Web Services Composition

1. Web Services Composition Incheon Paik, University of Aizu

2. Contents • Services :Web, Grid, Semantic Web, and Ubiquitous Services • Web/Ubiquitous Services Composition • Logical Composer and Physical Composer • Hierarchical Task Network (HTN) Planning • Distributed Constraint Satisfaction Problem (DCSP) • HTN-CSP Combined System Framework • Conclusion

3. Web Services Service: the condition or occupation of being a servant or someone who serves. the non-material equivalent of a good Work carried out for or on behalf of others Web Service: A software system designed to support interoperable Machine to Machine interaction over a network. - W3C - Web services are frequently just Web APIs that can be accessed over a network, such as the Internet, and executed on a remote system hosting the requested services.

4. Web Service • Three Main Parts • Simple Object Access Protocol (SOAP) • Web Service Description Language (WSDL) • Universal Description, Discovery, and Integration (UDDI)

5. Web Services: Basic Architecture Service Broker Registry; well-known Publish or announce (WSDL) Find or discover (UDDI) Service Provider Service Requestor Bind or invoke (SOAP) Not well-known

6. Web Service • Simple Object Access Protocol (SOAP) • SOAP Message • Envelope • Header : client authentication, transaction management • Body : include the information that a receiver should get finally • Fault element

7. Web Service • Simple Object Access Protocol (SOAP) • SOAP Message • Envelope • Header : client authentication, transaction management • actor and mustUnderstand attribute of auth element • Body : include the information that a receiver should get finally, • Information : RPC request, RPC result, Error in execution • Fault element • SOAP Encoding • How to processing data • Ex) String title = “Book”  <title xsi:type=“xsd:string>Book</title> • Encoding Style attribute • env:encodingStyle = http://schemas.xmlsoap.org/soap/encoding/ • Simple Type • Compound Type

8. Web Service • SOAP Encoding • Compound Type <ns0:addBook3> <Book_1 href=“#ID1”/> </ns0:addBook3> <book id=“ID1” xsi:type=“ns1:Book”> <title xsi:type=“xsd:string”>book1</title> <price xsi:type=“xsd:int”>29000</price> </book> deserialization by message receiver Book1 Book_1 = new Book(); Book_1.setTitle(“book1”); Book_1.setPrice(29000);

9. Web Service • Simple Object Access Protocol (SOAP) • SOAP Message Transport • Binding : How to combine with transport protocol • HTTP Binding • HTTP: Start line, Header, Body • SOAPAction : For RPC

10. Web Service • Web Service Definition Language(WSDL) • Specification of Web Service Function • Document Structure <definitions> <types> Complex types for arguments and return types </types> <message> Describe arguments and return values </message> <portType> // interface <operation> Describe remote procedures </operation> </ portType > <binding> Protocol used for invoking : SOAP(Application client), HTTP(Web Client), MIME(char & binary data) </binding> <service> <port> URL of Web Service (endpoint) </port> </service> </definitions>

11. Web Service • Universal Description, Discovery, and Integration (UDDI) • Create, Store, Search information • UDDI Data Structure • Information of White Page : Company Name, Address, Tel. No., and Description • Information of Yellow Page : According to Industry Classification(NAICS), According to Products(UNSPEC), and Area • Information of Green Page : Technical information of company, ex) end point URL, URL of WSDL document

12. Web Service: UDDI <tModel> ~ </tModel> <businessEntity> <businessService> <bindingTemplate> Reference </bindingTemplate> </businessEntity> <publisherAssertions> <publisherAssertion> Association <publisherAssertions> <publisherAssertion>

13. Standards for Web Services

14. Web Service Composition Stack

15. Web Service Composition Concept

16. Semantic Web The semantic Web, aims at machines and Web users’ cooperation to augment the existing Web by giving information a well-defined meaning. It mainly consists of machines (we say in other words, computers or agents) and information that is understood by the machines. The information contains semantically enriched knowledge and rules represented by ontologies and rule languages.

17. General Idea of Semantic Web Make current web more machine accessible(currently all the intelligence is in the user) Motivating use cases: • Search engines • Concepts, not keywords • Semantic narrowing/widening of queries • Shopbots • Semantic interchange, not screenscraping • E-commerce • Negotiation, catalogue mapping, personalisation • Web Services • Need semantic characterisations to find them • Navigation • By semantic proximity, not hardwired links © Michael N. Huhns

18. General idea of Semantic Web Do this by: • Making data and metadataavailable on the Web in formal machine-understandable form • Structure the data and metadata in ontologies © Michael N. Huhns

19. © Michael N. Huhns Which Semantic Web? • Version 1:"Semantic Web as Web of Data" (TBL) • Recipe:expose databases on the Web, use RDF, integrate • Metadata from: • expressing DB schema semantics in machine interpretable ways • Enable integration and unexpected reuse

20. © Michael N. Huhns Which Semantic Web? • Version 2:“Enrichment of the current Web” • Recipe:Annotate, classify, index • Metadata from: • automatically producing markup: named-entity recognition, concept extraction, tagging, etc. • Enable personalization, search, browse,..

