nature of the medium in which interconnected sensors move

Typical mobile sensor network Sensor move independently Random walk process Random waypoint process

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Mobility Model(2/6) Case of Fluids - the same velocity field advects all

the sensors Paths are deterministic Strong correlations between nearby sensors

Ocean forecasts Depends on the level of realism Atmospheric forcing Bottom topography Boundary conditions

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Mobility Model(3/6) Lagrangian transport [Ott89][Sam06]

Stratified movement Rotating fluid Drifter- a buoyant object floating near the surface Ignore vertical movements

Wind-driven upwelling/downwelling Exceptionally intense internal waves

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Mobility Model(4/6)

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k = number of meanders in the unit lengthc: phase speed with which they shift downstreamB: modulates the width of the meandersA: average meander widthe: amplitude of the modulationω: frequency of e(A = 1.2, c = 0.12, k = 2π/7.5, ω = 0.4, e= 0.3)


Mobility Model(5/6)

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Mobility Model(6/6)

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Network Model(1/9)

Time varying graph G = (V(t), E(t))

V(t): sensor nodes moving in a rectangular domain at time t

E(t): communication link between sensorsCommunication link: if a node can send a packet

to another node

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Network Model(2/9) Successful reception of a transmission depends on

Received signal strength Interference caused by simultaneously transmitting

nodes Ambient noise level

Particularly affect acoustic underwater communica-tion Shadowing Reflection Scattering diffraction

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Network Model(3/9) Homogeneous sensor network

Maximum communication range (Rc=1000m)

Deployment Domain: initially, deploy in the square [0,4]x[-2,2]km

to [0,80]x[-4,4]km Scenarios

Single deployment k-phase deployments

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Network Model(4/9) LCC(Largest Connected Component)

LCC(t) is the set of sensors in the largest connected component at time t

Disruption and delay tolerant networking(DTN) can be used to overcome [Fal03] Probability that communication graph G is parti-

tioned in several connected components Communications require multiple hops

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Network Model(5/9)

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Network Model(6/9)

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Network Model(7/9) Coverage

Area Coverage The area coverage of a sensor network at time t, fa(t)

is the fraction of the geographical area covered by one or more sensors at time t

Area Coverage over a time-interval The area coverage of a mobile sensor network during

the time interval [0,t), fm(t) is the fraction of the geo-graphical area covered by at least one sensor at some point of time within [0,t)

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Network Model(8/9)

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Network Model(9/9)

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Localization(1/3)

Most underwater sensor network applications require location infor-mation for data tagging

Cannot use GPS because the high frequency sig-nal does not propagate well through water

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Localization(2/3) Use a set of initial beacons [Ero07]

Sound sources Special devices placed in the ocean emitting signals

Dive and Rise The nodes have the ability to move vertically, get the

GPS coordinates and distribute

Localization Process A beacon distributes its coordinates to its neighbors Estimates coordinates by signals from 3 beacons

Assume that z coordinate to be calculated by a pres-sure sensor

Metric: Time of Arrival(ToA)

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Localization(3/3)

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Conclusion Contribution

First physically-inspired mobility modelAnalysis of mobile underwater sensor net-

worksCould be exploited in the design of underwa-

ter sensor networks

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References [Vas05] I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin, and P. Corke, “Data collection, storage,

and retrieval with an underwater sensor network,” in SenSys’05, San Diego, California, USA, 2005, pp. 154–165.

[Sye06] A. Syed and J. Heidemann, “Time synchronization for high latency acoustic net-works,” in Proc. of Infocom, Barcelona, Spain, April 2006, pp. 1–12.

[Cha06] V. Chandrasekhar, W. K. Seah, Y. S. Choo, and H. V. Ee, “Localization in underwater sensor networks: survey and challenges,” in WUWNet ’06, Los Angeles, CA, USA, 2006, pp. 33–40.

[Pom05] D. Pompili and T. Melodia, “Three-dimensional routing in underwater acoustic sensor networks,” in PE-WASUN ’05: Proc. of the 2nd ACM Int. workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks, Montreal, Quebec, Canada, 2005, pp. 214–221.

[Xie06] P. Xie, J. Cui, and L. Lao, “Vbf: Vector-based forwarding protocol for underwater sen-sor networks,” in In Proc. of IFIP Networking’06, Portugual, May 2006, pp. 1216–1221.

[Chi07] N. Chirdchoo, W.-S. Soh, and K. C. Chua, “Aloha-based mac protocols with collision avoidance for underwater acoustic networks,” in INFOCOM 2007, Anchorage, Alaska, USA, May 2007, pp. 2271–2275.

[Mak06] D. Makhija, P. Kumaraswamy, and R. Roy, “Challenges and design of mac protocol for underwater acoustic sensor networks,” in 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, Boston, Massachusetts, USA, 03-06 April 2006, pp. 1–6.

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References [Ott89] J. M. Ottino, The Kinematics of Mixing: Stretching, Chaos, and Transport, ser. Cam-

bridge Texts in Applied Mathematics. Cambridge University Press, 1989, no. 3. [Sam06] R. M. Samelson and S. Wiggins, Lagrangian Transport in Geophysical Jets and

Waves. The Dynamical Systems Approach, ser. Interdisciplinary Applied Mathematics. Springer-Verlag, 2006, no. 31

[Fal03] K. Fall, “A delay-tolerant network architecture for challenged internets,” in SIG-COMM ’03, Karlsruhe, Germany, 2003, pp. 27–34.

[Ero07] M. Erol, L. Vieira, and M. Gerla, “Localization with divenrise (dnr) beacons for un-derwater sensor networks,” in to be presented in WUWnet’07, 2007

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The Meandering Current Mobility Model and its Impact on Underwater Mobile Sensor Network November 25, 2008 TaeSeob,Yun KAIST DATABASE & MULTIMEDIA LAB.

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