Grid Service Discovery Grid Service Discovery with Rough Setswith Rough Sets

Maozhen Li, Member, IEEE, Bin Yu, Omer Rana, and ZidMaozhen Li, Member, IEEE, Bin Yu, Omer Rana, and Zidong Wang, Senior Member, IEEEong Wang, Senior Member, IEEE

IEEE TRANSACTION S ON KNOLEDGE AND DATA ENIEEE TRANSACTION S ON KNOLEDGE AND DATA ENGINEERING, VOL. 20, NO. 6, JUNE 2008GINEERING, VOL. 20, NO. 6, JUNE 2008

Present by Chen, Ting-WeiPresent by Chen, Ting-Wei

2

Outline

Introduction The Design of ROSSE QoS Modeling ROSSE Case Study ROSSE Evaluation Conclusions

3

Introduction

ROSSE • Rough sets-based search engine

• Discovery Grid service

• Maximize user satisfaction in service discovery

Evaluate the discovery of computing services • Accuracy

• Efficiency

4

The Design of ROSSE (cont.)

Service publication Service discovery

5

The Design of ROSSE (cont.)

6

The Design of ROSSE (cont.)

Step 1• advertise the service to ROSSE through a

Web user interface

Step 2• Load into the ROSSE Service Repository

• Names

• Properties

7

The Design of ROSSE (cont.)

Step 3• Publish service ontology that can be defined

in OWL

Step 4• Load into the ROSSE Ontology Repository

• Inference engine to infer the semantic relationships of properties

8

The Design of ROSSE (cont.)

Step 5-6

Step 7-9

Step 10-11

Step 12-13

Step 14-16

9

The Design of ROSSE (cont.)

Step 5• Post a service query to ROSSE

• Service category of interest

• Expected service properties

• Via its Web user interface

Step 6• Pass to the Irrelevant Property Identification c

omponent

To page 8

10

The Design of ROSSE (cont.)

Step 7• Access the ROSSE Service Repository

Step 8 • Identify and mark the properties of advertised

services

• Define in the ROSSE Ontology Repository

Step 9• The query is passed to the DPR component

To page 8

11

The Design of ROSSE (cont.)

Step 10• Access the ROSSE Service Repository to

identify and mark dependent properties

Step 11• The DPR component invokes the Service

Similarity Computing (SSC)

To page 8

12

The Design of ROSSE (cont.)

Step 12• Access ROSSE Service Repository

• Compute the match degrees of relevant properties of advertised service to the service query

Step 13 • Functionally matched services have distinct

nonfunctional properties related to QoS

• SSC invoke the QoS ModelingTo page 8

13

The Design of ROSSE (cont.)

Step 14• In turn filters functionally matched services

Step 15• Via the Web user interface of ROSSE

Step 16• A list of discovered services

To page 8

14

The Design of ROSSE (cont.)

Rough Sets for Service Discovery• Mathematical technique to deal with uncertainty in

knowledge discovery

• Rough set theory

• definitely has property p

• possibly has property p

• absolutely does not have property p

{ :[ ] }

{ :[ ] 0}

A

A

P

P

X x U x X

X x U x X

,x X x

,x X x

,x U X x

15

The Design of ROSSE (cont.)

• Rough set theory for ROSSE

X

1X

2 2:X X X X

1 0X

1 0X

X 1X

2X

1 0X

1 0X

1X7

8

16

The Design of ROSSE (cont.)

Irrelevant Property Identification• Semantic relationships with the properties

• Define• Exact match: pQ=pA, or pQ is a subclass of pA

• Plug-in match: pA subsumes pQ

• Subsume match: pQ subsumes pA

• Nomatch: No subsumption between pQ and pA

• Uncertain: No subsumption between pQ and pA, and pA=NULL

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The Design of ROSSE (cont.)

Dependent Property Reduction• Indecisive property

• ROSSE deals with uncertainty of property

• Identify indecisive properties

( )

( ) {( , ) : , ( , ) ( , )}

[ ] [ ] [ ]D INDA A A A

IND IND IND IND INDA Ai A Ai Ai

P P P P

IND P x y X p P f x p f y p

Y Y Y

3

4

18

The Design of ROSSE (cont.)

