Download presentation
Presentation is loading. Please wait.
1
1 Service Discovery using Diane Service Descriptions Ulrich Küster and Birgitta König-Ries University Jena Germany ukuester|koenig@informatik.uni-jena.de
2
2 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Agenda Introduction to DIANE Service Descriptions (DSD) Improvements to Discovery Solution estimation step handling temporal reasoning goals dynamic product listings user preferences basic composition
3
3 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 What is DIANE and DSD? Project goal: Complete efficient automation of service discovery, matchmaking and invocation Assumption: Simple two-phase choreography n stateless estimation (negotiation) steps 1 execution step DSD language: lightweight ontology language (object oriented) special constructs to describe services Keep efficient matching in mind
4
4 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Service specific elements of DSD (1) Operational elements to capture world altering effects states (instances of state ontology: Owned, Known, Printed, Shipped, Accessible, …) Aggregational elements Moon sells more than one item, Muller transports to a variety of countries Usually describe sets of effects Normal semantic: One out of a set of effects is requested / created
5
5 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Service specific elements of DSD (2) Selecting elements to support configuration by the requestor (select one out of the offered effects) to inform requestor about produced effect variables (input / output) Valuing elements to express preferences of the requestor fuzzy sets (the higher the membership, the higher the preference) strategies (specify how to i.e. trade-off price versus shipping time, underspecified offers, …) unbiased, deterministic, precise matching
6
6 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Example: Excerpt from Muller offer description
7
7 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Matching Given fuzzy request r and configurable offer o solve the following problem: a)Compute fuzzy containment value subset Є [0, 1] of o in r (How well is the offer contained in the requested effects?) b)Where possible, configure o such as to maximize subset Implementation descends through description graphs, fills variables with optimal values, recursively computes subset for each element, combines subset values
8
8 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Agenda Introduction to DIANE Service Descriptions (DSD) Improvements to Discovery Solution estimation step handling Temporal reasoning goals dynamic product listings user preferences basic composition
9
9 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Improved Estimation Operation Handling Estimation Operation (e.g. inquire price from Muller) only executed if necessary
10
10 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Temporal Reasoning Express shipping times rule based Express requirements on pickup time frame certain time a day minimum and maximum advance notice minimal length of interval Problematic: -length of interval -rule based shipping times
11
11 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Rule based shipping time computation "Ships in 2/3 days (national/international) if collected by 5pm" Rule evaluation delegated to external service integrated via estimation operation
12
12 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Length of pickup time frame Introduced conditions combining arbitrary attributes Problematic during automatic offer configuration
13
13 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – Dynamic Product Listings Dynamic offer descriptions using dynamic sets Completed at the beginning of the matchmaking Mapping rules to lift xml listing to semantic instances (minor problem: need to determine type of instance)
14
14 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – User Preferences
15
15 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – User Preferences (cont) Fuzzy sets map extremely well to balance competing optimization goals (HDD, RAM, processor, price, …) Fuzzy sets do not map well to rules (buy the white one if it is more than 100$ cheaper than the black one) Price: ~==[0.0, 1800.0] 0.0 100$ difference 0.055555 difference in match value Color: in {white [0.9444], black [1.0]} 0.5 * entity + 0.5 * price min (entity, price, 0.5 * entity + 0,5 * price) min(entity,price,(0.5 * entity + 0.5 * price) 5 ))
16
16 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – Basic Composition 1 Automatically composes offers Ensures atomicity Handles offers at different granularity
17
17 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – Basic Composition 2 Unable to solve Goal C2 DockingStation.compatibleTo{list of GTIN} Notebook.GTIN insufficient support for lists Maybe next workshop ;-)
18
18 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Discovery Scenario II – Basic Composition 3/4
19
19 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Summary Able to model all but one goal Main improvements: multi attribute conditions arithmetic expressions Main directions of future work: implement list support in matchmaking configuration in the presence of multi attribute conditions Not in the near future: direct support for rules
20
20 Fourth International SWS-Challenge workshop Innsbruck, Austria, June 2007 Thank you for your attendance! Questions? Ulrich Küster DIANE project (services in ad hoc networks) http://hnsp.inf-bb.uni-jena.de/DIANE/
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.