Composing semantic Web services under constraints E.Karakoc, P.Senkul Journal: Expert Systems with Applications 36 (2009)

Outline Introduction Motivating example Related work Composite Web Service framework (CWSF) Modeling the composition Plan generation Experiments Conclusion

I. Introduction A Composite Web service A process consisting of collaborating heterogeneous Web service. Dynamic Heterogeneous Distributive

I. Introduction (cont.) The reason of complexity Search A number of services available over the Web Dynamic up-to-date information Select Achieve the composition goal and Qos requirement Constraint defines how the services will be selected.

I. Introduction (cont.) The author ’ s work A constraint programming based approach for Web service composition problem. The aim: to generate solutions to find executable schedules by solving constraint.

I. Introduction (cont.) The properties: How to model Qos requirements on the composition Web service A unified framework (CWSF) Transformation  a constraints satisfaction problem Constraint solver  composition plan Semantic matching

II. Motivating example Travel Planner system Flight booking Travel booking Accommodation booking Car rental Free activity planning

II. Motivating example (cont.) User constraints: For example: max budget≤2500$ The goal of CWSF : to organize the travel by selecting the concrete services for abstract service templates based on the user constraints.

III. Related work The previous work Composition is pre-defined The service discovery without considering constraint on the composition service. Constraint optimizer: linear programming solver The difference: convert both composite flow model and users constraints into constraint satisfaction problem

IV. Composite Web Service framework (CWSF)

IV. CWSF (Cont.) CWSF designer model the flow structure of the composite service and constraints on the GUI Semantic domain model repository and semantic inference engine to keep the activities and their relationships in a given domain Service matching/mapping engine and service registry Use it semantic wrapper to communicate with UDDI Registry To obtain the list of candidate Web services To reduce the candidates by checking semantic matching

IV. CWSF (Cont.) Service query engine Gather information such as the cost, price etc. of the services, form candidate Web services Plan generator Constraint translator Solution analyzer

V. Modeling the composition Modeling the composition flow Composite Web service Language (CWSL) GUI : a nested block structure Basic blocks structures for CWSL Start Block End Block Sequential Block And Block Or Block Xor Block Iteration Block Decision Block Web Service Template Block Transition

V. Modeling the composition (cont.) Modeling the constraints Temporal and causality constraints Service selection constraints Logical constraints If/Then constraints Control constraints Modeling abstract services

VI. Plan generation to create the composition plans that satisfy all constraint and flow structure requirements. Constraint engine The constraint solver Choca, A Java library, which conform to GPL, for constraint satisfaction problems (CSP)

VI. Plan generation (cont.) Constraint translator Translating the flow model Sequential block OR block XOR block Iteration and decision blocks Translating the constraints

VI. Plan generation (cont.) Solution analyzer Converting final plan into executable service  BPEL4WS

VII. Experiments The effect of increasing number of candidate services The effect of flow model complexity (increasing number of blocks) The effect of number of variables/constraints

VIII. Conclusion The approach Motivation Method Result