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RGPS: Metamodel Framework for On-Demand Model Selection

RGPS: Metamodel Framework for On-Demand Model Selection He Keqing, Wang Jian, He Yangfan, Wang Chong State Key Lab of Software Engineering, Wuhan University, China 2008/5/21. A New Working Item for ISO/IEC JTC1 SC32.

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RGPS: Metamodel Framework for On-Demand Model Selection

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  1. RGPS: Metamodel Framework for On-Demand Model Selection He Keqing, Wang Jian, He Yangfan, Wang Chong State Key Lab of Software Engineering, Wuhan University, China 2008/5/21 A New Working Item for ISO/IEC JTC1 SC32 “Metadata DownUnder”:11th Open Forum on Metadata Registries Sydney, NSW Australia Sharing and advancing knowledge and experience about standards, technologies and implementations. 

  2. Content • Background • Overview of RGPS • Summary

  3. Content • Background • Why We Need On-Demand Model Selection? • Hints From MC • Overview of RGPS • Summary

  4. Options & Selection • In our daily life, when faced with many options, we need to know how to make a wise selection. • Selections are also important when there are a lot of options for data, model, …

  5. IT Evolution • Objectives: • Provide On-demand Services for End-Users • Provide On-demand Production for System Engineers

  6. From the perspective of SaaS • Software as a Service (SaaS) • A typical customer-centric application • A model of software delivery where software providers provide daily maintenance and technical supports for customers • What customers need is the online service provided by software, instead of software itself. • Customers care how to select suitable services. Accordingly,software providers should provide on-demand services to satisfy customers. • Scale changes everything! • System of systems • The size and complexity of systems are increasing continuously, which will increase difficulties and bring challenges to on-demand service selection. On-demand service selection should be effectively supported !

  7. Service Selection & Model Selection • Service selection  resorts to model selections • Services can be characterized by various models. • Service selection can be decomposed into several model selection processes. • Service selection mechanism helps to improve model selection process • Service model is a typical and representative kind of complex models. • The most parts of service selection mechanisms also work in model selection process. • Without loss of generality, we focus on service-oriented model selection instead of model selection. Service-oriented on-demand model selection should be effectively supported !

  8. From the perspective of MFI Research on On-demand Model Selection in MFI is still insufficient ! “choice of the model instance by a user purpose” From: Masaharu Obayashi, ISO/IEC SC32 19763(MFI) Part2, 2006

  9. Related Work • SOA (Service Oriented Architecture) • A way to implement SaaS • Promote interoperation between services • Do little for on-demand model selection • Intel DSD (Dynamic Service Discovery) • Provides a dynamic service discovery mechanism based on UDDI • Can be applied only when customers know exactly the parameters for expected service. Otherwise, DSD can hardly work because it doesn't provide a mechanism for modeling customers' real intention.

  10. Content • Background • Why We Need On-Demand Model Selection? • Hints From MC • Overview of RGPS • Summary

  11. What is Mass Customization (MC) • Mass Customization provides solutions for on-demand product supply • It has been successfully applied in manufacturing industry. • It embodies the key elements for effective on-demand model selection！ • Mass Customization • Mass Production + Customization Production • Point：Customization and personalization of products and services for individual customers at a low price and in a short time • Strategies in MC can also satisfy the need of on-demand model selection. • first conceived by Stan Davis in Future Perfect, then further developed by Joseph Pine II in his book Mass Customization - The New Frontier in Business Competition

  12. Product &Process Change Matrix in MC Virtual Enterprise Flow Mass Customization Innovation Dynamic Product Change Mass Production Axis Continual Improvement Static Mass Production Mass Customization Axis Static Dynamic Process Change From: B. Joseph Pine ll, Mass Customization: The New Frontier in Business Competition. 1993,USA

  13. Compare Change Matrix in MC with SCIS Mass Production Axis Model Sign Model Concept Mass Customization Axis Domain Mass Customization Personalized Innovation End User System Model Production Improvementof Service System Engineer Model Selection Model Instance Virtual Service Flow (Customer centric and Domain oriented) SCIS : Model Sign - Model Concept - Model Instance - Model Selection

  14. Applying Basic Strategies of MC into On-Demand Model Selection Model Selection • Quick Response • Modularized Components • Customization at Delivery Position MC Effective Model Mapping & Transformation Service based Resource Aggregation Modeling Customers’ Current Context and Making Online Service Selection RGPS helps to apply these strategies in On-Demand model selection!

