1. March 23, 2006M.I.T., Anna Univ, Chennai 1 Development of Front End tools for Semantic Grid Services Dr.S.Thamarai Selvi, Professor & Head, Dept of Information Technology, Madras Institute of Technology, Anna University, Chennai. Review Meeting – March 24, 06

2. March 23, 2006 M.I.T., Anna Univ, Chennai 2 Objective To develop a Front End Tools for Semantic Grid Services that enables the Service Requester to search a particular Grid Service/Resource Semantically. the Service Provider to describe a Grid Service/Resource Semantically.

3. March 23, 2006 M.I.T., Anna Univ, Chennai 3 Activities Study of current version of Globus Toolkit and study of Semantic Grid Services  Understand the grid architecture and study of globus toolkit.  Study of languages needed to implement semantic grid services. A prototype model for semantic grid services  Extending the UDDI registry to include semantic advertisements using TModels.  Design and Development of algorithms for intelligent discovery of grid services. Design and Development of Grid Resource Portal Functional testing and optimization of implementation

4. March 23, 2006 M.I.T., Anna Univ, Chennai 4 Road Map Understanding various Components of Globus Toolkit 4.0 Understanding Semantic Web Services. Understanding the technology used to develop Semantic Web Services. Understanding Semantic Grid Services. Developing a typical prototype for Semantic Grid Services.

5. March 23, 2006 M.I.T., Anna Univ, Chennai 5 Layered Architecture of semantic grid service Concepts and Tools to build semantic web applications that includes:- *Protégé, an OWL editor. *Algernon, an inference engine *OWLS for service descriptions The concept of Matchmaking of services using OWLS An application has been built that retrieves information from resource ontology using algernon. Summary of last review meet – Sep 02, 2005 Report

6. March 23, 2006 M.I.T., Anna Univ, Chennai 6 Creation of resource ontology may be automated * We have developed a java module using protégé-OWL APIs to develop and manage ontology. We can use this module for managing resource ontology * We are also developing a tool to convert WSDL into OWLS with which we can create service ontology without manual intervention. Aggregation of resource information may be automated ( may use RFC 2016 and RFC 2608) * We made thorough literature survey of GIIS of Globus toolkit and we identified wsrf-query and grid-info-search toolS in Globus toolkit with which we can aggregate the grid resource informationgrid-info-search Summary of last review meet – Sep 02, 2005 Observations and Suggestions

7. March 23, 2006 M.I.T., Anna Univ, Chennai 7 Status as on March 20, 2006 Implementation Issues have been identified Several Approaches for implementing Knowledge layer have been identified. Implementation of Semantic Grid Architecture using proposed approaches. Proposal of Versatile Knowledge layer.

8. March 23, 2006 M.I.T., Anna Univ, Chennai 8 Focus Today Semantic Grid Architecture Difficulties with Conventional Mechanisms Proposed Approaches for Knowledge Layer Semantic Grid Architecture using Protégé Enabled Globus toolkit(PEG) Semantic Grid Architecture using Resource Ontology Template Further Scope Conclusion

9. March 23, 2006 M.I.T., Anna Univ, Chennai 9 The Semantic Grid is an extension of the current Grid in which information is given a well- defined meaning, better enabling computers and people to work in cooperation Semantic Grid

10. March 23, 2006 M.I.T., Anna Univ, Chennai 10 Distributed Resources Computation Services LayerData Services LayerInformation Services LayerKnowledge Layer Semantic Grid Architecture Resources Includes Supercomputers, clusters Workstations etc., This layer Manages allocation of computational resources, Job Execution, Secure Access to grid resources This layer deals with the way resources are represented, stores, shared and Maintained This layer act as an infrastructure to support the management and application of scientific knowledge to achieve particular types of goal and objective shared and Maintained

11. March 23, 2006 M.I.T., Anna Univ, Chennai 11 Related Tools  Ontology You need an Editor to Create Ontology  Inference Engine To retrieve Knowledge from Ontology

12. March 23, 2006 M.I.T., Anna Univ, Chennai 12 Ontology Ontologies are used to capture knowledge about some domain of interest. Ontology describes the concepts in the domain and also the relationships that hold between those concepts Complex concepts can therefore be built up in definitions out of simpler concepts. Ontology Web Language (OWL) is widely used to create Ontology Ex : Protégé, an OWL editor

