A Formal Approach for the Inference Plane Supporting Integrated Management Tasks in the Future Internet in ManFI Selected Management Topics Session

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1 In conjuction with: A Formal Approach for the Inference Plane Supporting Integrated Management Tasks in the Future Internet in ManFI Selected Management Topics Session Martín Serrano Researcher at TSSG-WIT ArcLabs Irish National Research Centre John Strassner Director of Autonomic Research at TSSG-WIT ArcLabs Irish National Research Centre Mícheál Ó Foghlú Research Director at TSSG-WIT ArcLabs Irish National Research Centre Telecommunications Software & Systems Group (TSSG) ArcLabs Research & Innovation Centre Agenda Introduction. A Knowledge Plane for the Internet. Knowledge Plane and Beyond. The Inference Plane The Need for Management Systems in the Future Internet. Formal Representations Supporting Integarted Management Tasks. Future Internet Trends and Management Problems. Management in the Future Internet. Semantic-Based Functional Framework & Existing Solutions. Evaluation and Usage & Future Research Work. Conclusions. 1

2 Motivations and Trends A knowledge Plane for the Internet Knowledge Plane Description Different Network Features - Assemble Itself. - Consider High Level Instructions. - Aware to High Level Requirements. - Reassemble Itself. - Automatically Discover Diverse Technologies - Pervasive System. - High Level Service Models. - Service Provisioning. - Advice or Control Other Elements. Fundamental Design Principles. - Simple and Transparent Core. - Intelligence at the Edge. - Carry Data without Knowing What Data Is. David D. Clark, Craig Patridge, J. Christofer Rammin and John T. Wroclawski A Knowledge Plane for the Internet 2 Motivations and Trends Beyond A knowledge Plane Knowledge Plane Definition - Global System. - Decentralized System. - Network Overlay. - Able to Use Cognitive Information. - Self-managing Network End Users Industry Product SERVICE FEE Academia Topic Researchers Motivations for an Inference Plane - Unified Control Plane. - Singular Management Considerations. - Heterogeneous Networks Activiy. - Different Control Mechanisms. E - Coordination Between Different Control Planes. Service s Cost David D. Clark, Craig Patridge, J. Christofer Rammin and John T. Wroclawski A Knowledge Plane for the Internet E Knowledge Plane Data Transport Plane Assertions, Queries, Actions John Strassner, Micheal O Foghlu, Willy Donelly and Nazim Agoulmine Beyond the knowledge Plane: An Inference Plane to Support Next Generation Internet E 3

3 Motivations and Trends The Need for Management Systems Requirements Service Management - Accommodation of Varying Context. - Support for Heterogeneous Programming Languages. - Reuse of Models and Data. - Using Business Goals to Drive Network Services and Resources. Networking Technologies - Better Support of Wired and Wireless Networks - Better Flexibility in Supporting Nodes. - Control of Multi Access Networks. - Accommodation of Cognitive Networking. John Strassner, Micheal O Foghlu, Willy Donelly and Nazim Agoulmine. Beyond the knowledge Plane: An Inference Plane to Support Next Generation Internet 4 FI Management Problem Convergence Management and Middleware Pervasive Computing and Communications Divide Pervasive Computing Networking Technologies Distributed Applications Distributed Information Access Remote Systems Mobile Applications Context-Aware Services Smart Spaces Smart Location Systems Smart Devices Networks Sensors Cooperation Between Heterogeneous Systems and Support for multiple services Heterogeneity of the systems Interoperability systems and services Progressively self-operability of the systems Embedded technologies and capabilities More capabilities for connectivity Progressively smaller and powerful devices ManFI explores and follows the idea of Technological advances and continue evolution in the communications bring new paradigms and concepts as the Future internet 5

4 FI Management Problem Formal Representation Pervasive-Computing Management Tools and Applications Management Applications Diagnostics and Monitoring Agnostic Internet Networking Management Heterogeneous Sources Core Networks Semantics, Ontology Engineering Mechanisms Enforce Activities as Information Modelling Policy-Based Management Ontology-Based Representation 6 FI Management Problem Convergence Management and Middleware Objectives in the Future Internet Integrated Management - Integrate Context Information in Service and Management Environments. - Governance of Resources Devices and Networks. - Orchestration of Services. Future Internet Conditions Semantic Applications Actions Fundamental Approaches C 1,1 C 1,2 Policy Models A 1,1 - Incremental or Evolutionary Design. Policy A 1,2 (Middle box solutions as example) C n,m - Clean Slate Design. (Establishes a new set of ideas) - Evolutionary and Clean Slate Design Core Networks C n,m Policy Management Applications A n,m Compatibility with the Existing Internet. Co-Existing Core Networks IManFI 2009, IM 2009 proccedings, Hamstead, NY, USA Management of the Future Internet 7

