Icws10 lecue-gorronogoitia-gonzalez-radzimski-villa-presentation

Introduction Integrated Approach Architecture Components Experimentation Related Work Conclusion

SOA4All: An Innovative IntegratedApproach to Services Composition

Freddy Lécué1 Yosu Gorronogoitia2 Rafael Gonzalez2

Mateusz Radzimski2 Matteo Villa3

firstname.lastname@{manchester.ac.uk,atosresearch.eu, txt.it}

1The University of Manchester, Booth Street East, Manchester, UK2ATOS Research, Albarracín 25, Madrid, Spain

3TXT e-Solutions SpA, Via Frigia 27, Milan, Italy

IEEE 8th International Conference on Web ServicesJuly 5th - 10th, 2010

Miami, FL, USA

mailto:[email protected]




Outline

1 Introduction

2 An Integrated Approach for Service Composition

3 Architecture Components

4 Experimental Results

5 Related Work

6 Conclusion


Big Picture(Semi-automation of) service composition in the semantic web.

Here we address ...Semi-automated generation of optimal compositions wrt:

Properly formulated user requirements e.g., preferences,constraints, goal;On-demand generation of templates (or schema) basedcomposition.

So ...Compositions are not elaborated from scratch!... but rely on an end-to-end architecture of integratedcomponents: Template Generator, Composer andOptimizer.


Web service, Semantic Web and Semantic Web Services

Nowadays Web: syntax-based Web.Semantic Web is an extension of current Web in whichinformation is given well-defined meaning.

Ontology: a key enabling technology (RDF, OWL)Semantic web principles applied to web services

Give a semantics to services description;Description languages with a semantics;

1

Static URI, HTML, HTTPWWW Semantic Web

RDF, RDF(S), OWL

Semantics

DynamicUDDI, WSDL, SOAPWeb Services Intelligent Web

Services

Bringing the web to its full potential SAWSDL, OWL-S, WSMO ...


General Overview

Integration of 3 Main ComponentsService Template Generator, Composer and Optimizer

Reasoning

(ProM APIs)

Template

Generator

Services

JGAP)(Genetic Algorithms

Optimizer

Compositions

RelevantServices

Services Description

based Approach)(Parametric Design

Composer

Design−Time

Relevant

Semantic

Services Discovery

Ex

ecu

tion

Execution Logs

Abstract Activities

Repository of Compositions with

End User Constraintsand Preferences

Not Found

The end−user picks a

template that fulfills

her goals

Binding to ActivitiesConcrete Service

Compositions with

(Active BPEL)

(Fact++)

Atomic ServicesBPEL4SWS


General Overview

Integration of 3 Main ComponentsService Template Generator, Composer and Optimizer

RelevantServices

Services DescriptionSemantic−based

Compositions

Optimizer

(Genetic AlgorithmsJGAP)

Services

Monitoring and

Management

Infrastructure

Generator

Template

(ProM APIs)

Reasoning

Semantic

Relevant

Design−Time

Composer

(Parametric Designbased Approach)

Links([LecL06])(Fact++)

Ex

ecu

tion

Execution Logs

Abstract Activities

Repository of Compositions with

End User Constraintsand Preferences

Not Found

The end−user picks a

template that fulfills

[PedLMLDK10])(RDF Repository

her goals

Binding to ActivitiesConcrete Service

Compositions with

Atomic ServicesBPEL4SWS

Services Discovery ([JunAS10])

(Active BPEL)

Semantic


Integrated Approach: An Example

ContextUtilizing the cloud to expose (semantic web) services (with their nonfunctional properties) on product information (from differentcompanies) e.g., retrieving a product list, ordering a specific product.

GoalAggregation and classification of products from different service (e.g.,getProductData, getProductURI, getProductPrice) providers.

ProductData ≡ ∀hasID.ProductID u∀hasName.ProductNameu∀hasURI.URI

ProductURI ≡ ∀hasURI.URI

Product ≡ ∀hasID.ProductID u ∀hasName.ProductName

∀hasURI.URI u ∀hasPrice.ProductPrice

EuropeanProduct ≡ Product u ∀hasProvider .Europe

ProductIDList ≡ ∀hasID.ProductID

ProductID v >, ProductPrice v >, Europe v >


Template Generation (1)

IssueDesigning complex compositions: a difficult task for end-users.

ApproachContextual-driven filteringapproach to discover relevantpast executions (logs) .Process mining-orientedtechniques based on logs.Semantic Reasoning onservices descriptions.Discovery of possible templatesand their hierarchy.


Template Generation (2)

ResultsA selection of templates presented to end-users.

AdvantagesComposition of activities/services: Not from scratch!Collaborative generation of templates.Customized configuration of templates, depending on theabstraction level.

based Approach)

Generator

Template

(ProM APIs)

Composer

(Parametric Design

Monitoring and

Management

Infrastructure

Compositions

Optimizer


Design−Time


(Active BPEL)Exec

uti

on


Template Generation: An Example

ExampleAn E-Commerce template satisfying the goal: Aggregation andclassification of products of different service providers.

ANDby Provider AGetProduct

AbstractTask AbstractTask

AggregateProductfor Provider A

by Provider BGetProduct

AbstractTask

by Provider B

AbstractTask

ClassifyProduct

TaskImplicit Data Flow between Abstract Tasks of the Composition End NodeStart Node

Branching


Parametric Design Based Composition (1)

IssueGoal-based, semi-assisted, and context-aware service composition.

ApproachAdaptable concretizationtransformation using Multi-AgentSystems e.g., adding newontologies, services andtemplates.

Approach (Cont.)Elaboration of servicesbinding and data flow from anincomplete specification of acomposition.


Parametric Design Based Composition (2)

ResultAn executable composition of web services.

