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Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Tree Graph Views for a Distributed
Pervasive Environment
Tuyet Tram DANG NGOC (dntt@u-cergy.fr)Nicolas TRAVERS (Nicolas.Travers@prism.uvsq.fr)
ETIS Laboratory, University of Cergy-Pontoise
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Outline
1 Context
2 TGV : Tree Graph View
3 TGV for a Pervasive Environment
4 PADAWAN Prototype
5 Conclusion
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
1 ContextMotivationData Integration Issues
2 TGV : Tree Graph View
3 TGV for a Pervasive Environment
4 PADAWAN Prototype
5 Conclusion
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Motivation
Context
Integrate the pervasive vision of computing devices in order toallow any user anywhere in the world to query anything fromanywhere in the world.
Primergy
Doctor
Officer
Expert
Router
802.11
AP
IP
Sensor Network
Sink
Ad−Hoc Network
Internet
Fireman
Fireman
���
���
PADAWAN
PADAWAN
LDAP
SGBDWeb Server
News Feeder
Proxy
Emergency Unit
Proxy
ClientGIS
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Motivation
Context
Integrate the pervasive vision of computing devices in order toallow any user anywhere in the world to query anything fromanywhere in the world.
Primergy
Doctor
Officer
Expert
Router
802.11
AP
IP
Sensor Network
Sink
Ad−Hoc Network
Internet
Fireman
Fireman
���
���
PADAWAN
PADAWAN
LDAP
SGBDWeb Server
News Feeder
Proxy
Emergency Unit
Proxy
ClientGIS
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Motivation
Context
How to organize the graph, so a user with any type of profilecan connect on any node of the graph and access to otherdata that are dissiminated on nodes of the graph.
Nodes
Heterogeneousautonomous datasources
Proxies (both client andsource)
Heterogeneous clientapplications
Heterogeneous Network Links
S
P
C
S
S
S
S
S S
S
C
C
C
CS
S
C
C
C
S
S
S
S
CP
C
CP
P
P
S
Data Source
Client Terminal
Wireless Link
Wire Link
ProxyP
Legend
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
SourceHeterogeneous Data(relational,semi-structured)→common querylanguage and model :XML/XQuery
Database
Web
Site
FROM person p, car c
WHERE age>60
AND p.id=c.driver
AND c.color LIKE "RED"
SELECT p.name, p.address
ORDER BY p.address
name address
Well
Doeuf Cergy
Paris
GET http://example.com/persons.xml
GET http://example.com/car.xml
<person>
<name>Well</name>
<fname>Rose</fname>
<age>80</age>
<address>Paris</address>
</person>
<person>
<name>Cover</name>
...
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
SourceHeterogeneous Data(relational,semi-structured)→common querylanguage and model :XML/XQuery +Wrapper Database
Web
Site
XMLXQuery
Wrapper
XMLXQuery
Wrapper
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
SourceAutonomous Sourcesqueries more or lesssupported
Database
Web
Site
FROM person p, car c
WHERE age>60
AND p.id=c.driver
AND c.color LIKE "RED"
SELECT p.name, p.address
ORDER BY p.address
name address
Well
Doeuf Cergy
Paris
GET http://example.com/persons.xml
GET http://example.com/car.xml
<person>
<name>Well</name>
<fname>Rose</fname>
<age>80</age>
<address>Paris</address>
</person>
<person>
<name>Cover</name>
...
Here are the whole documents,
make the processing yourself !
Here are the exact results
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
SourceAutonomous Sourcesqueries more or lesssupported , internalinformation not available(cost model, statistics,schema)→Source Description Database
Database
Wrapper Wrapper
*card(T2)*CPU(restr)*TIO(restr)=0.0001ms
TIO=0.000282ms
CPU(Join)=card(T1)
CPU
*card(T2)*CPU(restr)*TIO(restr)=0.0001ms
TIO=0.000282ms
CPU(Join)=card(T1)
CPU
Cost model ? Cost model ?
Cost model ?
Cost model ??
Tps(statistic)=3ms (Avg)Tps(Calibration)=4*CPU(Join)
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
Client Heterogeneityaccess permission, userpreferences, terminalcapabilities→Client profile + View
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
Data integrationevaluate query ondistributed node→mediation + Sourcedescription Wrapper
Source
Wrapper
Source
Wrapper
Source
Wrapper
Source
Mediator
Client
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Data Integration Issues
Data Integration Issues
Source
Heterogeneous Data (relational, semi-structured)→common query language and model : XML/XQuery +WrapperAutonomous Sources queries more or less supported,internal information not available (cost model, statistics,schema)→Source Description
Client Heterogeneity access permission, user preferences,terminal capabilities→Client profile + View
Data integration evaluate query on distributed node→mediation + Source description
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
1 Context
2 TGV : Tree Graph View
3 TGV for a Pervasive Environment
4 PADAWAN Prototype
5 Conclusion
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Tree Graph View [ Travers and Dang-Ngoc 2004-2007 ]
declare function local:f($doc as xs:string) as element()
{for $x in (doc(?rev.xml?)/review|doc(?$doc?)/catalog)
[. contains(?Robin Hobb?)]/book/[.//price > 15]
where
some $y in $x/comments
satisfies contains ($y, ?Excellent?)