  15. Content • Background • Overview of RGPS • Summary

  16. Why RGPS? • Target -- modeling customers’ real intention and composing candidate components to satisfy customers. • Considering the characteristics of customers’ intention and implementation form in network • Customers’ intention is proposed from the perspective of the roles they play, and the roles are always tangled. • Customers’ goals are aptly variable and diverse. • The business processes to fulfill the goals are usually complex. • Services are the representative form of software systems in network. • Modeling customers’ real intention from four aspects: Role, Goal, Process, and Service. • Customers’ intention can be expressed from different level and different granularity • RGPS: From disorder to order -- To help users select appropriate service models

  17. Relationships between the four layers in RGPS • Relationships between Role and Goal • Roles take charge of corresponding role goals • An actor prefers his personal goal • Relationships between Goal and Process • Processes achieve functional goals • Processes contribute to the fulfillment of nonfunctional goals • Relationships between Process and Service • Services realize processes R G P S

  18. consistsOf plays Actor Role Organization Semantic Annotation Dynamic Context Profile R prefers takesCharge Personal Goal Role Goal Entity Ontology Goal Contextual Expectation Contextual Property Contextual Depend Object Process hasObject Nonfunctional Goal Functional Goal Atomic Process Composite Process Operation Ontology G P contributes achieves Input hasInput Context Ontology hasOutput Service Output Atomic Service Composite Service Operation hasOperation realizes Message hasMessage Semantic Annotation S Applying RPGS for Domain Modeling Functional Goal: Sort Order Domain Ontologies Users’ intention can be described with RGPS!

  19. Domain Ontology RGPS Metamodel Upper Model Lower Model Domain R,G,P,S Model Model Sign Model Concept Service 2 Service 5 Service 1 Service 3 Service 4 Model Selection Model Instance RGPS-based Model Selection User-friendly Languages Annotation End User Mapping & Transformation Evaluating Model Selection Personalized model Provision System Engineer Resource binding Standards are needed! Need to be strengthened for On-Demand model selection

  20. Recommended Standards to Support RGPS-based Model Selection RGPS framework RGPS Metamodel Metamodel for Evaluating Model Selection Metamodel for Personalized Model Provision Metamodel for RGPS Based Model Annotation Metamodel for RGPS Based Model Mapping and Transformation

  21. Domain Model Registration based on MFI-3 Process Process Process Process Process DomainModel Registration based on MFI-5 Applying MFI to Register RGPS-based Domain Model Description Language R Role / User OWL Goal G Subgoal OWL Subgoal Subgoal Subgoal Subgoal Subgoal P OWL-S+ OWL-S+ Service Service Service Service S

  22. Examples of RGPS-based On-demand Model Selection Developing a reservation system Role Model Reserving an air ticket between two cities prefers takesCharge Case1 Goal Model Choosing a reservation service with the least cost achieves contributes Decomposition Case2 Process Model realizes Service Model Case3 Resource Binding Service Mass Customization Service2 Service4 Service5 Service1 Service3 • RGPS paves the way for realizing On-Demand Model Selection Strategies! • Effective Model Mapping & Transformation • Service based Resource Aggregation • Modeling Customers’ Current Context and Making Online Service Selection

  23. Content • Background • Overview of RGPS • Summary

  24. Research Foundation • Projects supported • “Requirements Engineering - the Basic Research of Software Engineering for Complex System”, National Basic Research Program of China (No. 2007CB310801 ) • “Research on Requirements Elicitation and Evolution Modeling of Networked Software”, National Basic Research Program of China (No. 2006CB708302 ) • “Semantic Interoperability Application and Integration Mechanism of Complex Information Resource”, National High Technology Research and Development Program of China (No. 2006AA04Z156) • Research papers • Jian Wang, Keqing He, Ping Gong, Chong Wang, Rong Peng, Bing Li, "RGPS: A Unified Requirements Meta-Modeling Frame for Networked Software", In Proceedings of IWAAPF'08 at ICSE'08 Workshop , Leipzig, Germany, May 2008. • Keqing He, Peng Liang, Bing Li, Rong Peng, and Jing Liu, “Meta-modeling of Requirement for Networked Software - An Open Hierarchical & Cooperative Unified Requirement Framework URF”, Dynamics of Continuous Discrete and Impulsive Systems - Series B, Special issue on Software Engineering and Complex Networks, 2007, pp.293-298. • Jian Wang, Keqing He, Bing Li, Wei Liu, Rong Peng, “Meta-models of Domain Modeling Framework for Networked Software”. In: Proceedings of The Sixth International Conference on Grid and Cooperative Computing. Urumchi, China, July 2007, pp. 878-885. • Keqing He, Peng Liang, Rong Peng, Bing Li, Jing Liu, “Requirement emergence computation of networked software”, Frontiers of Computer Science in China, 2007, 1(3), pp.322-328.

  25. Current RGPS Metamodels Meta-class Meta-class Meta-class Meta-class The Goal Metamodel The Role Metamodel Context related Meta-class Context related Meta-class Context related Meta-class Context related Meta-class The Process Metamodel The Service Metamodel Trustworthy Meta-class Trustworthy Meta-class Trustworthy Meta-class Trustworthy Meta-class Legend Legend Legend Legend

  26. Capturing users’ Intention Analyzing user’s input Presenting the results Lifecycle of Model Selection Comparison

  27. Strength of RGPS • Help to model the real intention of customers • Support effective on-demand model selection • As an enabler for service mass customization • As a supplement of MFI and MDR

  28. A new project or a new part? • As a New Project of ISO/IEC JTC1 SC32 ? • As a New Part of ISO/IEC 19763(MFI) ?

  29. Thank you！ hekeqing@sklse.org wangjian_sd@163.com heyangfan927@163.com wangchong_whu@yahoo.com

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