Modeling Context Information in Pervasive Computing System Presented by Karen Henricksen, Jadwiga...

Modeling Context Information inModeling Context Information inPervasive Computing SystemPervasive Computing System

Presented by

Karen Henricksen, Jadwiga Indulska, and Andry Raktonirany

From University of Queensland

At Pervasive 2002

Summerized By Sungchan Park @ IDS Lab.

2008-09-24

Copyright 2008 by CEBT

OverviewOverview

The authors examine

Characteristics of Context Information

and propose

Their context modeling approach considering the characteristics

Center for E-Business Technology IDS Lab. Seminar - 2


Chracteristic of Context InformationChracteristic of Context Information

1. Context info exhibits a range of temporal characteristic

Dynamic or Static

2. Context info is imperfect

Highly dynamic

3. Context has many alternative representation

Contains many raw data,

and each application requires different form or level of abstraction of the same raw data

4. Context info is highly interelated

Dependency between data

IDS Lab. Seminar - 3Center for E-Business Technology


Problem of Modeling Context with Existing Modeling MethodProblem of Modeling Context with Existing Modeling Method

Existing Modeling Method

E-R, UML

Problem

Cannot deal properly

– Temporal and error characteristic of Context

– Relationships such as dependencies



Modeling Context Information: Core Modeling Context Information: Core ConceptsConcepts

Core Modeling Concpets

Directred Graph

– Node : Entity, Attribute

– Edge : Association



Modeling Context Information: Modeling Context Information: FeaturesFeatures

1. Classifying Association

By Temporal Characteristic

2. Structural Constraints on Association

3. Modeling Dependency

4. Modeling Context Quality



Modeling Context Information: #1 Classifying Modeling Context Information: #1 Classifying AssociationAssociation

Classifying Associations

Static Association

Dynamic Assocication

– Sensed Association

– Derived Association

– Profiled Association

User input info



Modeling Context Information: #2 Structural Modeling Context Information: #2 Structural ConstraintsConstraints

Association Contraints

Simple Association

– 1 to 1

Composite Association

– Collection association

1 to many

– Alternative association

1 to (one of)many

– Temporal association

Function mapping varying with time

Ex. Person EngagedIn Activity



Modeling Example with Additional Modeling Example with Additional FeaturesFeatures



Modeling Context Information: #3 Modeling DependenciesModeling Context Information: #3 Modeling Dependencies

Modeling Dependencies

Association a1 depends on another association a2



Modeling Context Information: #4 Modeling Context QualityModeling Context Information: #4 Modeling Context Quality

Modeling Context Quality

Each association has

– Quality Parameter

Accuarcy of Sensor, Freshness, …

– Qaulity Metric

Representation of Quality Metric



Complete Modeling ExampleComplete Modeling Example



ConclusionConclusion

Explored the characteristics of context information

Described a set ot context modeling concepts accommodate these

Future work

privacy



And Story Continues…And Story Continues…

The authors made Context Modeling Language(CML)

“A Software Engineering Framework for Context-Aware Pervasive Computing”, 2004, PerCom ‘04

and continue to refine it

“XCML: A Runtime Representation fot the Context Modeling Language”, PerCom ‘07



Interesting PointsInteresting Points

“Characteristics of Context Information” is remarkable

Presence of various temporal characteristic

Need for supporting diversity in representation of same data

Importance of dependency

Quality can be lower than other kind of info.

But, in their solution,

Need for “Alternative Representation” is not properly solved

“Dependency” is represented too simply

– Just marking “one depends on other one” is enough?


Modeling Context Information in Pervasive Computing System Presented by Karen Henricksen, Jadwiga...

Documents

Transcript of Modeling Context Information in Pervasive Computing System Presented by Karen Henricksen, Jadwiga...