order by $x/@isbn
return
<book>
{$x/@isbn} <price>{$x//price/text()}</price>
{ if (count($x/title) > 2)
then
{ for $z in doc(?books.xml?)/book
where $z/@isbn = $x/@isbn
return <title>{($z/title)[3]}</title>
}else<title/>
} </book>
}
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Tree Graph View [ Travers and Dang-Ngoc 2004-2007 ]
XQuery has a (too) rich syntax :XPathConstraints, FilterQuantifiersDocument constructionNesting, Aggregates, SortsConditional operators, Set operatorsSequences, Function
Hard to parse, process and identify subpart and dependancies.
XQuery XML
Query
Processor
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Tree Graph View [ Travers and Dang-Ngoc 2004-2007 ]
Model based on Tree Pattern matching that :
Supports Full untyped XQuery [ WEBIST2007 ]
Provides an intuitive representation [ DASFAA 2007 ]
Designed for distributed environment [ IBIS Journal 2006 ]
Support for optimisation and for evaluation [ ICEIS 2007 ]
logicalTGV
AnnotatedTGV
XQuery XML
Application
profileOptimization Evaluation
Rule Processing
XQueryCanonized
TGVEvaluationannotation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Example
”list every buildings occupied by more than 100 inhabitants, and for each, get the districtand the list of maximum temperature measured by the sensors located in the samedistrict.”
for $a in /buildings/buildingwhere $a/description/inhabitant > 100return
<districtMonitoring><location> {$a/district} </location><temperatures>
{ for $b in //sensorwhere
$b/deploymentArea/district = $a/districtreturn
<temperature>{$b/max temp}
</temperature>}</temperatures>
</districtMonitoring>
<districtMonitoring><location> Yellow Lake </location><temperatures>
<temperature> 14 </temperature></temperatures>
</districtMonitoring><districtMonitoring>
<location> Green Valley </location><temperatures>
<temperature> 163 </temperature><temperature> 25 </temperature><temperature> 43 </temperature>
</temperatures>
</districtMonitoring>
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Example
”list every buildings occupied by more than 100 inhabitants, and for each, get the districtand the list of maximum temperature measured by the sensors located in the samedistrict.”
for $a in /buildings/buildingwhere $a/description/inhabitant > 100return
<districtMonitoring><location> {$a/district} </location><temperatures>
{ for $b in //sensorwhere
$b/deploymentArea/district = $a/districtreturn
<temperature>{$b/max temp}
</temperature>}</temperatures>
</districtMonitoring>
$a $b
> 100
temperatures
location
districtMonitoring
description
building
buildings
inhabitant
sensor
district
deploymentAreadistrict
temperature
$t
max_temp=
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Generic Annotation for any type of
Information
A layer per informationtype
Information on any set ofTGV elements (includingannotation)
Any granularity, possiblerecovering
Generic Annotation (ex.several type of cost modelwith complex formulas)
4) Logical TGV
description
building
inhabitant
temperatures
locationdeploymentArea
deploymentArea max_temp
location
$a $b sensor
sensor$t
> 100
buildings
=
district
annotation
3) Physical TGV
annotation
with cost2) Physical TGV
annotation
1) Physical TGV
with evaluation
with location
description
building
district deploymentArea
$a $b sensorbuildings
=
deploymentArealocation
temperatures
> 100
inhabitant
sensor$t
max_temp
location
description
building
inhabitant
district
temperatures
location
deploymentArea max_temp
location
$a $b sensor
sensor$t
> 100
buildings
=
deploymentArea
temperatures
location
$t
buildings
=
deploymentArea
sensor
max_tempdeploymentArea
$b
sensorlocation
> 100
inhabitant
$a building
districtdescription
Yellow Lake | 1678
Rhode Forest | 1986
Green Valley | 82761
Yellow Lake | 14
Green Valley| 163
Green Valley| 25
Green Valley| 43
C2=cost_card*0.02cp=max(C1, C2)
cost=cp+Op
CS1=Cost(S1) Cost(S2)C1=CS1*sel*CS2*IO
Source1
Mediator
Source2, Source 3
Mediator
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
Rule
Annotated TGV Pattern → Annotated TGV Patterncondition” Conclusion”
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
=
card ($x)*card($y)*CPU_unit
CPU_unit=0,02
=
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
person
name age refsrc person
name age refsrcFR_SRC2
card
50,000
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
=$x $y
bind−join
card ($x) > card ($y)
=
bind−join
$y $x
card ($x)card ($y)
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
= =$a $b $a $b
join (eval ($a), eval ($b))
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV : Rules
Rules for :
Local Transformation
Optimization
Local Evaluation
Distributed Evaluation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
1 Context
2 TGV : Tree Graph View
3 TGV for a Pervasive EnvironmentTGV EvaluationTGV*
4 PADAWAN Prototype
5 Conclusion
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV Mobile Agent
Initiated by the client
Evaluated on the fly
Parallel evaluation :
cloning the TGV on somenodes.evaluation rules located onthe node.
