topological hole detection in wireless sensor networks and its applications stefan funke department...

Topological Hole Detection in Wireless Sensor Networks and its Applications

Stefan FunkeDepartment of Computer Science, Stanford University, U.S.A.

DIAL-M-POMC 2005DIAL-M-POMC 2005

SpeakerSpeaker：： Shih-Yun HsuShih-Yun Hsu

DIAL-M-POMCDIAL-M-POMC

Discrete Algorithms and Methods for Mobile Computing and CommunicationsWorkshop in conjunction with ACM/SIGMOBILE

MobiCom (1997～ 2004)

Principles of Mobile ComputingWorkshop in conjunction with

ACM/SIGACT and SIGOPS PODC (2001)ACM/DISC (2002)

OutlineOutlineIntroduction

Related works

Main methodsTopology hole findingCoarse Boundary Sampling and Pruning

ApplicationsExperiment evaluationConclusions

IntroductionIntroductionDue to cost restrictions and to achieve the

maximum life-time by energy savingsThe characteristics of sensors

Low-capability devicesTemperatureHumidity

Small radio device that allows for communication between nearby sensor nodes

Easy to be deployed by airplanes

IntroductionIntroductionTo achieve the maximum life-time

It is impossible to equip energy-hungry GPS unitNone of the sensor nodes is aware of its geographic loca

tion

IntroductionIntroductionThere are many holes in the monitoring region

Fall right into the flames and be destroyedPlunge into a lake or pond and be unable to

perform their monitoring taskFall from airplane on the grand then break

Detecting the boundaries of such holes in the monitored space created by fire or other phenomena

Related worksRelated worksGLIDER: Gradient Landmark-Based

Distributed Routing for Sensor NetworksGeographic Routing without Location

InformationMAP: Medial Axis Based Geometric Routing

in Sensor Networks

Main methodsMain methodsTopology hole findingCoarse Boundary Sampling and Pruning

Topology hole findingTopology hole findingBasic concept

Beacon

Euclidean lengthhole

Unit Disk Graph (UDG)

Topology hole findingTopology hole finding Monitoring (connected) region Beacon Any points dp(x) denotes the minimum Euclidean

length from p to x The isolevel (contour of level) of k

The sub-graph of UDG induced by I(k) might be disconnected

2R Rp R

x R

( ) { ( ) }pI k x R d x k

1 2( ) { ( ), ( ), ...}I k C k C k

p

xdp(x)

I(k)

C1(k)

C2(k)

Topology hole findingTopology hole finding Pick a local beacon q Compute hop-distances h(v’) to q Mark all nodes v which do not ha

ve a 2-hop neighbor v’ with h(v’) > h(v)

C1(k)

q

v

Topology hole findingTopology hole findingbeacon

Border nodes

Topology hole findingTopology hole finding

Topology hole findingTopology hole finding The first beacon was chosen rand

omly Maintain a variable CBD(v) (Clos

est Beacon Distance) storing the (hop-)distance and choose the last 3 beacons as far as possible1

2

3

4

Coarse Boundary Sampling and Coarse Boundary Sampling and PruningPruningA natural way to reduce this number is to com

pute a maximal independent set (MIS) within all the marked nodesMaximal independent sets in radio networks

Thomas Moscibroda, Roger WattenhoferDepartment of Computer Engineering and Networks Laborato

ry, ETH Zurich, Switzerland

ACM Symp. on PODC 2005

Coarse Boundary Sampling and Coarse Boundary Sampling and PruningPruning

Coarse Boundary Sampling and Coarse Boundary Sampling and PruningPruning

Density

ApplicationsApplicationsGLIDER: Gradient Landmark-Based Distri

buted Routing for Sensor NetworksQing Fang, Jie Gao, Leonidas J. Guibas, Vin de Sil

va, Li ZhangDepartment of Electrical Engineering, Computer Scienc

e, Mathematics, Stanford UniversityInformation Dynamics Lab, HP Labs

INFOCOM 2005

ApplicationsApplications -GLIDER--GLIDER-

S

D


Paths that share the same subsequence of tiles are kept apartLoad-balance


GLIDER for random landmark selection

GLIDER for topology-aware landmark selection


In inter-tile, the GLIDER protocol is also load-balance


In intra-tile, the GLIDER protocol could not be load-balance

Near Far


Load imbalance due to Landmarks being too close to boundaries


Landmarks sends a HELLO message with distance counter 0 which increases at every hop

The value △(v) is then the minimum counter value over all messages received

dlocal(p)=min(d(p, qi)) New position of landmark p’=dloca

l(p)/3 p still in the tile of p’ Any tile will not contain a whole

hole If d(p’, q’)<dlocal(p) (p and q are c

loser) Removed q’

p

q1

q2

q3

q4

P’

ApplicationsApplicationsGeographic Routing without Location Infor

mationAnanth Rao, Sylvia Ratnasamy, Christos Papadimi

triou, Scott Shenker and Ion StoicaUniversity of California, Berkeley

INFOCOM 2003

ApplicationsApplications - - Geographic Routing Geographic Routing --


Holes might obstruct the shortest paths between nodes of the network and hence their lengths are not a good estimate of the true geometric distance


Truthful distances

Not truthfuldistances


P is the set of boundary nodesThe distance measured between a pair

is truthful, if the respective shortest path in the communication graph from p to q providing this estimate does not contain any as intermediate node

( , )p q P P

r P

ApplicationsApplicationsMAP: Medial Axis Based Geometric Routin

g in Sensor NetworksJehoshua Bruck, Jie Gao, Anxiao (Andrew) Jiang

California Institute of Technology, USCaltech, US

MobiCom 2005

ApplicationsApplications -MAP--MAP-

ApplicationsApplications -MAP--MAP-

Near Far to the border

Experiment evaluationExperiment evaluation4900 nodes800×800 square regionCommunication range is 15(average degree 5),

20(10), 27(18), 40(39)The degree is rcommunication/rsense

Unit disk graphs (UDG)Random Uniform DistributionsRandomly perturbed Grid

Non-UDG

UDG with Random Uniform UDG with Random Uniform DistributionsDistributions

15(5) 20(10)

27(18) 40(39)

Communication Range (Ave. degree)

UDG with Randomly perturbed UDG with Randomly perturbed GridGrid

15(5) 20(10)

27(18) 40(39)

Communication Range (Ave. degree)

Non-UDGNon-UDG

With UDG With Non-UDG

Non-UDGNon-UDG

Degree 8 Degree 16 Degree 20

ConclusionsConclusionsThis paper we have presented a rather simple

and straightforward algorithm for detecting holes in a wireless communication networkLocation-unawareHigher density is better

This paper also sketched further applications of hole finding routine, where the knowledge about holes in the network provides for better performance of existing topology-based, location-free protocols

Thank You!!Thank You!!

topological hole detection in wireless sensor networks and its applications stefan funke department...

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