Identify Identify individual individual indecisive indecisive propertiesproperties

Check all Check all possible possible combinations combinations of these of these individual individual indecisive indecisive properties properties

19

The Design of ROSSE (cont.)

Computing Similarity Degrees• The preliminary

• Fuzzy

• From a semantic relationship to a fuzzy variable

• Does not consider the semantic distances of the properties

• To increase the accuracy in assigning matching degrees• Between andAp Qp

20

The Design of ROSSE (cont.)

• 1 if exact match,

if plug in match,

if subsume match,

0 if nomatch

• Similarity degree to a service query

, 2Q AP P

( , )Q Adom P P

( , 1)

1 1

2 Q AP Pe

( , 1)

1

2 Q AP Pe

, 1Q AP P 5

1 1

( , ) max( ( , )) /DL M

Qi Aj Dj i

S Q s dom p p L

6

21

QoS Modeling (cont.)

System-Related QoS • System-Related QoS Properties

• Reliability

if

1 if

• Execution Efficiency

if

1 if

• Availability

max

max min

iT T

T T

( )reliability iq s min

max min

iE E

E E

max minE Emax minE E

( )efficiency iq s max minT Tmax minT T

9

10

( )( )

( )avail

availabilityinvoke

n sq s

N s

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QoS Modeling (cont.)

• Non-System-Related QoS Properties• Cost-Effectiveness

if

1 if

• Reputation

cos _ ( )t effectiveness iq s max

max min

iC C

C C

max minC C

max minC C

1( )

( )

k

jjreputation

RD sq s

k

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QoS Modeling (cont.)

• Overall QoS Values of Functionally Matched Services• Overall QoS value

1 2 3 4 cos _ 5( ) availability reliability efficiency t effectiveness reputationQ s w q w q w q w q w q

( )Q s

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ROSSE Case Study (cont.)

ROSS Implementation• Web system

• JAVA

• Web

• ROSS Service Repository• UDDI registry for WSDL services

• Service repository for OWL-S

• OWL-S service repository• Record service element (name and property)

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ROSSE Case Study (cont.)

Discovery of Computing Services in ROSSE• Building a Decision Table

• 1

→ The property is explicitly

• X

→ The property is not explicitly

Properties

Service

d3 b4 e4 f3 d7 f2 c4

g3

e1 b3

S1 1 1 1 1 x x x 1 1

S2 X 1 x 1 x x x 1 X

S3 X 1 x 1 x 1 1 X X

S4 X 1 x x 1 1 1 X X

S5 X 1 1 x x x 1 X X

S6 1 1 1 1 1 x x x X

S7 X 1 x x x 1 x X X

S8 1 1 1 1 x x 1 X X

S9 X 1 x 1 x 1 x 1 X

S10 X 1 x x x x x 1 X

S11 X 1 x x x 1 x x x

S12 X 1 1 1 1 x x 1 1

S13 1 1 1 1 1 x 1 x X

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ROSSE Evaluation (cont.)

Accuracy of ROSSE in Service Discovery• Increased Similarity Degrees of ROSSE

• UDDI

• OWL-S

• ROSSE

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ROSSE Evaluation (cont.)

• Measuring Precision and Recall• Group 1-Constrains

• No service had an uncertain property

• At least one property of a service was assigned an exact match

• Group 2-No constrains

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ROSSE Evaluation (cont.)

• The performance in the tests of group 1

• The performance in the tests of group 2

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ROSSE Evaluation (cont.)

• The performance of ROSSE in group 1 and group 2

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ROSSE Evaluation (cont.)

The overhead of ROSSE in matching services

Efficiency of ROSSE in accessing service records

Efficiency of ROSSE in Service Discovery

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Conclusions

ROSSE for discovery of grid services Dynamically reduce uncertain properties

when matching services• ROSSE increase the accuracy of service

discovery

• To maximize user satisfaction in service discovery

ROSSE improves the precision and recall

Thanks for your attention

See you next timeSee you next time