Leaves of the recursion tree onsource node. Source node fill theevaluation annotation layer.
P
S
S
S
SS
S
C
S
SP
TGV
TGV
TGV
TGV
TGV
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV Mobile Agent
Initiated by the client
Evaluated on the fly
Parallel evaluation :
cloning the TGV on somenodes.evaluation rules located onthe node.
Leaves of the recursion tree onsource node. Source node fill theevaluation annotation layer.
P
S
S
S
SS
S
C
S
SP
TGVeval
TGVeval
TGVeval
TGVeval
TGVevalTGV
eval
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV : Evaluation
Evaluation rules :
Evaluation onSourceWrappers
Join
Nest
Finalprojection
$a $b
> 100
temperatures
location
districtMonitoring
description
building
buildings
inhabitant
sensor
district
deploymentAreadistrict
temperature
$t
max_temp=
Yellow Lake | 14Green Valley | 163Green Valley | 25Green Valley | 43
Yellow Lake | 678Rhode Forrest| 1986Green Valley | 82761
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV : Evaluation
Evaluation rules :
Evaluation onSourceWrappers
Join
Nest
Finalprojection
$a $b
> 100
temperatures
location
districtMonitoring
description
building
buildings
inhabitant
sensor
district
deploymentAreadistrict
temperature
$t
max_temp=
Green Valley | 82761 | 163Green Valley | 82761 | 25Green Valley | 82761 | 43
Yellow Lake | 678 | 14
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV : Evaluation
Evaluation rules :
Evaluation onSourceWrappers
Join
Nest
Finalprojection
$a $b
> 100
temperatures
location
districtMonitoring
description
building
buildings
inhabitant
sensor
district
deploymentAreadistrict
temperature
$t
max_temp=
Green Valley | 82761 | 163Green Valley | 82761 | 25Green Valley | 82761 | 43
Yellow Lake | 678 | 14
14
163
25
43
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV Evaluation
TGV : Evaluation
Evaluation rules :
Evaluation onSourceWrappers
Join
Nest
Finalprojection
$a $b
> 100
temperatures
location
districtMonitoring
description
building
buildings
inhabitant
sensor
district
deploymentAreadistrict
temperature
$t
max_temp=
Green Valley | 82761 | 163 | | 25 | | 43
Yellow Lake | 678 | 14
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
TGV*
TGV* : Sources Description
How to annotate the TGV?→TGV* to describe sources inan exhaustive manner.
Dataguide : source part(STP) of the TGV withannotation
Annotations
Set of rules (for operators)
TGV*
person
adressstreettownname
car
idimmmodel
appbrandcol
Rules
Join (cost−memoryà
Restriction (cost exec_time)
Join (cost−memory)
personn
id
immmodelbrandcol
name
person
town
id appnameadress
street modelimm
car
brandcol
car
app
streettown
adress
Cost (exec_time)
Dataguide
Cost (memory)
Location
personn car
adress
streettown
id
immmodel
app
brandcol
name
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
1 Context
2 TGV : Tree Graph View
3 TGV for a Pervasive Environment
4 PADAWAN PrototypeNodes and Agents
5 Conclusion
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Nodes and Agents
PADAWAN : a Multi-Agent Plateform
Client Oracle Wrapper
Sensor WrapperRules Forwarders
Wrappers Rules
Forwarders
Web Site WrapperClientForwarders
Node 0
Node 2Node 1
Node 3
Node 4
Node 5Node 6
Forwarders
Node 7
ForwardersRulesCache
1 2
3
4
5
6
TGV *Profile
TGV
TGV *
TGV *
TGV
ProfileProfile
TGV *
It is the agentslocated on thenode that definethe functionalitiesof the node.