13. March 23, 2006 M.I.T., Anna Univ, Chennai 13 Limitation of OWL Though OWL has a well-defined semantics, but it is not sufficiently expressive to characterize and describe services So, OWL-S, OWL for Service

14. March 23, 2006 M.I.T., Anna Univ, Chennai 14 OWL-S OWL-S is an OWL-based web service ontology, which supplies a core set of markup language constructs for describing the properties and capabilities of web services in unambiguous, computer interpretable form

15. March 23, 2006 M.I.T., Anna Univ, Chennai 15 Limitations of OWLS Though OWLS has WSDL2OWLS, but it cannot convert Grid WSDL to OWLS. It cannot recognize WSRF specific WSDL elements. Hence we need to compromise while using the tool WSDL2OWLS

16. March 23, 2006 M.I.T., Anna Univ, Chennai 16 Currently there is no tool available to create Grid Service Ontology automatically from its WSDL file Difficulties We need to create Service Ontology using Protégé Editor Need to identify a tool to convert Grid WSDL into OWLS descriptions. Need to automate semantic descriptions of resource Solution Challenges in OWLS

17. March 23, 2006 M.I.T., Anna Univ, Chennai 17 Proposed Approach Semantic Description and Discovery of Grid Services We propose and implement Semantic Grid Architecture by integrating protégé editor with Globus Toolkit and implements Parameter Matchmaking Algorithm for semantic discovery of services. Semantic Description and Discovery of Grid Resources We propose a five layered semantic grid architecture using Gridbus broker that addresses the need of semantic component in the grid environment to discover and describe the grid resource semantically Also It is decided to devise a knowledge layer for semantic description of resources and its retrieval, for semantic description of services and matchmaking of advertised grid services against the requested ones.

18. March 23, 2006 M.I.T., Anna Univ, Chennai 18 Semantic Description and Discovery of Grid Services

19. March 23, 2006 M.I.T., Anna Univ, Chennai 19 Protégé Enabled Globus Toolkit Globus Toolkit (GT) lacks a component to describe concepts semantically. In PEG, protégé has been integrated into Globus Toolkit 4.0 It addresses the demands of a single toolkit to build grid infrastructure as well as for semantic description and representation of services and resources. Globus user now can develop ontology for their services.

20. March 23, 2006 M.I.T., Anna Univ, Chennai 20 Architecture of Semantic Grid Service using PEG

21. March 23, 2006 M.I.T., Anna Univ, Chennai 21 Service Matchmaking Refers to capability matching which means to compare requested service description with the advertised service description to determine how similar they are. Matchmaking algorithm uses Inputs and Outputs for matching and does not consider Preconditions and Effects as they are not sufficiently standardized to be considered for matchmaking On an optional basis, other properties can also be taken into account assuming they have been described using any specific ontology language such as OWL. In our Parameter Matchmaking Algorithm, We propose to use Inputs, Outputs and Functionality for matchmaking of services.

22. March 23, 2006 M.I.T., Anna Univ, Chennai 22 Parameter Matchmaking Algorithm We introduce Parameter Matchmaking Algorithm that computes degree of matching of service advertisement (A) and request (R) The algorithm compares IOF of A and that of R, computes various degree of matches namely:- Exact: A and R exactly matches A(IOF) ≡ R(IOF) Plug-in: A offers more functionalities than R A(IOF) ≥ R(IOF) Subsume: R requests more functionalities than advertised A A(IOF) ≤ R(IOF) Intersection: Not all functionalities matches A(IOF) ∩ R(IOF) Disjoint:A and R does not match A(IOF) ≠ R (IOF)

23. March 23, 2006 M.I.T., Anna Univ, Chennai 23 Processes Involved Ranked Degree of Match Input Matching Output Matching Functionality Matching A (I) R (I) R (O) A (O) R (F) A (F) Aggregate Module IrIr OrOr FrFr Parameter Matchmaking Algorithm Intermediate Ranks after Comparing I, O, F individually Computes Final ranked Degree of match

24. March 23, 2006 M.I.T., Anna Univ, Chennai 24 Functional Model of the Knowledge Layer

25. March 23, 2006 M.I.T., Anna Univ, Chennai 25 Service Provider A GridService that implements four functionality namely Addition, Subtraction, Multiplication and Division. Service Ontology has been created using Protégé editor to describe the service. Implementation A sequence diagram of service provider

