Scalable automated service composition using a compact directory digest

Authors:
Walter Binder;Ion Constantinescu;Boi Faltings
Affiliations:
Artificial Intelligence Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;Artificial Intelligence Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;Artificial Intelligence Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Venue:
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Year:
2006

Citing 8
Cited 2

Zero-suppressed BDDs for set manipulation in combinatorial problems

DAC '93 Proceedings of the 30th international Design Automation Conference
Specification matching of software components

ACM Transactions on Software Engineering and Methodology (TOSEM)
On the properties of combination set operations

Information Processing Letters
Semantic Matching of Web Services Capabilities

ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
A software framework for matchmaking based on semantic web technology

WWW '03 Proceedings of the 12th international conference on World Wide Web
Introduction: Service-oriented computing

Communications of the ACM - Service-oriented computing
Large Scale, Type-Compatible Service Composition

ICWS '04 Proceedings of the IEEE International Conference on Web Services
Flexible and Efficient Matchmaking and Ranking in Service Directories

ICWS '05 Proceedings of the IEEE International Conference on Web Services

Efficient Service Composition Using Zero-Suppressed Reduced Ordered Binary Decision Diagrams

WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Modeling Service Level Agreements with Binary Decision Diagrams

ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The composition of services that are indexed in a large-scale service directory often involves many complex queries issued by the service composition algorithm to the directory. These queries may cause considerable processing effort within the directory, thus limiting scalability. In this paper we present a novel approach to increase scalability: The directory offers a compact digest that service composition clients download to solve the hard part of a composition problem locally. In this paper we compare two different digest representations, a sparse matrix and a Zero-Suppressed Reduced Ordered Binary Decision Diagram (ZDD). Our evaluation confirms that both representations are compact and shows that the ZDD enables more efficient service composition.