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Managing Quality of Context in Pervasive Computing

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Title: Managing Quality of Context in Pervasive Computing


1
Managing Quality of Context in Pervasive Computing
  • Yingyi Bu, Shaxun Chen, Xianping Tao, Jun Li and
    Jian Lu
  • Department of Computer Science Technology,
    Nanjing University

Tao Gu Institute For Infocomm Research,
Singapore
2
Outline
  • Introduction
  • Related work
  • Quality measurement of context
  • Context model
  • Context Management Mechanism
  • Evaluations
  • Case Study
  • Conclusions

3
Introduction
  • Context awareness
  • A major software type in pervasive computing
    environment
  • Quality of software in pervasive computing
  • Quality of program
  • Quality of document
  • Quality of context

4
Motivating example
Im a context-aware music player, and play Jazz
for you.
Oh, I dont want Jazz now! I want classical music!
5
Context Mismatching
  • A serious quality issue in current context-aware
    software system
  • Context in real world ? context in computers
    view
  • What could we do?
  • To make context in computers approximate context
    in real world!

6
Related work
  • Existing context-aware middleware
  • SOCAM (IEEE pervasive computing)
  • CoBrA (IEEE internet computing)
  • CARISMA (IEEE trans. software engineering)
  • Active campus (ICSE 2003)
  • MobiPADs (IEEE trans. software engineering)
  • .

7
Weakness of those systems
  • Dont pay enough attention to quality of context.
  • In fact, lower quality of context may make users
    unpleasant.

8
Work for quality of context
  • Dey, et al. gave a novel solution for ambiguity
    resolution by user mediation. (ACM TOCHI)
  • Throw the responsibility of maintain quality of
    context to users.

9
Work for quality of context
  • Xu et, al. established a context consistency
    management mechanism (ESEC/FSE 2005)
  • providing a middleware architecture for
    inconsistency detection and resolution

10
Work for quality of context
  • Xu et, al. proposes an context consistency
    checking mechanism (ICSE 2006)
  • Incremental consistency checking

11
Our contribution
  • Propose quality measures for context
  • Establish a formulated context model
  • Use ontology based context consistency checking
  • Resolve context inconsistency automatically
  • Shorten the delay of context delivering

12
Quality measures for context
  • Delay Time
  • the time interval between the time when the
    situation happens in real world and the time when
    the situation is recognized in computers.

13
Quality measures for context
  • Context Correctness Probability
  • The accuracy rate of sensed data
  • What is the percent of context correct matching

14
Quality measures for context
  • Context Consistency Probability
  • the probability that contexts in computers are
    consistent
  • Dr.Gu in laboratory and Dr.Gu at home are two
    inconsistent contexts
  • We use the 3 quality measures as our design
    principles

15
Context Model
  • Ontology
  • a set of shared vocabularies of concepts and the
    interrelationships among these concepts
  • Entity
  • person, desk, classroom, meeting room, and campus
  • Relationship
  • the situations or predicates about entities
  • Dependency
  • the dependent relationship between Relationship

16
Example
17
Formulate to graph model
  • Context graph
  • Context
  • ER-graph
  • Dependency graph
  • Context repository
  • (see Section4.2 for details)

18
Context management mechanism
  • Context processing procedure
  • Inconsistency resolution in raw context level
  • Raw level refactoring in context repository
  • Context reasoning and context repository updating

19
Context processing procedure
20
Inconsistency resolution in raw context level
  • Definition Conflict Pair Set
  • Conflict pair set, is a set consisting of pairs
    such as (edgea, edgeb), in which corresponding
    contexta(contains edgea) conflicts with
    contextb(contains edgeb).
  • Definition Conflict Set
  • For a given edge set denoted as EdgeSet, if its
    members conflict with each other, we call EdgeSet
    a conflict set.

21
Inconsistency resolution in raw context level
  • Definition Relative Frequency-rf
  • A formula that calculates the rf value of a
    raw-edge edgei is shown as follow

22
RCIR algorithm
23
Raw level refactoring in context repository
  • Why?
  • Before context reasoning, the context repository
    should be updated in order to ensure incorrect or
    outdated high-level contexts are removed.

24
RLR algorithm
25
Context reasoning and context repository updating
  • Use rule reasoning and ontology reasoning orderly
  • Update context repository (similar to raw level
    refactoring)

26
Evaluations performance study
27
Evaluations effectiveness study
28
Application Case study
  • Smart office scenario

Web Server
Office Room
Meeting Room
show warning
edit slide
29
Effect
30
Implementations
  • We implement 3 versions
  • With a simplified quality management (SIR)
  • With inconsistency resolution on high level
    contexts (CIR)
  • With context management mechanism in this work
    (RCIR)

31
Error rate comparison
32
Conclusions
  • Context quality measures
  • Context model
  • Context management mechanism
  • Evaluations
  • Case study

33
Future work
  • Further improvement on quality of context
  • A theoretical model for quality of context

34
Reference
  • H. Chen, T.W. Finin, A. Joshi, and L. K. F.
    Intelligent agents meet the semantic web in smart
    spaces. IEEE Internet Computing, pages 6979,
    November 2004.
  • A. K. Dey and J.Mankoff. Designing mediation for
    context-aware applications. ACM Transactions on
    Computer-Human Interaction(TOCHI), 12(1)5380,
    2005.
  • W. G. Griswold, R. S. Boyer, S. W. Brown, and T.
    M. Truong. A component architecture for an
    extensible, highly integrated context-aware
    computing infrastructure. In Proceedings of the
    25th International Conference on Software
    Engineering (ICSE2003), Portland, Oregon, USA,
    pages 363373. IEEE Computer Society, 2003.
  • T. Gu, H. K. Pung, and D. Q. Zhang. Towards an
    osgibased infrastructure for context-aware
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    Scheibe, and C. Chatham. Context cube Flexible
    and effective manipulation of sensed context
    data. In Proceedings of the Second International
    Conference on Pervasive Computing (PERVASIVE
    2004), Vienna, Austria, volume 3001 of LNCS,
    pages 5168. Springer, 2004.

35
Reference
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  • X. Jiang, N. Y. Chen, J. I. Hong, K.Wang, L.
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36
Reference
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37
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