Phd Proposal (Slides)

8/10/2019 Phd Proposal (Slides)

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PhD Research Proposal

By:Keyvan Mohebbi

Supervisor:

Assoc. Prof. Dr. Suhaimi bin Ibrahim

April 2010


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Introduction

Literature Review

Comparative Evaluation of Semantic Web Service DiscoveryApproaches

Research Methodology

Preliminary and Expected Findings

Question and Answer

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Background of the Problem

Statement of the Problem

Objectives of the Study

Scope of the Study

Significance of the Study


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After the arising of SOA, the popularity of Web Services has beenincreased.

Most enterprises are deploying their services on the Web. Thisaugments the request for tools to maintain the processes involvedin the lifecycle of Web Services.

Discovery

SelectionComposition

Invocation

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Recent researches concentrate on theprocesses of the Web Services life cycle.

Discovery process includes comparing thegoals of service requesters with thedescriptions of Web Services.

At design time

At run time

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RQ1: What are Web Services and how are they discovered?

RQ2: Why the existing approaches for Web Service discovery arestill inadequate to satisfy all users requirements?

RQ3: How to (semi-) automatically discover the Web Services viaLogic-&Non-Logic techniques?

RQ4: How to use Logic-&Non-Logic techniques within WSMO?

RQ5:How effective is the proposed methodology in achievingSemantic Web Service discovery?

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1 To study and investigate the state of the art of Web Service discovery

approaches, their strengths and weaknesses.

2

To formulate and design a new approach for hybrid Web Service discovery thatintegrates logic based matchmaking with information retrieval techniques.

3 To develop a Web Service discovery tool that supports the proposed approach.

4 To evaluate the proposed approach and justify its findings.

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Web Service

SemanticWeb

SemanticWeb Service

Logic-&Non-Logic-based

Matchmaking

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Most of the organizations implement their B2B and B2Ctransactions in the form of Web Services. Need for efficient and effective discovery techniques to find an

appropriate Web Service from a large number of Web Services

The process of Web Service discovery should return thoseservices that fully or partially match with the requirementof a user. Need for enhanced discovery techniques to find all desired Web

Services

Not all Web Services follow a standardized format. Need for semantics to increase the capability of discovery

techniques by overcoming unimportant differences in WebServices

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Web ServiceSemantic WebSemantic Web ServiceWeb Service DiscoveryThe Architecture of Semantic Web Service DiscoverySemantic Web Service Frameworks

Taxonomy of Web Service Discovery SystemsComparing Syntax- and Semantic-based MatchmakingApproaches in Semantic Web Service DiscoveryInformation Retrieval Techniques


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Service Provider Service Requester

Invoke via SOAP

Service Repository


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Semantic WebProvides a common framework that allows data to

be shared and reused across applications andenterprises in a meaningful way.

OntologyA structure to express links between information

resources on the Web and connect them to formalterminologies.

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Refers to the automation of service usage tasks (discovery,selection, composition,), thus enabling intelligent WebServices.

How:by making Web Services machine-understandable viasemantically annotating them.

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The act of locating a machine-processabledescription of a Web Service that may have beenpreviously unknown and that meets certain

functional criteria. It involves matching a set ofcriteria with a set of Web Service descriptions.The goal is to find an appropriate Web Service.[W3C]

Semantic Web Service Discovery attempts tomake the process of discovery run automatically.

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Service

Provider

1: advertises

ServiceAdvertisement

Services

Registry2: searches

ServiceRequest

Service

Requester

3.b: matches

Matching

Engine

3.a: usesDomain

Ontologies

4: returns service matches

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Framework Submission Date Submitter(s)

OWL-S November 2004

France Telecom, Maryland Information and Network

Dynamics Lab at the University of Maryland, National

Institute of Standards and Technology (NIST), Network

Inference, Nokia, SRI International, Stanford University,

Toshiba Corporation, and University of Southampton

WSMO April 2005

DERI Innsbruck at the Leopold-Franzens-Universitt

Innsbruck, Austria, DERI Galway at the National Universityof Ireland, Galway, Ireland, BT, The Open University, and

SAP AG

WSDL-S October 2005 IBM

SAWSDL August 2007 W3C Recommendation

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CharacteristicsSemantic Web Service Framework