AdvantagesComposition problem defined by domain-specificsub-problems.Adaptable and flexible version to achieve composition.Knowledge-intensive configuration procedure.

Generator

Template

(ProM APIs)

Design−Time

Composer


Optimizer


Monitoring and

Management

Infrastructure

Compositions


(Active BPEL)Exec

uti

on


Parametric Design Based Composition: An Example

Example

Concretization of an E-Commerce template satisfying: Aggregationand classification of products of different service providers.

Semantic Link sl

by Provider AGetProduct

AbstractTask AbstractTask

AggregateProductfor Provider A

by Provider BGetProduct

AbstractTask

by Provider B

AbstractTask

ClassifyProduct

getClothingProductIDList

aggregateClothingProductPriceData

getFootwearProductPrice

Implicit Data Flow between Abstract Tasks of the Composition Start NodeTask/Service

Output ParameterInput Parameter

BranchingAND

ProductIDList

ProductURI

ProductPrice

getFootwear

EuropeanProduct

ProductID

ProductID

ProductIDList ProductPriceDatagetFootwear

BranchingAND

ProductURI

classifyEUFootwear

End Node


Optimization (1)

IssueHow select the most optimal among some achieving a same goal?

ApproachCriteria: Semantic and non functional properties of services.Multi-objective optimization: Genetic algorithm-based approach.

Selection

SelectionSemantics based

QoS baseds1 s5

s3 s6

s7

T4

T2 T3 T6

T7

T8T1 T5

s4

s8

s12, s

22, s

32, ...


Optimization (2)

ResultAn optimal composition of services on complementary dimensionsi.e., semantic and non functional.

Advantages

A general and extensible model to evaluate compositions.

CSOP (Constraints Satisfaction Optimization Problem)formalization.

Scalability of the Genetic algorithm-based approach despite theoff-line DL reasoning.

Generator

Template

(ProM APIs)

Design−Time

Composer


Compositions

Optimizer


Monitoring and

Management

Infrastructure


(Active BPEL)Exec

uti

on


Optimization: An Example

Example

Optimization of an E-Commerce composition satisfying: Aggregationand classification of products of different service providers.

ProductPriceData

Service Updated by the Composition Optimizer

getClothingProductIDList

aggregateClothingProductPriceData

ServiceOutput ParameterInput Parameter


ProductData


ProductID

ProductIDList AND

getClothing

ProductPrice

ProductIDList

ProductID

Product

Semantic Link sl End NodeStart Node

ProductPrice

ProductIDList

getFootwear

ProductPriceDatagetFootwear

ProductID

ProductID

ProductIDList BranchingAND

ProductURI

ProductURI

EuropeanProduct

classifyEUFootwear

getFootwearProductData

classifyFootwearProductPriceData

getFootwearBranching

ProductIDListaggregateClothing


Scalability of the Architecture

ContextUp to 200 users u design compositions, up to 25 services s each:(10u, 5s), (50u, 10s), (100u, 15s), (150u, 20s), (20u, 25s).

1 10

100 1000

10000 100000 1e+06 1e+07 1e+08 1e+09

Case 110u;5s

Case 250u;10s

Case 3100u;15s

Case 4 150u;20s

Case 5 200u;25s

Avg

. Tim

es (

ms)

in L

ogar

ithm

Sca

le

Case i: Users u;Services s

From aTemplate of 2 act. 4 act. 7 act. 10 act. 12 act.

Templates GenerationCompositionOptimization

Main Results

Template Generator: Number of logs, users and services.

Composer/Optimizer: Number of activities and services.


Integration in the EU SOA4All project Architecture

Part of a SOA4All: Service-oriented Architecture for Allhttp://www.soa4all.eu/, http://coconut.tie.nl:8080/dashboard/

http://www.soa4all.eu/

http://coconut.tie.nl:8080/dashboard/


Related Work

Template Generator

R. Agrawal, D. Gunopulos, F. Leymann,Mining process models from workflow logsIn EDBT, pages 469-483, ??, ??, 1998

Design Time Composer

P. Traverso and M. PistoreAutomated Composition of Semantic Web Services into Executable ProcessesIn ISWC, pages 380–394, Hiroshima, Japan, 2004.

Optimizer

L. Zeng, B. Benatallah, A.H.H. Ngu, M. Dumas, J. Kalagnanam, and H. Chang.A Qos-aware middleware for web services compositionIEEE Trans. Software Eng., 30(5):311-327, 2004

As an End-to-End Integration

P. Bertoli and J. Hoffmann and F. Lécué and M. PistoreIntegrating Discovery and Automated CompositionIn ICWS, pages 815-822, Salt Lake City, USA, July 2007.


An Integrated Approach to Services CompositionEnd-to-end composition and optimization:

Template Generator: Not to start from scratch.Composer: Further details to the generated templates.Optimizer: Maximization of the quality of compositions.

→ Validating in a realistic setting.

Future WorkScalability issues: Template Generation:

Context-based filtering to improve relevance of logs.Semantic-based mining for more relevant abstract process.

Adapting our architecture to contextual information.


An Integrated Approach to Services CompositionEnd-to-end composition and optimization:

Template Generator: Not to start from scratch.Composer: Further details to the generated templates.Optimizer: Maximization of the quality of compositions.

→ Validating in a realistic setting.

Future WorkScalability issues: Template Generation:

Context-based filtering to improve relevance of logs.Semantic-based mining for more relevant abstract process.

Adapting our architecture to contextual information.

Thanks for your attention!Freddy Lécué [email protected]

http://www.soa4all.eu/, http://coconut.tie.nl:8080/dashboard/

http://www.soa4all.eu/

http://coconut.tie.nl:8080/dashboard/

Icws10 lecue-gorronogoitia-gonzalez-radzimski-villa-presentation

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