5 Semantic-Based Framework Supporting Integrated Management Guidelines to Solve the Problem Integration and representation of context information Integration of context information in next generation services and networks. Ontologies as formal technique for knowledge representation. Ontology-based managing tools, as mechanisms to integrate information Policy-based management systems. Pervasive management using information from data models. Integrated management of the services in next generation networks. Semantic drawbacks inherent in current ICT systems 8 Formal Approach Objective Inference Plane Support Scope and General Objective Formalize Inference Plane Describe a formal inference plane using ontology engineering to increase the semantic richness of policy and other management information models. Serrano, J. Martin Management and Context Integration based on ontologies for Pervasive Service Operations in Autonomic Communication Systems PhD Thesis, Chapter 1, June Inference plane Semantic structures to formalize and represent information. Explicit representation of information management related. Functional and architectural structures. Formalization Declarative language for knowledge representation. Formal language as OWL. Integrated Management Facilitate management operations. Policy-Based Management. Exchange information. 10

6 Formal Approach Objective Inference Plane Support Scope and General Objective Complexity for Integrated Management from different domains Pervasive Computing Domain Network & Services Management Domain Ontology Engineering Domain Middleware Solutions Languages & Protocols Architectures Middleware Solutions Context-Awareness Policy-Based Management Languages Management Domain Service Domain Action(s) Condition(s) Semantic Enriches Semantic Expression Context Information Integration Semantic Event Shortage The Problem to Solve Shortage Syntaxes Context Integration Based on Ontologies for Management Operations A single specific problem to facilitate and provide effective solutions 11 Formal Approach Objective Inference Plane Support General Future Internet Domain Challenges Pervasive Computing Domain Towards Future Internet Semantically augment the context and management information. Augmented information described in the form of policy information. Integrate context, policy-based and ontology engineering concepts. Provide mechanisms for reducing complexity of managing information. Kim Sung-Su, Young J. Won, Mi-Jung Choi, James Won-Ki Hong and John Strassner. Towards Management of the Future Internet 12

7 Thesis Objective Focusing the Problem and Thesis Execution General Domain Challenges Policy Based Management Policy information and data models semantically augmented. Functional framework for managing pervasive services. Integrated Management Related management operations and context by using ontological data. Information models containing lifecycle operations of pervasive services. Facilitate services portability across homogeneous and heterogeneous networks. 13 Formal Approach Objective Inference Plane Support Initial Intentions and Contributions to the Inference Plane Initial Intentions Idea A) Context information model improvements for its integration in management. Idea B) Satisfy semantic shortage in policy information models. Results and Consequences Context information representation and integration by using ontologies. A policy information model integrating context information to be used in policy-based management systems. Idea C) Semantic plane definition as formal information models and functional components. A transitive information model representing and accessorising Onto- Context management framework. 14

8 Existing Solutions Formal Information Models and Ontologies Pervasive Computing Vision Information Models, Languages and Working Groups or Consortiums Semantic Web W3C World Wide Web Consortium Definition for data sharing and re-utilization between communities and applications. OWL Ontology Web Language World Wide Web Consortium. CIM DMTF Distributed Management Task Force, Inc., Management model definition for systems, networks, applications and services. MOF Managed Object Format IDL Interface Definition Language etom TMF Tele Management Forum Enterprise processes descriptions by required service provider. enhanced Telecom Operations Map High Level Descriptions SID NGOSS New Generations Operations Systems and Software Supplementary to the etom, information/data reference model Provides a mapping to the business and system views of the NGOSS system. Shared Information Data Model UML Unified Model Language 15 Existing Solutions Formal Information Models and Ontologies Management Vision Information Models, Languages and Working Groups or Consortiums IETF Internet Engineering Task Force Extensible information models from CIM (PCIM, QPCIM, QDDIM) MIBII IETF RFC 1213 Management Information Model II Internet Engineering Task Force. Information model for logic and physical representation of management object entities and its relationships. DEN-ng Motorola (John Strassner) Business and system views of managed entities and their relationships. Extended scope for business and system views of the SID in NGOSS. Reflexion for the Future Internet Design Process 16 Existing models might be converge by using semantic description of resources, business and operator policies Serrano, J. Martin Management and Context Integration Based on Ontologies for Pervasive Service Operations in Autonomic Communication Systems PhD Thesis, Chapter 6, June 2008.

9 Existing Solutions Services & Management Integration Facts to consider: Information can be modelled by ontologies Management become dynamic with PBNM Pervasive Service Requirement can be expressed in a semantic way. PBNM policies can also be expressed in ontology way. Conditions Semantic Applications Inference Plane Conditions Autonomic Management Autonomic Management Events Actions Actions Management Plane Management Plane Data Model A Network A Data Model B Network B 17 Existing Solutions Services & Management Integration Alternatives Fusion of concepts - Perform mapping to OWL to benefit from existing models. Adam Mickiewicz University, ITTI A.Flizikowski, W.Hołubowicz, K.Samp, R.Marcińczak OpenNet Workshop: March 2007, Brussels 18

