1. 1 Michael Klein, Universität Karlsruhe, Germany Integrating Preferences into Service Requests to Automate Service Usage First AKT Workshop on Semantic Web Services Milton Keynes, UK, December 8, 2004 Michael Klein Institute for Program Structures and Data Organization Universität Karlsruhe, Germany DIANE Project http://www.ipd.uni-karlsruhe.de/DIANE/en Birgitta König-Ries Institute of Computer Science Friedrich-Schiller-Universität Jena, Germany

2. 2 Michael Klein, Universität Karlsruhe, Germany Dynamic Service Binding Application Business Process Service A Service B Service C Service D Agile Networks  change inefficient or unavailable service providers on runtime  Enhance efficiency and robustness

3. 3 Michael Klein, Universität Karlsruhe, Germany State of the Art  How is this typically achieved? Application Service B Description of the desired service Description of the offered service 1.Attach service description to application and services 2.In case of a call, a matcher calculates similarity between request and all offers 3.Best offer is chosen and invoked Matcher [0..1] invoke

4. 4 Michael Klein, Universität Karlsruhe, Germany Difficulties EASY:  If descriptions are exactly equal: Matcher returns 1.0  If descriptions are obviously different: Matcher returns 0.0 DIFFICULT:  In the common intermediate situations:  The offer differs somewhat from the request  What value in (0,1) is appropriate?

5. 5 Michael Klein, Universität Karlsruhe, Germany Example for a Service Request :Service :Profile:Booked :CinemaTicket :SeatInShow 2004-07-10 spiderman2:Movie presents effect entity validFor visible date cinema Service Request: I want a Service which books me a seat for Spider Man 2 time 20:00 hortonPlaza:Cinema price <= 8.00

6. 6 Michael Klein, Universität Karlsruhe, Germany Example for a Service Offer :Service :Profile:Booked :CinemaTicket :SeatInShow 2004-07-10 spiderman2:Movie presents effect entity validFor visible date cinema cinerama6:Cinema Service Offer: I can book you a ticket for Spider Man 2, this saturday at 8:15 pm in the Cinerama 6. time 20:15

7. 7 Michael Klein, Universität Karlsruhe, Germany Is it a Match? The requestor wanted :SeatInShow time 20:00 …but the offer can only book a ticket for 20:15. This is not ok, or is it? So assign 0.9? :SeatInShow cinema hortonPlaza:Cinema The requestor wanted …but the offer can only book a ticket in the Cinerama 6. Is this ok? Say yes, because it‘s in the same city  Assign 0.8? What is more important for the offerer: A good price, a good time, a near cinema?  Simply take the average, or the minimum, or…? :CinemaTicket price <= 8.00 The requestor wanted …but this information is missing in the offer. Return 0.0 and skip the service? Or just assign 0.5? Or 1.0?

8. 8 Michael Klein, Universität Karlsruhe, Germany Main Problem Matcher does not know the preference/tolerance of the requestor. Main Problem The Matcher  has to use general deviation heuristics  or is very conservative and only allows exact matchs  biased matching  often provides many or no matching offers  Requestor has to choose manually or blindly rely on it.  Cannot or is not used for automatic service binding.

9. 9 Michael Klein, Universität Karlsruhe, Germany Our Approach  Tell the matcher exactly what the preferences are Generic Matcher requestoffers - generic - based on heuristics  biased Personal Matcher request creates offers - personal - only based on the specified preferences  unbiased FROMTO

10. 10 Michael Klein, Universität Karlsruhe, Germany Preference-Containing Requests  Request != single instance describing the perfect service  But: Set of suitable services  degrees of membership from (0,1] determines preference for this service

11. 11 Michael Klein, Universität Karlsruhe, Germany Introduction of Object Sets spiderman2 Movie contains all existing movies represents one single movie Movie represents a set of movies Membership conditions are defined in a structured manner

12. 12 Michael Klein, Universität Karlsruhe, Germany Cinema Request (Revisited) Service ProfileBooked CinemaTicket SeatInShowMovie presents effect entity validFor visible date cinema time price Double ~<= 8.00 Date == 2004-07-10 Time ~< 20:00 <= 21:00 Cinema near(hortonPlaza) min(date, time^2, cinema, visible) ==spiderman2

13. 13 Michael Klein, Universität Karlsruhe, Germany Unbiased Matching  Now: Unbiased Matcher  Matching = Calculating the membership value of the request set  Matcher exactly takes the preferences of the requestor into account  Personal Matcher  Automatically gained matching result is accepted.

14. 14 Michael Klein, Universität Karlsruhe, Germany Summary  Main Goal of Service Oriented Computing: Dynamic Service Binding  Up to now: Generic Matcher tests similarity between the offer instance and the request as perfect service instance  Problem: Unknown preferences of the requestor in case of deviations  Matcher uses heuristics and is biased  Result is not accepted and must be postprocessed manually  Our Thesis: Tell the matcher exactly what the preferences are  Possible technique: Fuzzy object sets  Matching is test on set membership  unbiased  Result is accepted without further manual processing

15. 15 Michael Klein, Universität Karlsruhe, Germany Current & Further Work  Service descriptions can contain variables. How to match them? Can we derive binding from request?  Currently finishing the implementing the matcher.  Difficult for the requestor to adjust the conditions and strategies  Guide user through process  How to evaluate the approach? Other approaches?

16. 16 Michael Klein, Universität Karlsruhe, Germany Thank you for your attention! DIANE Project http://www.ipd.uni-karlsruhe.de/DIANE/en