IntelligentIntelligent SSpacepace國立台灣大學資訊工程研究所 智慧型空間實驗室國立台灣大學資訊工程研究所 智慧型空間實驗室
Managing Quality of Context Managing Quality of Context in Pervasive Computingin Pervasive Computing
AuthorsAuthors
Y.Bu, T.Gu, X.Tao, J.Li, S.Chen, and J.LuY.Bu, T.Gu, X.Tao, J.Li, S.Chen, and J.Lu
Proceedings of 6th IEEE International Conference on Quality Software (QSIC’06)
ReporterReporter
C.F.Liao (C.F.Liao ( 廖峻鋒廖峻鋒 ))
Apr 27,2007Apr 27,2007
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Context-Aware Middleware for the Smart Context-Aware Middleware for the Smart EnvironmentsEnvironments
OSGi
Middleware forSmart Home
Middleware forSmart Environments
Univ. of Florida (USA)(OSCAR)(OSCAR)
Semantic Web Ontology
新加坡大學新加坡大學(SOCAM)(SOCAM)
Agent Oriented
Georgia TechGeorgia Tech(Context-Toolkit)(Context-Toolkit)
Maryland Univ.Maryland Univ.(CoBra, SOUPA)(CoBra, SOUPA)
HK PolytechnicHK Polytechnic(MobiPADS)(MobiPADS)
Washington UniversityWashington University (LIME)(LIME)
Jini
BerkleyBerkley(Context-Fabric)(Context-Fabric)
Univ. College LondonUniv. College London(CRISMA)(CRISMA)
HCI JournalIEEE Transactions on Software Engineering
ACM Transactions on Software Engineering and Methodology
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion
(RLR and the Case Study sections are skipped in this presentation)
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Using RDF as a Common Context Using RDF as a Common Context Representation FormatRepresentation Format
Sensor
ContextProvider
ContextProvider
Id=John,activity=lie down,place= bed
Activity Recognition
Module
Activity Recognition
Module
raw data Context(John,has posture,lie-down)
(John,location,bed)RDF
SOCAMSOCAM
RDF = Resource Description FrameworkRDF = Resource Description Framework
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Describing Data with RDFDescribing Data with RDF
RDF is a W3C standard, which has the following RDF is a W3C standard, which has the following capabilitiescapabilities Able to describe most kinds of data. Able to describe the structural design of data sets. Able to describe relationships between data.
Format: Format: Example:Example:
(bedroom, contains, light1) (light1, state, “on”)
(subject, predicate, object)
Actually, all resources are represented by URI, for example:http://www.foo.bar/myhome/mybedroom#light1
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Representing Context with RDF NetworkRepresenting Context with RDF Network
LightSwitch1 state
on Literal
Resource
Bedroom
locatedIn
size
9
contains
TV1
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The Structure of this PaperThe Structure of this Paper
Current Context Applications can not work well in real world
Low Context Quality!
What do we mean by low “Context Quality”?Context Quality Model
A Context Management mechanism to Improve Context Quality.
startTimeedgeecurrentTim
ttledgefrequencyedge
rfedgei
ii
i .
..
.
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MotivationMotivation
Context-awarenessContext-awareness plays a key role in a plays a key role in a paradigm shift from traditional desktop paradigm shift from traditional desktop computing to pervasive computing.computing to pervasive computing.
Most context-aware applications are unlikely to Most context-aware applications are unlikely to work well in the real world.work well in the real world.
Two major factors:Two major factors: Inconsistent contexts The limited data gathering frequency
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Context Repository
Context Inconsistency Context Inconsistency
Room 311 Aisle3
(Mary,walkIn,Room311)
(Mary,walkIn,Room311)
(Mary,walkIn,Aisle3)
(Room311,disjointWith,Aisle3)
(Mary,walkIn,Aisle3)
t t+2t+1
Conflict!
It seems that we either have to check context repository constantly or some conflict-resolving techniques have to be developed.
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Data Gathering FrequencyData Gathering Frequency
t t+5 t+10
10 10 10 11 12 14 10 12 10 10 12
12
Real World
System
The temperature data gathering period is 2 seconds.
10 1010 10 12 12 10 10 10 10
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion
(RLR and the Case Study sections are skipped in this presentation)
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Evaluating Context QualityEvaluating Context Quality
Context Quality MeasurementsContext Quality Measurements Delay Time Context Correctness Probability Context Consistency Probability
A well-designed context-aware system should A well-designed context-aware system should have:have: Low Delay Time High Context Correctness Probability High Context Consistency Probability
Context Pooling
RCIR / RLR
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Delay TimeDelay Time
t t+k
An event happens
System know what happens in the real world
Sensor Data Gathering
ContextProcessing
Service Provision
Delay Time
The time interval between an event happens in real world and when it is recognized by the system.
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Context Correctness ProbabilityContext Correctness Probability
t t+5 t+10
TemperatureContext
10
Context Correctness Probability = 7/ 11 = 0.64Context Correctness Probability = 7/ 11 = 0.64
10 10 11 12 14 10 12 10 10 12
10 10 11 10 10 12
Real World
System
10 10 11 10 10
The raw context gathering period is 2 seconds
Error due to context conflict resolution
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion
(RLR and the Case Study sections are skipped in this presentation)
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Context and Context RepositoryContext and Context Repository
Room342CSIE
BuildinglocatedIn
BABA nodeedgenode ,,
Context Graph (Extended RDF Network)Context Graph (Extended RDF Network)
Context RepositoryContext Repository
ContextContext
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Context Graph is essentially an extended RDF Context Graph is essentially an extended RDF Network. Network.