10 Existing Solutions Services & Management Integration Alternatives Composition of Ontology - Generate new Ontology, from common concepts over existing models. 19 Elias Zavitsanos, Georgios Paliouras, George A. Vouros A Distributional Approach to Evaluating Ontology Learning Methods Using a Gold Standard - OntoSUM 3rd Ontology Learning and Population Workshop, ECAI 2008 Semantic & Formal Approach Ontology Engineering OSM (Ontology for Support and Management). Ontology for supporting management operations of pervasive services and the integration of the user s context information in service management operations. OSM is a global domain ontology that captures knowledge from 20

11 Semantic & Formal Approach Ontology Engineering OSM (Ontology for Support and Management). OSM Features: Vocabulary of terms with a precise and formal specification. Relate semantics from separate terms defined in different information models. Associated meanings that can be used in heterogeneous information systems. OSM constitutes a guide-example for build up an ontology. OSM follows a four-phase methodology construction process. [Liao07][Horridge04][Ying02][Sure02][Uschold96] and [Grüninger95]. I - Purpose and scope definition. II - Formal definition. III - Evaluation of the Ontology. 21 IV - Maintenance of the ontology. Formal Approach OSM Ontology - Specialization OSM (Ontology for Support and Management). Semantic Descriptions. Formal Representation Knowledge Formalization. OWL OWL S OWL DL OWL Lite DAM+OIL RDF-S RDF XML OSM Policy Information Model Context Representation and Management Operations Representation Information Descriptions & Representation Context, Policy and Management Descriptions Tim Berners-Lee at XML-2000 Conference (Washington DC, Dec, 2000) Serrano, J. Martin Management and Context Integration Based on Ontologies for Pervasive Service Operations in Autonomic Communication Systems PhD Thesis, June Terms Definition Concepts Representation. Tags and Labels. 22

12 Formal Approach OSM Information Model Interactions Context Information and Policy-Based Management Interactions OSM ontology integrates domain concepts. OSM use DEN-ng model concepts. OSM model is composed by pervasive management concepts. 23 Formal Approach OSM Information Model Support and Management Operations Model Simplified View 24 Interaction Graphical representation for two or more elements in class diagrams. Relationship Semantic description of the interaction between two or more elements Simple syntax rules and specific keywords (e.g., isdefinedas ).

13 OSM Evaluation Usage OSM Comparison with Related Works Considerations in Related Work Comparison Context Data Capabilities of the Ontology to represent context information. Information can be expressed using a structured and defined. The information model use a formal grammar. Capabilities to represent the concepts in a graphic form. Capability to handle information by using schemas. Other computing mechanisms to facilitate inference. 25 OSM Evaluation Usage OSM Comparison with Related Works Considerations in Related Work Comparison Communications Systems Capability to make use of the context information coming from end-user. Capability to support management policies in the standard format if <Condition> then <Action> else <Action> content for the condition and action can be made up of context itself. Capability to include properties of management systems that make use of the context information coming from pervasive applications. Capability to exchange information with applications and sensors. 26

14 OSM Evaluation Usage OSM Comparison with Related Works Considerations in Related Work Comparison Ontology Support Features to determine how extensible is the ontology. Features to determine extensibility and formalism. Operation in other management systems Capability to support language-based applications. 27 OSM Evaluation Usage OSM Comparison with Related Works Related Work Comparison 28 Serrano, J. Martin Management and Context Integration based on ontologies for Pervasive Service Operations in Autonomic Communication Systems PhD Thesis, Chapter 6, June 2008.

15 Conclusions Summarizing Contributions Ontology enhancement for the Inference Plane - A formal mechanism to integrate context information. - Pervasive service management operations FI Mgt. Operations. Ontology as formalism necessary to capture concepts from the context information for helping to integrate data - Service management operations - Future Internet business models. Semantics augments the expressiveness of policy information model - Adding domain-specific context data. - Ontologies in the inference plane facilitate service management operations definition. 29 Conclusions Summarizing Contributions Ontology engineering provides - Enrichment necessary to satisfy lacking in information models. - Structures necessaries for formalization and explicit representation. - Policies and its elements as well as other management information related semantic features to be shared. Inference plane refers to the architectural guidelines for developing support systems that accessorise the management of pervasive services associated with such information. 30

16 Future Research Activities Applications and FI Mgt. Architectures Applications of Ontology-Based Information Models. Emerging Architectures. Ontologies and Management Systems Implementation. Credits and Aknowledgements Image Attribution and Web Site Support Introduction: Thesis Objective: Thesis Contributions: Revision of Concepts: Tim Berners Lee s original web server in CERN. Thesis Approach: Existing Solutions: No attribution - original removed Evaluation and Usage: Conclusions: Slides Support: [UPC-NMG] Ontology Engineering Seminar [WIT-TSSG] Taught Master - Master Talk A Formal Approach for the Inference Plane Supporting Integrated Management Tasks in the Future Internet Martín Serrano Researcher at TSSG-WIT ArcLabs Irish National Research Centre John Strassner Director of Autonomic Research at TSSG-WIT ArcLabs Irish National Research Centre Thank You! Mícheál Ó Foghlú Research Director at TSSG-WIT ArcLabs Irish National Research Centre Telecommunications Software & Systems Group (TSSG) ArcLabs Research & Innovation Centre