Client Node : Client and Presentation Agents
Source Node : Wrapper Agent
Proxy Node : Cache, Router, and Rules Agents
Repository Node : Agent Library
Prototype PADAWAN (a Plateform for All Devices Accessingthe World And Neighbourhood) on http ://padawan.ensea.fr/
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
1 Context
2 TGV : Tree Graph View
3 TGV for a Pervasive Environment
4 PADAWAN Prototype
5 ConclusionBibliographySimulation
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Conclusion
TGV Mobile Agent
Full untyped-XQuery evaluation
Evaluation through the Multi-Agents PlatformPADAWAN graph
Dynamic Optimization
Current Work : TGV* Mobile Agent
describe data
generic enough to describe all information known on asource.
abstract TGV*
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Bibliography
Publications on TGV and PADAWANDang-Ngoc, T.-T. and Travers, N. (2007).
Tree graph views for a distributed pervasive environment.In the 1st International Conference on Network-Based Information Systems (NBIS), Regensburg, Germany.
Liu, T., Dang-Ngoc, T.-T., and Laurent, D. (2007).
Cost framework for a distributed semi-structured environment.In in the proceedings of the International workshop Database Management and Application over Networks -DBMAN (APWeb/WAIM Workshop), Huangshan, China.
Travers, N. and Dang-Ngoc, T.-T. (2007).
An extensible rule transformation model for xquery optimization.In The 9th International Conference on Enterprise Information Systems (ICEIS), Madeira, Portugal.
Travers, N., Dang-Ngoc, T.-T., and Liu, T. (2006).
Tgv : an efficient model for xquery evaluation within an interoperable system.International Journal of Interoperability in Business Information Systems (IBIS), 3.ISSN : 1862-6378.
Travers, N., Dang-Ngoc, T.-T., and Liu, T. (2007a).
An efficient evaluation of xquery with tgv.In the 3rd International Conference of WEB Information Systems and Technologies (Web-IST), Spain.
Travers, N., Dang-Ngoc, T.-T., and Liu, T. (2007b).
Full untyped xquery canonisation.In in the proceedings of the International workshop on Emerging Trends of Web Technologies andApplications -WebETrends (APWeb/WAIM Workshop), Huangshan, China.
Travers, N., Dang-Ngoc, T.-T., and Liu, T. (2007c).
Tgv : a tree graph view for modelling untyped xquery.In the 12th International Conference on Database Systems for Advanced Applications (DASFAA), Thailand.
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Discrete Event Simulation
P1
S3
C1
C
S
S
P
PC
C
P2
S1
S2
r(C1,P1,P2)
r(C1,P1,P2)
r(C1,P1)
r(C1,P1)
4a−
SINK
r(C1)
R(C1,P1,P2)
R(C1,P1,P2)
R(C1,P1)
R(C1,P1)
R(C1)1−
2a−
2b−
6−
3c−
5a−
3a−
4b−
3b−
Sources alreadylocated located
route of the requestrandomly generated,using randomly 0-Nsources
time of service, andqueries generationparameterized
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation
Mediation Architecture
Direct Access to sources
Bottleneck on mediator
nbclients = 3 nbproxy = 1 nbsources = 6
C3
C2
C1 S1
S2
S3
S4
S5
S6
P1
(a) Mediation Infrastructure
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation
P2P Network
Each Peer is a mediator
Direct Access to sources
Load on each peer
Each peer knows how toresolve a whole request
nbclients = 3 nbproxy = 5 nbsources = 6
S1
S2
S3
S4
S5
S6
P2
P3
P4
P5
P1
C3
C2
C1
(b) Infrastructure PàP
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation
Padawan Network
A peer has access to someother peers and eventuallyto some sources
Distribution of the queryevaluation
Evaluation depending onthe peers capabilities
Distributed waiting time
nbsources = 6nbproxy = 5nbclients = 3
C3
C2
C1S1
S2
S3
S4
S5
S6
P1
P2
P3
P4
P5
(c) Infrastructure PADAWAN
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation Result
Times / Number of queries to process in the system 20 queriesgenerator (=clients), 100 sources, For P2P and PADAWAN :20 peers.
Mediator : Bottleneck
P2P Architecture betterthant PADAWANArchitecture
Linear
graph
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation Result
Times / Number of queries to process in the system 20 queriesgenerator (=clients), 100 sources, For P2P and PADAWAN :20 peers.
Mediator : Bottleneck
P2P Architecture betterthant PADAWANArchitecture
Linear
But :Mean waiting time better inPADAWAN
graph-tw
Département des Sciences Informatiques
Context TGV : Tree Graph View TGV for a Pervasive Environment PADAWAN Prototype Conclusion
Simulation
Simulation limitation
Opening connection delay
PADAWAN : few connection per proxy→all connections can be left opened.P2P : each peer can potentially reach any source→can’t maintain all opening/closing connection→consider connection delay
Nodes capabilities
In the major P2P networks, equivalent nodes with samecapabilities (or 2 or 3 categories with Superpeer andnormal peer)PADAWAN queries can be evaluated on nodes withdifferent capabilities
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