Context GraphContext Graph
Mary
Room311
CSIE Building
locatedIn
locatedIn
locatedIn
Node
Implicit Edge Meta Edge
Raw Edge
What are the benefits of this extension…?
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Persistent and Dynamic EdgesPersistent and Dynamic Edges
Room342CSIE
BuildinglocatedIn
TomCSIE
BuildinglocatedIn
Persistent Edge.The relationship that is unlikely to change.
Dynamic Edge.The relationship that is changing with time.
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion
(RLR and the Case Study sections are skipped in this presentation)
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Context Processing ProcedureContext Processing Procedure
Raw Context Gathering
InconsistencyResolution
Row LevelRefactoring
ContextRepository
Rule-basedReasoning
Rules
TriggeringApplications
Updating ContextRepository
Ontology-basedReasoning
OntologyContextRepository
RCIR RLR
JENA
Not-addressed in this paperJENA is a Semantic Web Framework for Java, Welcome to the lecture on 5/17 at R310
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Inconsistency Resolution (Definitions)Inconsistency Resolution (Definitions)
Conflict PairConflict Pair
Conflict Set Conflict Set ba edgeedge ,
Mary Room311locatedIn
Mary Room311locatedIn
Conflict
ba edgeedge ,
dc edgeedge ,
fe edgeedge ,
hg edgeedge ,We use an edge to represent a context instance here.
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Inconsistency Resolution by Inconsistency Resolution by RFRF
Core ideaCore idea When resolving conflicts, more frequent contexts
have more priority than infrequent ones. RF (Relative Frequency): Using TTL (Time to live) to
transform static frequency to dynamic frequency.
Term definitionsTerm definitions Edge TTL
The time period in which a context is valid.
Edge Frequency Edge Start Time
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Relative Frequency ( Relative Frequency ( rf ))
ExampleExample TTL = 2s Frequency = 1/6 (次 /s)
t t+6t+2 t+12t+8
startTimeedgeecurrentTim
ttledgefrequencyedge
rfedgei
ii
i .
..
.(for persistent edges)
(for dynamic edges)
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Raw Context Inconsistency Resolution Raw Context Inconsistency Resolution (RCIR)(RCIR)
Raw Context Sets(Mary,walkIn,Room311)
(John,walkIn, A)
(Mary,walkIn, Aisle3)
(Tom,walkIn, A)
Jena’s Conflict Detection Mechanism
(edge,edge)
Conflict Sets (edge,edge)(edge,edge)
(edge,edge)
(edge,edge)
Next edge type
Consistent Sets(edge,edge)(edge,edge)
No more edges
(walkIn,walkIn),rf=0.9
(walkIn,walkIn),rf=0.8
(walkIn,walkIn),rf=0.6
(walkIn,walkIn),rf=0.4
Preserve a pair that have highest rf value.
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Context RefactoringContext Refactoring
If a raw edge is changed, its related implicit edgIf a raw edge is changed, its related implicit edges should also be changed.es should also be changed.
The RLR (Raw Level Refactoring)algorithm aims The RLR (Raw Level Refactoring)algorithm aims to remove edges that are dependent to in-existinto remove edges that are dependent to in-existing raw edges.g raw edges.
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Conflict!
Context Refactoring: An ExampleContext Refactoring: An Example
LightSwitch state
on
Toilet 1
locatedIn
Aisle 3
contains
Tom
Bedroom contains
contains
contains
(Toilet, contains,”Tom”) (Aisle 3, contains, “Tom”)
(Bedroom, contains, “Tom”)
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Context PoolingContext Pooling
Context Repository
Application A RDQL
Context Pool
Context Change
InvalidateContext Manager
Pooling the unchanged context Pooling the unchanged context nodes in local cache to reduce nodes in local cache to reduce network traffic overhead.network traffic overhead.
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion
(RLR and the Case Study sections are skipped in this presentation)
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Performance EvaluationPerformance Evaluation
2 Intel Xeon CPUs, 4G RAM, Linux OS2 Intel Xeon CPUs, 4G RAM, Linux OS SensorSensor
Mica / Cricket (MIT)
PlatformPlatform OSGi Platform 1257 RDF triples
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ConclusionsConclusions
The authors proposed a Context Quality The authors proposed a Context Quality Measurements Model based on their Measurements Model based on their experiences of designing context-aware experiences of designing context-aware applications.applications.
Several mechanisms are proposed to Several mechanisms are proposed to increase the context quality:increase the context quality: ER-Ontology Context Model RCIR / RLR Context Pooling
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DiscussionsDiscussions
The limitation of context resolution mechanism.The limitation of context resolution mechanism. Raw context gathering period.Raw context gathering period.
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Limitations of Context ResolutionLimitations of Context Resolution
Sensor
Activity Recognition Agent
OSGiPlatformApplications
Bio-informationAgent
??
Raw Data
Bill is walking
Bill is sleeping
Actually, I’m sleep walking
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Raw Context Gathering PeriodRaw Context Gathering Period
The gathering period is important to both The gathering period is important to both performance and effectiveness.performance and effectiveness. To short – the processing mechanism will degrade to
piece by piece processing. To long – to much inconsistency, the RCIR algorithm
will have low performance.
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OutlineOutline
IntroductionIntroduction Quality-based Context ManagementQuality-based Context Management
Context Quality Measurements ER-Ontology Context Model Quality-based Context Processing Context Pooling
ExperimentsExperiments ConclusionConclusion