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
Outline
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Introduction
Related work
Quality measurement of context
Context model
Context Management Mechanism
Evaluations
Case Study
Conclusions
Introduction
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Context awareness
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A major software type in pervasive
computing environment
Quality of software in pervasive
computing
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Quality of program
Quality of document
Quality of context
Motivating example
I’m a context-aware
music player, and play
Jazz for you.
Oh, I don’t want
Jazz now! I want
classical music!
Context Mismatching
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A serious quality issue in current contextaware software system
Context in real world ≠ context in
computer’s view
What could we do?
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To make context in computers approximate
context in real world!
Related work
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Existing context-aware middleware:
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SOCAM (IEEE pervasive computing)
CoBrA (IEEE internet computing)
CARISMA (IEEE trans. software engineering)
Active campus (ICSE 2003)
MobiPADs (IEEE trans. software engineering)
…….
Weakness of those systems
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Don’t pay enough attention to quality of
context.
In fact, lower quality of context may make
users unpleasant.
Work for quality of context
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Dey, et al. gave a novel solution for
ambiguity resolution by user mediation.
(ACM TOCHI)
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Throw the responsibility of maintain
quality of context to users.
Work for quality of context
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Xu et, al. established a context consistency
management mechanism (ESEC/FSE 2005)
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providing a middleware architecture for
inconsistency detection and resolution
Work for quality of context
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Xu et, al. proposes an context consistency
checking mechanism (ICSE 2006)
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Incremental consistency checking
Our contribution
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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
Quality measures for context
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Delay Time
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the time interval between the time when the
situation happens in real world and the time
when the situation is recognized in computers.
Quality measures for context
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Context Correctness Probability
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The accuracy rate of sensed data
What is the percent of context correct
matching
Quality measures for context
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Context Consistency Probability
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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
Context Model
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Ontology
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Entity
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person, desk, classroom, meeting room, and campus
Relationship
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a set of shared vocabularies of concepts and the
interrelationships among these concepts
the situations or predicates about entities
Dependency
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the dependent relationship between “Relationship”
Example
Formulate to graph model
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Context graph
Context
ER-graph
Dependency graph
Context repository
(see Section4.2 for details)
Context management mechanism
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Context processing procedure
Inconsistency resolution in raw context
level
Raw level refactoring in context repository
Context reasoning and context repository
updating
Context processing procedure
Inconsistency resolution in raw
context level
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Definition: Conflict Pair Set
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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
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For a given edge set denoted as EdgeSet, if its
members conflict with each other, we call
EdgeSet a conflict set.
Inconsistency resolution in raw
context level
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Definition: Relative Frequency−rf
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A formula that calculates the rf value of a
raw-edge edgei is shown as follow:
RCIR algorithm
Raw level refactoring in context
repository
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Why?
Before context reasoning, the context
repository should be updated in order
to ensure incorrect or outdated highlevel contexts are removed.
RLR algorithm
Context reasoning and context
repository updating
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Use rule reasoning and ontology reasoning
orderly
Update context repository (similar to raw
level refactoring)
Evaluations – performance study
Evaluations – effectiveness study
Application Case study
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Smart office scenario
FollowMe Infrastructure
Web Server
Meeting Room
download slide
Office Room
upload slide
show
warning
Stranger
edit
slide
Tom
Effect
Implementations
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We implement 3 versions
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With a simplified quality management (SIR)
With inconsistency resolution on high level
contexts (CIR)
With context management mechanism in this
work (RCIR)
Error rate comparison
Conclusions
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Context quality measures
Context model
Context management mechanism
Evaluations
Case study
Future work
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Further improvement on quality of context
A theoretical model for quality of context
Reference
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