GLIDER: Gradient Landmark-Based Distributed Routing for Sensor Networks

Qing Fang, Jie Gao, Leonidas J. Guibas, Vin de Silva, Li ZhangDepartment of Electrical Engineering, Computer Science, Mathematics, Stanford University

Information Dynamics Lab, HP Labs

INFOCOM 2005

SpeakerSpeaker：： Shih-Yun HsuShih-Yun Hsu

OutlineOutlineIntroductionGLIDER

Landmark selectionLocal landmark coordinateNamingRouting

SimulationConclusions

IntroductionIntroductionRouting algorithm are classified

ProactiveRouting table

Proactively maintained and take advantage of the hierarchical structure of IP addresses to enable route discovery

Hard to maintain routing table when topology changes frequently

ReactiveAODV or DSR

Flooding the network in order to discover the desired route

IntroductionIntroductionRouting algorithm in WSNs

Power conservation becomes a serious concern and flooding is undesirable

IntroductionIntroductionGeographical routing

Compute routes that are often close to the best possible

Do so with very little overhead in maintaining auxiliary routing structures

GPS receivers can be costly and lead to cumbersome node form factors

IntroductionIntroductionLocalization algorithms

Only some nodes, called anchor nodes, know their location by manually or GPS

Other nodes determine their location by estimating their distances to three or more of these anchors and then become anchors themselves

Localization algorithms are still quite expensive in terms of computation or communication, and often insufficiently accurate

IntroductionIntroductionGLIDER

Location-unawareTopology-enabled routing

The whole networks are connectivity

GLIDERGLIDERLandmark selectionLocal landmark coordinateNamingRouting

Landmark selectionLandmark selectionDesire to have several landmarks lying close

to topological features, such as hole boundariesArrange for nodes near the boundary to be selected

as landmarks with higher probability than interior nodes

Expect the number of landmarks to be proportional to the number of holes (or topological features) of the sensor domain

Landmark selectionLandmark selection

GLIDERGLIDERLandmark Voronoi Complex (LVC)

GLIDERGLIDERCombinatorial Delaunay Triangulation (CDT)

GLIDERGLIDEREach node in the same tile is knowing their

home landmark and the shortest path to the home landmark

GLIDERGLIDEREach landmark also flooding to neighbor tile

Each node is knowing the shortest path to neighboring landmark

Each landmark is knowing other landmark positionsEach landmark builds its shortest path tree by CDT

Local landmark coordinateLocal landmark coordinateEach node calculate the distances or hops

between home landmark and neighboring landmark to itself

1

2

3

(1, 2, 3)

NamingNamingEach node has ID and Name

ID is uniqueName is not necessary unique

Name isHome landmark ID For local landmark coordinate

Ex： (Name, 1, 2, 3)

RoutingRoutingGlobal routingLocal routing

Local routingLocal routingLocal routing (intra-routing) is done by

gradient descent using the local landmark coordinatesGreedily routing

Global routingGlobal routing

SD

SimulationSimulationC++ programming

Network-level simulations using ns-2 will be undertaken in the near future

2000 sensor nodes23 landmarks

5 landmarks are near the hole boundary18 are chosen randomly

Using a Gaussian random variable with standard deviation equal to 50%

SimulationSimulation

20 pairs of sources and destinations selected at random, with path length about 40 hops in each case

The density of network is important

SimulationSimulation

GLIDER GPSR

SD

S

S

S

D

D

D

SimulationSimulation

S

D

S SS

SS

D

D D

DD

GLIDER GPSR

SimulationSimulation

GLIDER GPSR

45 pairs of randomly chosen source and destination

ConclusionsConclusionsThis paper propose a topology-based and

location-unaware routingThis paper combines LVC and CDT to

maintain routingIt will more power balance than GPSR

Thank You!!Thank You!!