OWL-S WSMO WSDL-S SAWSDL

Supported Elements forAnnotating Semantically

Service, Operation,Input/Output,

Pre/Post-Condition


Pre/Post-Condition


Pre/Post-Condition

Service,Operation,

Input/Output

Directly Supporting Non-Functional Properties

Service Profile All Elements No Element No Element

Relation with WSDL

Defines connectivity toWSDL via Grounding

Model

Defines connectivity toWSDL via Grounding

Model

Specifiesannotations

directly in WSDL

Specifiesannotations

directly in WSDLSupport Complex Services

(Processes)Yes Yes No No

Ontology DescriptionLanguage OWL WSML User Choice User Choice

Formalism DL DL-FOL-LP User Choice User Choice

Support MultipleSemantic Annotations for

ServicesNo No Yes Yes

Support ConditionalResult

Yes Yes No No

Overall Result Good Good Medium Medium

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Centralized:rely on one single service repository, supported by a certain peer

Decentralized:rely on P2P technologies to distribute services over severalpeers

Architecture View

Manual:invoked by a human user and typically at design time

Automatic:invoked by a system agent either at design time or at run time

Automation View

Syntax-based: rely on matching keywords included in query against theservices descriptions stored in the registry

Semantic-based: rely on similarity matchmaking based on semantic serviceannotations and ontology matching

Matchmaking View

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Web Service Discovery Systems

Architecture View Automation View Matchmaking View

Centralized Decentralized Manual Automatic Syntax-based Semantic-based

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Syntax-based

Causes the huge number of availableservices, be filtered rather quickly.

Works on no particular annotations forservices, rather just simple WSDLdescriptions.

Limited by the ambiguities of naturallanguages.

Precludes fully automatic discovery,composition, invocation, andmonitoring of services, due to the lackof semantic understanding.

Semantic-based

Overcomes the inadequacies ofSyntax-based discovery.

Matching algorithms are more

complex than Syntax-based.

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Determine semantic relations between services based onlogical reasoning on the semantic annotations of services.Logic-based

Exploit semantics that are implicit in patterns or relativefrequencies of terms in service descriptions based on graphmatching, data mining, or information retrieval techniques.

Non-Logic-based

Use Logic-based matchmaking which exploits explicitsemantics besides Non-Logic-based matching which exploit

implicit semantics of the services.


Combine means of Logic-based and Syntax-based matching.Logic-&Syntax-based

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Information Retrieval (IR) is used to locaterelevantdocuments. It is not devised to find

simple matches to patterns. Boolean Indexing

Language Models

Probabilistic Retrieval

Vector Space Model

Latent Semantic Indexing

The majority of currentdiscovery approachesrely on VSM (OWL-S,WSMO, iMatcher,

SAWSDL-MX).

It is based on Syntaxmatching, so inheritsthe relative limitations.

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Comparative Benchmarks

Comparing Approaches of Semantic Web Service Discovery

Criteria for Classification Semantic Web Service Matchmakers

Classification of Semantic Web Service Matchmakers


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1. Performance:A discovery service with high performance shouldprovide both highPrecisionand high Recall.

Precision = Relevant Retrieved / Retrieved

Recall = Relevant Retrieved / Relevant

Relevant

Retrieved

Relevant Retrieved

All documents

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2. Query Response Time:The duration of discovery process.

3. Scalability:The degree to which the semantic matchingapproach supports retrieval of non semanticservices without the need to annotate them.

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CategoriesProminent

Approaches

BenchmarksOverall

ResultPerformance

QueryResponse

TimeScalability

Logic-basedOWL-S IDE (Srinivasan+ 06),

(Kifer+ 04),

(Somasundaram+ 06)Average Average Low Medium

Non-Logic-basedURBE (Plebani+ 09),

(Li+ 07)Low Low High Medium


OWLS-MX (Klusch+ 09),

iMatcher (Kiefer+ 08),

WSMO-MX (Kaufer+ 06),SAWSDL-MX2 (Klusch+ 09)

High High Low Good

Logic-&Syntax-basedLumina (Li+ 05),

FUSION (Kourtesis+ 08) Average N/A Low Medium

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Matching ElementsConsidered parts of service advertisement and service

request for matching. IO:Inputs and Outputs PE:Preconditions and Effects Non Functional Properties:Non functional aspects

(business category, name, QoS, cost, reliability, ) Other:WSDL descriptions, textual descriptions, operation

name and numbers,

Support for DoMThe approach enables ranking of the matching resultsaccording to their relevance to the user request.

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Multi-stage MatchingThe approach performs matching process in severalstages, between different elements to reach a morefine-grained and effective result.

Support for UDDIThe approach can support matching both semanticand non-semantic Web Services by combining thematchmaker and UDDI.

Support for Different OntologiesThe approach supports matching Web Services whoserequesters and providers use different ontologies.

