ubiquitous gis part iii: implementation issues

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Ubiquitous GIS Part III: Implementation Issues

Fall 2007

Ki-Joune Li

http://isel.cs.pnu.edu/~lik

Pusan National University

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STEMPusan National University

STEM-PNU

Two Viewpoints

GeographicContext

RealWorld

ApplicationSystems

How to provideGeographicContext ?

How to store andsearch Geographic

Context ?

How to analyzeGeographicContext ?

Representation of Geographic

Context

Identification of Geographic

Context

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Challenges for Implementation

Representation of Geographic Context

Identification of Geographic Feature

Providing Geographic Context

Storing and Searching Geographic Context

Collecting and Analyzing Geographic Context

Context Modeling

Context Representation

Ontology

Geo-Labeling GUID

In-Network Processing

UBGI Middleware Standard

Contextual Reasoning and Context-Aware Mapping

Data Streaming Managementfrom Geo-Sensors

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Most basic part of UBGI A Framework of Context is required to describe context

Context in Linguistics

in Ubiquitous Computing

Context Modeling

Text Meaning

Context

Fact Interpretation

Context

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Context as Parameters

Data Interpretation

Spatial and Spatiotempoal Context

Behavioral Context

System Environment Context

Human Context

Others

ParametricGML

ContextualParameters

User-centricMeaning

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Issues of Context Modeling

Classification of Context

Representation of Context Spatio-Temporal Properties of Context Parametric Approach

Ontology and Context

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Geo-Labels

Geo-Label: A label for recognizing geographic feature

Implementation Physical Device

2-D Bar Code RFID

Virtual Geo-Label Dynamic Computation from Viewpoint

Contents of Geo-Labels UFID u-Location Other Information

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2-D Bar Codes

Home Page URL,UFID,u-Location, andOther Information

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Virtual Geo-Labels

No Physical Devices Dynamic Computation of Geo-Labels with 3-D Objects

Position View Direction Velocity

Real World

Augmented Realityon a screen

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Implementation of Virtual Geo-Label in 3-D

Server of 3-DGIS Databases

Server ofApplication DB

Geo-Label Mobile Client

Position

Velocity

Interest

View Point

Geo-Label

DynamicComputation

Presentation of UsefulInformation

Progressive Transfer

Simplification of 3-D Objects to

Lessen the Computation Overhead

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Issues of Geo-Label

Implementation of Virtual Geo-Labels iPointer TM of IST Paper Map Panoramic View of 3-D objects

Storing GUID in Geo-Label GUID: Global Unique Identifier

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STEM-PNUShould be processed

in Real-Time

Large Number of Nodese.g. 1 Million Nodes

→ 1 sec/ node

Scalability and Real-Time Constraint

Geographic Context

MobileNode

MobileNode

DynamicUpdates of

Position

ContextRequest

MobileNode

MobileNode

MobileNode

MobileNode

MobileNode

MobileNode

GIS DBGIS DBLocation DBstationary and mobile nodes

Location DBstationary and mobile nodes

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STEM-PNUServer

Geographic Context-Awareness by In-Network Processing

Scalability Problem

Each node has a small fraction of geographic Information.

Each node exchanges geographic information by

P2P Sensor Network Broadcasting

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In-Network Processing: Sensor Network

Sensor Network DatabaseSensor Network Database

No Centralized ServerMobile Ad-Hoc Network (MANET)

Databases are scattered into mobile node

Coverage Area

Multi-Hop

Needs Geographic Routing

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In-Network Processing: P2P

Peer-to-Peer

No Centralized ServerOriginally for File Sharing Services - Examples: Napster, Gnutella, StarCraft

Sensor Network or Infrastructure Network - Each node has an IPv6 address - No Geographic Limit unlike sensor network

Databases are scattered into mobile nodes

(x1,y1,t1), IPAddr1(x2,y2,t2), IPAddr2(x3,y4,t4), IPAddr3(x4,y4,t4), IPAddr4

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Data on Air

Data on AirData on Air

Broadcasting like DMB - Needs a Broadcasting Server - Databases are periodically broadcasted

BroadcastingGeographic Context

Broadcasting Server

Hybrid Approach - Push-Protocol by Broadcasting - Pull-Protocol by Request on Demand

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Issues in In-Network Processing: Indexing

