1. Context-aware Semantic Web Service Composition
Yasser Ganji Saffar
Semantic Web Laboratory
Computer Engineering Department
Sharif University of Technology

2. Outline What is the Problem? Related Works Contributions
Semantic Web Services
Service Discovery
Service Composition
Context-awareness
Related Works
Contributions
Proposed Architecture for a Context-aware Service Broker
Proposed Methods for Service Matchmaking

3. What is the Problem?

4. Web Services Web-accessible Self-describing Platform independent
Definition of World Wide Web Consortium (W3C):
“a software system designed to support interoperable machine-to-machine interaction over a network. It has an interface described in a machine-processable format (specifically WSDL). Other systems interact with the Web service in a manner prescribed by its description using SOAP messages, typically conveyed using HTTP with an XML serialization in conjunction with other Web related standards”

5. Service Oriented Architecture
WSDL
Service
Provider
Publish
Bind
Only Syntax,
Agents can not understand meanings
SOAP
SOAP
Service
Broker
Service
User
Find
SOAP
UDDI
SOAP – Simple Object Access Protocol / SOA Protocol
UDDI – Universal, Description, Discovery, and Integration
WSDL – Web Services Description Language

6. Semantic Web Services Semantic Web Web Services Semantic Web Services
Sharing Information on the Web
Computer-interpretable
Web Services
Sharing Programs on the Web
Semantic Web Services
Web Services + Semantic Web
Using ontologies to describe web services

7. Ontologies for Semantic Web Services
Use ontologies to describe Web Services
DAML-S (since 2001)
OWL-S (since 2003)
Based on OWL-DL
WSMO (since 2004)
SWSO (since 2005)
Based on FLOWS (First-order Logic Ontology for Web Services)

8. Issues in Semantic Web Services
Discovery (Matchmaking): Locate different services suitable for a given task
Selection: Choose the most appropriate services among the available ones
Composition: Combine services to achieve a goal
Automatic Service Composition might enable programmer to become specifying what to do and not anymore how to do it!
Execution: Invoke services following programmatic conventions
Monitoring: Control the execution process

9. A trivial Example

10. An Obvious Solution

11. Composition: An Example
BookName
UserName
Password
Inputs
CardType
CardName
CardExpiryDate
Login
HotelReservation
BookLookUp
ShipItem
Available Services
PutInCart
CarRental
FlightBooking
CreditCardCheck
GetInfo
Goal
BookShipped

12. Composition: An Example
UserName
Password
BookName
Login
UserType
BookLookUp
CardType
CardName
CardExpiryDate
GetInfo
ProfileExists
BookInStock
ISBN
CreditCardCheck
PutInCart
Approved
InCart
ShipItem
BookShipped

13. Related Works

14. Composition Approaches
Manual
Design-time composition
BPEL4WS (Business Process Execution Language for Web Services)
Workflow-based
Only works when the web service environment doesn’t, or only rarely changes
Automatic
AI Planning & Workflow-based

15. AI Planning Actions Initial State Goal State move(a,table) move(c,a)
move(b,c) A C B C A
Actions
Initial State
Goal State

16. AI Planning for Composition (1)
Planning Domain Definition Language (PDDL)
PDDL is a standardized input for state-of-the-art planners
PDDL and OWL-S representations are very similar.
OWLS2PDDL is available.
Different planners have different capabilities and by using this method we can use the best suited planner for each particular composition task.

17. AI Planning for Composition (2)
Rule-based Planning
Medjahed (2003)
Composability rules are used to determine whether two services are composable.
Message composability (output of one service is compatible with input of another).
Operation semantic composability (defines the compatibility of domains and categories and purposes of two services).
Qualitative composability (defines the requester’s preferences for quality of operations).
Composition soundness (determines whether a composition of services is reasonable). Composition templates that define dependencies between services are used.

18. AI Planning for Composition (3)
Rule-based Planning
SWORD
It uses Entity-Relation model to specify web services.
A service is modeled by its preconditions and postconditions and is represented in the form of a Horn rule that denotes postconditions are achieved if the preconditions are true.
User specifies the initial and final states.
A rule-based Expert System is used for plan generation.

19. AI Planning for Composition (4)
Situation Calculus
Activities users perform on the web can be viewed as customizations of reusable, high-level generic procedures.
Runtime customization of these generic procedures.
Situation calculus is a logic language for reasoning about action and change.
GOLOG is a logic programming language built on top of the situation calculus.
McIIrith et. al. (2001,2002), adapt and extend the GOLOG language for automatic construction of Web services.
Web Service = Action
Primitive
World-altering: change the state of the world
Information-gathering: change the state of the knowledge
Complex
Compositions of individual actions
Main Problem: GOLOG programs are difficult to create

20. AI Planning for Composition (5)
Hierarchical Task Network Planners
Composite task decomposition in HTN planning is very similar to Composite process decomposition in OWL-S.

21. AI Planning for Composition (6)
Hierarchical Task Network Planners
User must give an abstract task list.
SHOP2
More efficient than other planning languages such as GOLOG.
OWL-S can be translated to SHOP2.
JSHOP2 is open source.
Main Problems:
Lack of parallel execution, a feature frequently needed for efficient web service usage.
Processes either must have outputs or effects, but not both.
It enables information gathering during planning.
it is not possible to directly express the semantics of OWL DL using SHOP2 axioms.
A task can not be both primitive and nonprimitive.