21. © Michael N. Huhns Which Semantic Web? • Version 1:“Semantic Web as Web of Data” • Version 2:“Enrichment of the current Web” • Version 3:“Semantic Web as Web of Services” • Different use cases • Different techniques • Different users

22. Ubiquitous/Web Service Composition • Service composition: Process of combining different services to provide a new value-added service. • Infrastructure & Language of Web : OWL-S, BPEL, • Modeling Framework: WSMF, WSMO, METEOR-S • Automatic Composition: Logical Composition and Physical Composition

23. Services Composition • Logical Composer • Physical Composer • Logical Composer Methodologies • Physical Composer Methodologies • Composition Attributes

24. Automatic Services Composition

25. Flow of Services Composition

26. Services Composition • To create a new value-added service from existing Web services • Logical Composition: Abstract Workflow • Physical Composition: Concrete Workflow • QoS Attributes : Performance, Preferences, Service Quality • Interactivities

27. Services Composition Logical Composer • Logical composition process is usually carried out by creating a series of processes from a planner. • To develop a plan for logical composition, • Situation Calculus • HTN Planner • Finite Automata • are used.

28. Logical Composer (LC) Finite State Machine and Planner

29. Logical Composer Finite State Model and OWL-S

30. Logical Composer State Transition System and Plan

31. Logical Composer Example of State Transition System and Plan

32. Logical Composer Situation Calculus (Golog)

33. Services Composition Physical Composer • Physical composer evaluates composition attributes and produces the best candidate services combination. • To develop a plan for physical composition, • Linear Programming • Graph Theory • Constraint Satisfaction Problem • are used.

34. Physical Composer (PC) Constraint-Based Service Composition Define service composition problem as a COP by (X,D,C,f(sl))

35. Physical Composer Constraint-Based Service Composition Define service composition problem as a COP by (X,D,C,f(sl))

36. Physical Composer Constraint-Based Service Composition

37. Physical Composer Constraint-Based Service Composition

38. Physical Composer Constraint-Based Service Composition

39. Physical Composer Constraint-Based Service Composition

40. Physical Composer Constraint-Based Service Composition

41. Physical Composer CSP Solving Algorithm

42. Combining LC & PC • Solving real-life problems requires a set of appropriate services to be composed via planning, scheduled, and then executed. • Combining LC(HTN) and PC (CSP) • Hierarchical Task Network : Planning • Constraint Satisfaction Problem : Evaluation and Scheduling • HTN-CSP combined system

43. Scenario 1 • Chulsoo and Younghee’s Mother: Now she is complaining of pain and tingling in her legs Prescription for Anti-inflammatory Drug MRI Electromyography Follow-up with Physician Make appointments for the doctor’s follow-up Make appointments for the two treatments Fill the Prescription • Preferences and Constraints • For the two treatments: • - Bill and Joan would prefer two appointment times that are close together scheduled at one or two nearby places • - Otherwise, they would prefer two appointment times on different days • After two treatments, Next doctor’s follow up • An appointment time must fit the schedule of the person that will drive.

44. From Aizu to Kangnung

45. Scenario 2 By SkyLiner • Travel from Aizu-Wakamatsu City in Japan to Kangnung in Korea Aizu- Wakmatsu JR Station Koriyama Shinkansen Station Ueno Station Narita Airport By Bullet Train By Airplane By JR Train Incheon Airport Hotel in Kangnung By Bus • Preferences and Constraints • Depart from Aizu-Wakmatsu after 14:00 • Arrive at Narita Airport before 15:00 on Oct. 15. • Hotel: Normal Class OK, Airplane: Business Class

46. Hierarchical Task Network （HTN) Planning • To produce a sequence of actions by task decomposition from large tasks • Similar to classical AI planning • Can produce plans to reach final goal, but it is not suitable for scheduling

47. HTN Planning • An HTN planner consults the description of • Planning domain • Prescription for how to decompose a task into subtasks. • Planning problem • Definition of initial states and goal tasks. • We chose SHOP2 as our basic planner.

48. Planning Domain Example : Method (transport ?p) task: (at ?p ?x) (destination ?p ?y) (available-truck ?t) preconditions: : compound task : primitive task subtasks: : state (dispatch ?t ?x) (!load ?t ?p) (!move ?t ?x ?y) (return ?t ?y) (dispatch ?t ?x) (return ?t ?y) task: task: subtasks: subtasks: (!reserve ?t) (!move ?t home ?x) (!move ?t ?x home) (!free ?t)

49. Constraint Satisfaction Problem (CSP) • CSP is a triple <X, D, C> where: • X is a set of variables {X1, X2, …, Xn}. • D is a set of (variable) domains{D1, D2, …, Dn}.Di is a set of possible values for Xi. • C is a set of constraints {C1, C2, …, Cm} on assignments to X.

50. CSP • The solution to a CSP is a complete assignment of a value in Di to each variable Xi that satisfies all the const-raints Cj. • General complex problems can be represented as simple assignment problems.