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AccuracyThe ability to accurately capturing all the requirements that are soughtby requesters and offered by services. Based on: Matching Elements Support for DoM

Multi-stage Matching

ScalabilityBased on: Support for UDDI Support for Different Ontologies

Performance EvaluatedThe retrieval performance is experimentally evaluated by the authors ofthe approach. Based on: Precision Recall

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Matchmaking

Algorithm

Prominent

Approaches

Criteria

Overall

ResultMatching Elements

Supportfor DoM

Multi StageMatching

AccuracySupport for

DifferentOntologies

Support forUDDI

ScalabilityPerformance

EvaluatedIO PE

Non

Functional

PropertiesOther

Logic-based

(Kifer+ 04) Low Average Low-

OWL-S IDE (Srinivasan+ 06) Low Low Low-

(Somasundaram+ 06) Average Average Average-

Non-Logic-based(Li+ 07) Average High Average-

URBE (Plebani+ 09) Low Average Low-


WSMO-MX (Kaufer+ 06) High Low Average+

OWLS-MX (Klusch+ 09) Average Low Average+

iMatcher (Kiefer+ 08)

Average

Low

Average+

SAWSDL-MX2 (Klusch+ 09) Average Low Average+

Logic-&Syntax-based

Lumina (Li+ 05) Low Average Low-

FUSION (Kourtesis+ 08) Average Average Average-

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Research Procedure

Research Flow Chart

Operational Planning

Research Planning and Schedule


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LiteratureReview

The survey of Web Service languages and platforms which includes an investigation of existing languages andplatforms to support the description, provision and invocation of Web Services.

The survey of Web Service discovery which includes an investigation of applicable part of the relevant researchefforts, in particular, the Logic-&Non-Logic-based approaches.

Analysis ofRequirements

An Evaluation of State-of-the-Art approaches for Web Service discovery.

An inventory of the problems in Web Service discovery and an analysis of the raised requirements.

Development

Development of approach, based on logic and non-logic techniques in WSMO framework.

Development and implementation of the prototype application

Evaluation

Compare the proposed approach with other approaches.

Identify strengths and weaknesses of the proposed approach

Try to eliminate weaknesses of the proposed approach as much as possible

The experimental evaluation of using proposed approach in examples.

ENDIs

Complete?

START

Yes

No

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No Research Question Objective Activity Deliverable(s)

1What are Web Services and how

are they discovered?

To investigate Web Services concepts

to support Web Service discovery- Literature study - Result of literature review

2

Why the existing approaches for

Web Service discovery are still

inadequate to satisfy all users

requirements?

To evaluate all of the current WebService discovery approaches

- Literature study

-Comparative evaluation of

current approaches

- Results of comparative evaluation

3

How to (semi-) automatically

discover the Web Services via

Logic-&Non-logic techniques?

To present new approach for (semi-)

automated Web Service discovery

based on logic and non logic strategies

-Building a model for Web

Service discovery

-Designing an algorithm to

improve existing Web Service

discovery approaches

-The Web Service discovery model

- Source code of the algorithm

4How to use Logic-&Non-Logic

techniques within WSMO?

To integrate the designed matchmaker

with WSMO

- Designing the prototype tool

- Coding

- Integrating the tool

- Design documentation

- Source code

- Executable tool

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How effective is the proposed

methodology in achieving

Semantic Web Service discovery?

To evaluate effectiveness of the Web

Service discovery approach based on

proposed benchmark

- Analyzing the results - Analysis results

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No ActivityMonth

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

1 Literature Review

2 Comparative Evaluation

3 Problem Definition

5 Design the Proposed Approach

5 Develop the Prototype

6 Integrate the Application Tools

7 Test and Modify the Discovery Tool

8 Evaluate the Proposed Approach

9 Write up the Thesis Report

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Preliminary Findings (Proposed Framework)

Expected Findings


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Proposed Framework

Service

Requester

WSMX

Discovery

Matchmaker

Web

Service

Repository

Composer

Selector

GoalRepository

Logic-based

Non-Logic-based

Web Portal

Communication Manager

Discovery Manager

Mediator

Planner

Process Data

Invoker

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An (semi-) automated Semantic Web Servicediscovery approach based on the Logic-&Non-Logic-based matchmaker.

A supporting prototype tool to verify theapplicability of the proposed approach fordiscovery of Semantic Web Services.

An evaluation of the result of the proposedapproach with other current approaches todetermine the effectiveness of the approach.

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Thank you for your attention

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