22. AI Planning for Composition (7)
OWLS-Xplan
An open source composition tool released Dec. 2005
Based on Xplan planner

23. Template-based Composition
Sirin et al., Nov. 2005
A workflow template describes the outline of activities that need to be performed to solve a problem.
Some of the activities are defined as abstract activities.
Recursive decomposition of templates.
Generic templates can be customized for a specific instance of the problem based on the users’ preferences:
Use only certified services
Try to find non-fee services
Do not buy the plane ticket if we can not reserve the hotel room.

24. Semi-automatic Composition
Current automatic composition approaches can not scale with the amount of knowledge on Semantic Web.
Sirin et al. (2004)
Automatic planner and human being can work together to generate the composite service.
The user starts the composition process by selecting one of the services registered to the engine. A query is sent to the KB to retrieve the information about the inputs of the service, and for each of the inputs, a new query is run to get the list of the possible services that can supply the appropriate data for this input.

25. Context-awareness What is context? (in our work) For example,
context encompasses all information about the client of a web service that may be utilized by the web service for adjusting the execution and output to provide the client with a customized and personalized behavior.
For example,
Profile
General-info:
Name, , credit-card number,...
Preferences:
Currency, Language, ...
Location
CC/PP (Composite Capabilities / Preferences Profile)
Bandwidth

26. Context-based Adaptation
What is the Screen size?
Is it JavaScript Enabled?

27. Contributions

28. A Context-aware Service Broker
Service Specification + Inputs
Profile Request
Inputs request
Adapted outputs
Ask for inputs
Adapted inputs
Generated outputs
Request + Context
Adapted Request
Matchmaking Request
Composition Request
Registered Services Info
Selected Service

29. Matchmaking

30. Proposed method for Matchmaking
Fuzzy Matchmaking:
Instead of using strict levels of matching, let’s use a value between 0 and 1.
We can use the concept of Semantic Distance.
1/2
CCP
1/4
1/4 C1
1/8 C2
1/16

31. Evaluation

32. Input/Output Matching is not sufficient
Add and Multiply services both have similar signatures:
We need to find what services actually do.
Integer
Add
Integer
Integer
Integer
Multiply
Integer
Integer

33. Publications
Y. Ganji Saffar, H. Abolhassani, R. Jalili, “An Architecture for a Context-aware Service Broker for Ubiquitous Computing Environments”, to appear, The 4th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA-06), UAE, March 2006
Y. Ganji Saffar, H. Abolhassani, “Context-aware Semantic Web Service Brokering”, to appear, 11th Computer Society of Iran Computer Conference, Iran, 2006

34. Future Plan Design & Implementation of a Service Composer 3 months
Context modeling and implementation of a context manager
1 month
Design & Implementation of an Adapter
Adding Context-awareness capability to Matchmaker and Composer components
2 months
Finalizing the thesis

35. Questions ?

36. Main References
M. Klusch, B. Fries, and M. Khalid, “OWLS-MX: Hybrid Semantic Web Service Retrieval”, In Proceedings of 1st International AAAI Fall Symposium on Agents and the Semantic Web, Arlington VA, USA, 2005.
M. Klusch, A. Gerber, and M. Schmidt, “Semantic Web Service Composition Planning with OWLS-Xplan”, AAAI Fall Symposium Series, Arlington, Virginia, USA, Nov
B. Medjahed, A. Bouguettaya, and A. K. Elmagarmid, “Composing Web services on the Semantic Web”, The VLDB Journal, vol. 12, no. 4, Nov
S. McIlraith and T. C. Son, “Adapting Golog for composition of Semantic Web services”, In Proceedings of the 8th International Conference on Knowledge Representation and Reasoning (KR2002), Toulouse, France, April 2002.
S. R. Ponnekanti and A. Fox, “SWORD: A developer toolkit for Web service composition”, In Proceedings of the 11th World Wide Web Conference, Honolulu, HI, USA, 2002.
D. Wu et al., “Automatic Web services composition using SHOP2”, In Proceedings of the Workshop on Planning for Web Services, Trento, Italy, June 2003.
E. Sisrin, B. Parsia, and J. Hendler, “Filtering and selecting semantic web services with interactive composition techniques”, IEEE Intelligent Systems, vol. 19, no. 4, pp , 2004
M. Paolucci et al., “Semantic matching of web services capabilities”, In Proceedings of the 1st International Semantic Web Conference (ISWC), Springer Verlag, 2002, pp
S. Ben Mokhtar et al., “Context-aware Service Composition in Pervasive Computing Environments”, In Proceedings of the 2nd International Workshop on Rapid Integration of Software Engineering techniques (RISE’05), Heraklion Crete, Greece, Sep

37. Discovery Approaches ? Based on service inputs and outputs
Pure logic-based
Exact
Subsume
Plug-in
Fail
Logic-based methods + Information retrieval methods
Using implicit knowledge which is available in service descriptions
BookName ?
ISBN

38. AI Planning for Composition (2)
Situation Calculus
Every situation is defined by a world history, that is a sequence of actions.
The constant s0 describes the initial situation, that is a situation where no actions have occurred yet.
A state do(putDown(A), do(walk(L), do(pickUp(A), s0))) describes the situation created by the execution of a sequence [pickUp(A),walk(L), putDown(A)].
A composite service is a set of atomic services which connected by procedural programming language constructs (like if-then-else, while, for and so forth).