Indexing Databases are scattered into small pieces at local devices NO GLOBAL Server storing a Global Index Modification of

DHT (Distributed Hash Table) or Distributed Index Structures

are required

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Issues in In-Network Processing: Data Format

Data Format for exchange should be defined Data Items to be included in messages

Distributed Data Structures like distributed index Efficiency Heterogeneity

Standards like SensorML and TransduceML Middleware for Massively Distributed Systems Space Heterogeneity

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Issues in In-Network Processing: Protocols

Distributed Algorithms Strongly related with protocol P2P, Sensor Network, Data on Air, and Hybrid

Example: Data on Air Push Protocol

Tradeoff between data items and period Determination of Data Items to Broadcast: Hotspot Analysis Hybrid Approach

Push Protocol for Hotspot data items Pull Protocol on demand request

Other Communication Media like WIBRO

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Ubiquitous Computing Architecture

Heterogeneity UBGI Middleware

MobileNode

MobileNode

MobileNode

Middleware Middleware Middleware

MobileNode

MobileNode

MobileNode

Middleware Middleware Middleware3-Tiers Architecture

Server Server Server

Middleware

Client Client Client

Massively Distributed Environment

Binding Client and Server

Binding Mobile Nodes

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STEM-PNUPerformanceBottleneck

Heterogeneity UBGI Middleware

Middleware

Binding ObjectsGeographic Binding

Location Data Server

(GIS)

Mobile Node Mobile Node

Middleware Middleware

Mobile Node Mobile Node

LDS LDSStandard

e.g. SensorML

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Heterogeneity of Spaces and Reference Systems

Linear Space

Euclidian Space

(L57,Seg22,49) (E121213,N3750015)

Indoor Space

(BD218,Room431)

Heterogeneous Representation of Location

User of UBGI service

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Seamless Space

Linear Space: (L57,Seg22,49)

Indoor Space: (BD218,Room431) Euclidian Space : (E121213, N3750015)

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Example: Indoor Space

No more Euclidian Space Different coordinate systems and different properties.

We should rebuild Spatial DBMS for Indoor Space

Emergency Bell A

401

W.C.

404

405

406

ElevatorStairs

Emergency Bell Bp (F4, 401, 15, 18)

4th Floor

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Context-Aware Mapping

Traditional Map

userA

userB

userI

userD

userC

userF

userG

userH

Context-AwareMapping

user A Context-AwareMapping

user B


user C


user D

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Spatial and Spatiotemporal Aspects


GeographicInformation

For Everyone

My GeographicInformation

My Context

My Profile

My Status

Interpretation

Contextual Reasoning

My Surroundings

My H/W and S/W Context

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Context-Aware Mapping: Example

Spatial and Spatiotemporal Aspects

GeographicFeatures around

My Position

1. Highway or Accessible from Highway2. Gas stations within 50Km3. If possible cheapest gas4. No restaurant for 3 hours5. GI without complicated visualization6. GI without heavy geometric computation

My Context

Lunch before 30 min.

On a highway

Interpretation

Preference to cheapest gas

Small Screen, PDA

Fuel for only 50 Km

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Context-Aware Mapping: Requirements

Contextual Reasoning in Real-Time Mapping NOT Map itself Dynamic Context: Data Stream from Geo-Sensors

Two possible approaches Approach 1: GI with Context-Awareness Features

Example: Extension of GML with Context-Awareness Tags More Preprocessing and Less Runtime Contextual Reasoning

Approach 2: GI without Context-Awareness Features Example: GML and Agent for Context-Awareness Less Preprocessing and More Runtime Contextual Reasoning

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STEM-PNU

Data Stream from Geo-Sensors

Data from sensors: Stream rather than databases

Data Stream differs from Databases Online arrival of data elements, No control over the sequence Data elements are to be discarded after processed

Only small size of memory to store them Continuous queries rather than “one-time” query

DSMS: Different Approaches from conventional DBMS Query Processing, Indexing etc.. Stream Mining rather than Data Mining

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Summary

Context Modeling

Heterogeneity

Geo-Labeling

Scalability In-Network Processing

UBGI Middleware


Data Streaming Management

ubiquitous gis part iii: implementation issues

Documents

geographic contextcollecting

network manetdata

d objectsstoring guid

ubgia framework of context

d bar codeshome page

ubiquitous gis

implementation issuesfall

kijoune lihttp