Semantic Variability Modeling for Multi-staged Service Composition

Transcription

1 Semantic Variability Modeling for Multi-staged Service Composition Bardia Mohabbati 1, Nima Kaviani 2, Dragan Gašević 3 1 Simon Fraser University, 2 University of British Columbia, 3 Athabasca University, Canada [email protected], [email protected], [email protected] SPLC SOAPL 2009 Software Engineering Institute Carnegie Mellon SOAPL 2009 Bardia Mohabbati, 25 August 2009

2 Outline Objectives and Introduction Motivating Scenario Overview Analysis and Design Feature Model and Variability Modeling Service Requirements Specification Software Service Products Configuration Service Discovery and Specialization Semantic Variability Modeling Feature Model Ontology Feature Model Annotation Feature Model Specialization Conclusion 2

3 Objectives Adaptive development of software-intensive systems for mobile and ubiquitous Computing Pervasive/Ubiquitous computing (ubicomp) is about providing services and computing capabilities in heterogeneous environments Heterogeneous computing device Resource constraints of deployment platform Utmost functionality and satisfying non-functionality requirements (NFRs) in final product Service-Oriented Software Development and SPL 3

4 Objectives We exclusively focus variability coming from the different delivery platform of service oriented architecture Workflow Variability Business Process Layer Business Business Business Business... Process Process Process Process... Alternative and Optional Unit Service Different Web services for a unit services according to NFR rather than FR Matching Unit Service Interface and Web services Interface published in UDDI Changing part of functionality of Unit Service by adapting service component Composition Variability Interface Variability Logic Variability Unit Service Layer Unit Unit Unit Unit... Service Service Service Service... Service Interface Layer Service Service Service Service... Interface... Interface Interface Interface Service Component Layer... Component Component Component Component... S. Ho Chang et al 4

5 Motivating Scenario Airport Large Screen Display Ubiquitous Information Service Service Provider Remote Service (Web services) Mobile Devices 5

6 Overview Analysis Design Domain Analysis Product Family Feature Extraction Representing Variability by Feature Modeling Feature Model Ontology Feature Model Annotation Service Oriented Product Configuration Feature Model Specialization Configuration Validation Annotated Feature Model Software Service Product Specialization Soft Constraint Hard Constraint Device Ontology Instantiation User s Requests and Preferences Device Specification Request Specification Service Adaptation 6

7 Feature Model & Variability Modeling Functional Requirements Core Services in the system Carry the objectives of the system Non-functional Requirements Replaceable or alterable services Quality of Service (QoS) requirements Security requirements 7

8 Feature Model Ontology (FMO) Semantic Feature Model Ontology is defined as a formal specification of a conceptualization and utilizes the representation of knowledge contained in feature models. Semantic representation of features : Relations and dependencies feature constrains Transformation : o Using the Web Ontology Language (OWL) o Constructing mutual disjoint classes F1 F2 F3 [FM Mapping] F i FM i Rule hasf i ObjectProperty FM i Rule hasf i. F i F i F j, for i 1, j n i j Fn Feature Model Feature Model Ontology 8

9 Feature Model Annotation Feature Model Ontology enables us to take advantages of ontology annotation capabilities in order to enrich the definition of domain assets with the constraints concerning the non-functional requirements of a domain F1 F2 F3 [FM Mapping] ` Fn [FM Annotation] Feature Model Feature Model Ontology (FMO) Device Ontology(DCO) AN ObjectProperty AN FM m, domain(fm m ) AN.DC n, range (DC n ) hasbluetooth_an ObjectProperty hasbluetooth_an Bluetooth, domain(bluetoothrule) has Bluetooth_AN.BluetoothDevice, 9

10 Software Service Products Configuration Device Ontology model reflect device capability (NFRs) NFRs as Integrity Constraints (IC)- which include and exclude the selection of services in annotated feature model Feature Model Specialization : Stage refinement process which constitute staged configuration Specialization: The features don t satisfy the NFRs of target deployment platform are discarded and pruning feature model Ontology-based reasoning : consistency checking and verification o If instances of NFRs ontology are consistent with respect to the annotation properties defined in feature model 10

11 Software Service Products Configuration Design Time 1. Creating the feature model 2. Incorporating NFRs into designing the feature model 3. Binding Services to the NFR ontology Run Time 4. Platform Deployment Capability analysis 5. Feature selection 6. Service composition 7. Validation and Deployment 11

12 Software Service Products Configuration Feature Model Specialization FMO : Feature Model Ontology DCO: Device Capability Ontology K = (O, T, A, R) T : set of concept axioms (TBox) A : set of assertional axioms (Abox) R : set of rules written as inclusion axioms DEFINITION 1 Let d DCO be an instance of a device which has n capabilities. Each capability for device d is an instance (i k ) of a concept (C k ) from DCO such that A C k (i k ) (1 k n). S dc = {C 1,..,C n }, represents the set of all concepts C k from DCO that d supports. DEFINITION 2 Let S AF AN i CF i AN i.c k where C k DCO. FMO be a set consisting of concepts CF i such that CF i. 12

13 Software Service Products Configuration Feature Model Specialization AN j ObjectProperty SFA= n i 1 CF i for each C k S dc for each CF i S AF if ( AN j.c j AN j CF i and C j DCO) if (C j S dc ) if (A CFi(i i ) ) SFA SFA - {CF i (i i )} else SFA SFA - {CFi (i i )} return (SFA) AN j DCO 13

14 Feature Model Specialization Model Verification During the process of the configuration validation, model constraints are checked against the derived configuration to provide proper assurance in terms of correct exclusion and inclusion of optional and mandatory features. OWL-DL reasoning engines: To support automated class subsumption, consistency reasoning and detection of possible inconsistencies in the specialized feature. Consistency and conflicts detection : Formulate and define a list of Semantic Web Rule Language (SWRL ) rules to represent all invalid states 14

15 Service Discovery and Specialization The result of consistency checking in the previous step can be two folded : Inconsistent ontology Design Stage - family composition refinement Consistent ontology Service Specialization based on soft constraints Deployment of the service-oriented system: Web Service Modeling Ontology framework (WSMO) Transformation feature model to WSMO service (with ATL transformation language) Web service Execution Environment (WSMX) (the reference implementation for WSMO) Analysis Domain Analysis Product Family Feature Extraction Representing Variability by Feature Modeling Design Feature Model Ontology Feature Model Annotation Service Oriented Product Configuration Feature Model Specialization Configuration Validation Annotated Feature Model Software Service Product Specialization Soft Constraint Hard Constraint Device Ontology Instantiation User s Requests and Preferences Device Specification Service Adaptation Request Specification 15

16 Conclusion Ontologies as an underlying formalism for representation of feature models to enrich Feature Model with semantics Ontology-based approach for feature model annotation with NFRs ontologies Inference and Ontological Reasoning Over Feature Model validating (non-) functional requirements Semi-automatic Product configuration Product consistency check 16

17 Thank you 17