26. March 23, 2006 M.I.T., Anna Univ, Chennai 26 Service Requester The requester submits Query. The semantic component extracts F from the query (R F ) and also from service ontology (A F ). It compares R IOF with A IOF and computes ranked degree of match {exact, plugin, subsume, intersection, disjoint} Sequence diagram of service requester

27. March 23, 2006 M.I.T., Anna Univ, Chennai 27 Sl.No Capability Requested Degree of Match Possibility of service invocation 1Addition and SubtractionPlug inTrue 2 Addition, Subtraction, Multiplication and Division Exact True 3 Addition, Subtraction and Reversal of string Intersection True 4Squaring and Temperature serviceDisjointFalse 5 Addition, Subtraction, Multiplication and Division, Temperature Service subsume True 6Multiply, add, dividePlug in True 7Square serviceDisjointFalse 8Addition and factorialIntersection True 9Add, sub, divide and MultiplyExactTrue Experimental Results

28. March 23, 2006 M.I.T., Anna Univ, Chennai 28 Snapshots

29. March 23, 2006 M.I.T., Anna Univ, Chennai 29 Parameter Matchmaking Algorithm

30. March 23, 2006 M.I.T., Anna Univ, Chennai 30 The Scenario of plug in match

31. March 23, 2006 M.I.T., Anna Univ, Chennai 31 The Scenario of Exact match

32. March 23, 2006 M.I.T., Anna Univ, Chennai 32 The Scenario of Intersection match

33. March 23, 2006 M.I.T., Anna Univ, Chennai 33 The Scenario of Disjoint match

34. March 23, 2006 M.I.T., Anna Univ, Chennai 34 Semantic Description and Discovery of Grid Resources

35. March 23, 2006 M.I.T., Anna Univ, Chennai 35 Objective To propose a five layered semantic grid architecture with knowledge layer at the top of gridbus broker Knowledge layer – Semantic grid resource description using adaptive ontology template and Knowledge discovery using Algernon inference engine.

36. March 23, 2006 M.I.T., Anna Univ, Chennai 36 Motivation Conventional mechanisms UDDI MDS They offer searching mechanism based on keywords. The node providers need to agree upon attribute names and values. In grid like environment, where resources come and go there is always a demand for framework to support semantic description and discovery of services and resources.

37. March 23, 2006 M.I.T., Anna Univ, Chennai 37 A Five Layered Architecture of Semantic Grid Services

38. March 23, 2006 M.I.T., Anna Univ, Chennai 38 Knowledge Layer Comprises two modules – Semantic Description and Discovery Semantic Description Domain Knowledge of grid is represented in ontology template MDS is used to ‘plug’ grid resource information Protégé-OWL APIs are used to build knowledge base of the grid using ontology template Semantic Discovery Algernon inference is used to retrieve resource information Job Descriptor Creates Application Description File and Resource Description File to run the broker

39. March 23, 2006 M.I.T., Anna Univ, Chennai 39 Ontology Template Definition – 1 Any resource can be modeled as an instance of a specific class provided that the resource can be described using the properties defined in that class. Definition – 2 An ontology template is the domain specific ontology that provides hierarchy of classes with properties to define characteristics. Protégé-OWL APIs are used to describe grid resources in the ontology template.

40. March 23, 2006 M.I.T., Anna Univ, Chennai 40 Resource Ontology Template

41. March 23, 2006 M.I.T., Anna Univ, Chennai 41 Grid Resource Knowledge base

42. March 23, 2006 M.I.T., Anna Univ, Chennai 42 Query Generator User Resource Description GridBus Broker Job execution Resource Discovery Resource App. Des FileRes. Des File Querying OWL file Algernon Query MDS Request User Submit Job Semantic Repository Results To user … Job Descriptor Resource Information Semantic Description Semantic Component

43. March 23, 2006 M.I.T., Anna Univ, Chennai 43 Semantic Description GIIS service runs on globus machine will retrieve resource information of the local host and stores it in LDAP server from where we can query the information. Protégé-OWL provides versatile libraries with which one can manage ontology and knowledge base. With those APIs insertion and removal of resources are possible OWLNamedClass computerC=owlmodel.getOWLNamedClass("WorkStation"); OWLDatatypeProperty hasIP = owlModel.getOWLDatatypeProperty("hasIP"); cpuI.addPropertyValue(owlModel.getOWLObjectProperty("hasCPUVendor"),cVendorI); computerI.addPropertyValue(owlModel.getOWLObjectProperty("hasCPU"),cpuI);

