Modeling Context Information in Pervasive Computing System Presented by Karen Henricksen, Jadwiga Indulska, and Andry Raktonirany From University of Queensland At Pervasive 2002 Summerized By Sungchan IDS Lab
Copyright 2008 by CEBT Overview The authors examine Characteristics of Context Information and propose Their context modeling approach considering the characteristics Center for E-Business TechnologyIDS Lab. Seminar - 2
Copyright 2008 by CEBT Chracteristic 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
Copyright 2008 by CEBT Problem 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 IDS Lab. Seminar - 4Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: Core Concepts Core Modeling Concpets Directred Graph – Node : Entity, Attribute – Edge : Association IDS Lab. Seminar - 5Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: Features 1.Classifying Association By Temporal Characteristic 2.Structural Constraints on Association 3.Modeling Dependency 4.Modeling Context Quality IDS Lab. Seminar - 6Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: #1 Classifying Association Classifying Associations Static Association Dynamic Assocication – Sensed Association – Derived Association – Profiled Association User input info IDS Lab. Seminar - 7Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: #2 Structural Constraints 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 IDS Lab. Seminar - 8Center for E-Business Technology
Copyright 2008 by CEBT Modeling Example with Additional Features IDS Lab. Seminar - 9Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: #3 Modeling Dependencies Modeling Dependencies Association a 1 depends on another association a 2 IDS Lab. Seminar - 10Center for E-Business Technology
Copyright 2008 by CEBT Modeling Context Information: #4 Modeling Context Quality Modeling Context Quality Each association has – Quality Parameter Accuarcy of Sensor, Freshness, … – Qaulity Metric Representation of Quality Metric IDS Lab. Seminar - 11Center for E-Business Technology
Copyright 2008 by CEBT Complete Modeling Example IDS Lab. Seminar - 12Center for E-Business Technology
Copyright 2008 by CEBT Conclusion Explored the characteristics of context information Described a set ot context modeling concepts accommodate these Future work privacy IDS Lab. Seminar - 13Center for E-Business Technology
Copyright 2008 by CEBT 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 IDS Lab. Seminar - 14Center for E-Business Technology
Copyright 2008 by CEBT Interesting 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? IDS Lab. Seminar - 15Center for E-Business Technology