44. March 23, 2006 M.I.T., Anna Univ, Chennai 44 Semantic Discovery  We use Algernon Inference Engine to retrieve information semantically.  This module accepts user query in the form of A:opB and converts it into Algernon query to interact with the knowledge base.  Once suitable resource is discovered, user’s job will be submitted to gridbus broker for execution.  This Knowledge Layer is implemented in Gridbus Broker, it can support most of the popular middlewares including Globus, Alchemi etc.,

45. March 23, 2006 M.I.T., Anna Univ, Chennai 45 Snapshots

46. March 23, 2006 M.I.T., Anna Univ, Chennai 46 Protégé Ontology Editor

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53. March 23, 2006 M.I.T., Anna Univ, Chennai 53 Further Scope Semantic Grid Architecture using PEG Currently, service descriptions are done manually. We are in the verge of developing a tool to convert WSDL of WSRF services into OWS descriptions thereby overcoming the limitation of human intervention for creating service ontology. Wide literature survey of domain ontology is required. Ontology clustering can be implemented to improve the performance of matchmaking. Storing OWLS descriptions into UDDI registry is to be resolved for better management of semantic descriptions

54. March 23, 2006 M.I.T., Anna Univ, Chennai 54 Semantic Grid Architecture using Resource Ontology Template The discovery module relies on the power of Inference engine used to retrieve information semantically from the Knowledge base. Since Algernon is an rule based inference engine, we need to implement rules to improve the efficiency of searching Mechanism Workflow Engine Integrating Workflow component with the knowledge layer.

55. March 23, 2006 M.I.T., Anna Univ, Chennai 55 Extended Knowledge Layer With these observations and scope, we present a versatile knowledge layer that performs, Semantic Description of resource using ontology template Semantic description of services using GridWSDL2OWLS Managing OWLS descriptions in UDDI registry Clustering the OWLS descriptions using appropriate clustering mechanism Implementation of QoS based Matchmaking Algorithm with the help of domain ontology. Implementation of Rule based semantic search engine

56. March 23, 2006 M.I.T., Anna Univ, Chennai 56 Extended Knowledge Layer

57. March 23, 2006 M.I.T., Anna Univ, Chennai 57 Conclusion The semantic grid architecture using PEG enables the service providers to describe their grid services semantically. Whereas, the architecture using Gridbus broker, provide semantic descriptions of grid resources using grid resource ontology template. We also identify the necessity of GridWSDL2OWL-S tool and is being developed in our Grid Computing Laboratory. We made a wide literature survey of ontology clustering with which the performance of ontology matchmaking can be improved. With these observations, we propose a versatile knowledge layer which can be implemented in the grid architecture that performs semantic descriptions of grid resources, WSDL description of WSRF services into OWL-S descriptions, Discovery of Suitable Grid resources, Ontology clustering and QoS based Matchmaking algorithm. With these sophisticated features implemented in architecture will result in versatile front end for implementing semantic grid services.

58. March 23, 2006 M.I.T., Anna Univ, Chennai 58 Appendices

59. March 23, 2006 M.I.T., Anna Univ, Chennai 59 Ontology Framework Web Services WSRF Services OWL OWL-S OWL RBAC uses descr Product/ Process Model Business Process Ontology Organisational Ontology Service Ontology Resource Ontology User/Role Authorisations Services System Resources represents Auth. Service Ontology-Based Virtual User Desktop Distributed run-time environment ref uses WSDL grid run on ? Courtesy: Global Grid Forum 16 Athens, Greece, February 13-16, 2006

60. March 23, 2006 M.I.T., Anna Univ, Chennai 60 Life without Broker Courtesy: University of Melbourne, Gridbus Broker Presentation

61. March 23, 2006 M.I.T., Anna Univ, Chennai 61 Life with Broker Scheduling ? Courtesy: University of Melbourne, Gridbus Broker Presentation

62. March 23, 2006 M.I.T., Anna Univ, Chennai 62 Questions

63. March 23, 2006 M.I.T., Anna Univ, Chennai 63 Thank You