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An OWL Ontology for QoS

An OWL Ontology for QoS. Glen Dobson (Russell Lock, Ian Sommerville) Lancaster University g.dobson@lancs.ac.uk. Overview. QoSOnt is an OWL ontology for Quality of Service (QoS) I will attempt to answer: What is an ontology? What is OWL? What is QoS? Why is a QoS ontology needed?

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An OWL Ontology for QoS

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  1. An OWL Ontology for QoS Glen Dobson (Russell Lock, Ian Sommerville) Lancaster University g.dobson@lancs.ac.uk e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  2. Overview • QoSOnt is an OWL ontology for Quality of Service (QoS) • I will attempt to answer: • What is an ontology? • What is OWL? • What is QoS? • Why is a QoS ontology needed? • How should one go about designing such an ontology? • What are the possible approaches? • What are the difficulties? e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  3. What is an ontology? • Standard answer: • “A specification of a conceptualization” (Gruber) • Pragmatically: • A description of the concepts and relationships which exist in some domain using a formal language. • An ontology is an engineering artefact for machine understanding • Its purpose is important. • It should represent shared conceptualisations. • A shared vocabulary is the fundamental component of an ontology • Domain rules are also important e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  4. What is OWL? • OWL is the Web Ontology Language • Supports sharing ontologies via the web • Built on top of RDF (and XML in turn) • Aim is to enable machine “interpretation” of terms and their relationships • It is a Description Logic • Primary constructs are Classes and their Properties • A Class defines a set of Individuals by precisely stating a set of membership conditions. • Main form of inference is subsumption • i.e. is Class B a complete subset of Class A? • + Classification: What Classes is Invidual I a member of? e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  5. OWL in the Semantic Web OWL e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  6. Class Definitions in OWL • Classes can be described • As named resources (as in RDF) • As an enumeration • By constraints on their Properties • By combining other Classes using set operators • Descriptions be combined to give a Class definition using OWL’s: • subClassOf • equivalentClass • disjointWith e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  7. OWL and Inference • A Dog could be asserted to be a Mammal. • Or this classification could be inferred based upon the Class Dog’s Properties (and Property restrictions) • E.g. warm blooded, feeds young with milk, internal fertilisation, etc. • Problem of maintaining a polyhierarchy manually • a Dog is a Mammal, an Animal, a Pet, etc. • Therefore assert a “monohierarchy” and have multiple classifications inferred e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  8. What is your definition of QoS? • Any non-functional aspect of a system that someone may use to judge quality • Extends the definition in distributed multimedia where QoS is primarily concerned with the network (and performance in particular) • In practice we have concentrated primarily on dependability – but the concepts apply beyond this. • What QoS concepts are modelled? • We are primarily concerned with the core concepts of QoS (e.g. attributes, metrics) • Also some consideration to QoS requirements e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  9. Why an ontology for QoS? • To provide a shared vocabulary • For use primarily by machines – but perhaps also in human-readable documents (e.g. requirements documents, SLAs). • To embody machine interpretable “knowledge” • e.g. QoS brokers may need to translate between terms/infer aggregate values/convert units, etc. • Also the provision of QoS description and reasoning capabilities to the semantic web e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  10. QoS Sub-Systems Service Payment Banking systems Service Discovery Service Differentiation Service negotiation Service Agreements Service Operation Service Monitoring Service Mediation QoS Prediction Re-negotiation Workflow Planning Law e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  11. What “added value” could a QoS ontology provide? • Translation based upon machine “understanding” • Translation of units, computation of composite metrics, inference of aggregate QoS for workflows • Leeway in syntax matching • i.e. multiples terms can refer to the same thing • An interlingua for translation between other QoS languages • A means for agents to communicate e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  12. QoSOnt Structure • At the core of QoSOnt is a taxonomy of Attributes and Metrics • i.e. two trees formed using the subClassOf construct • An attribute is e.g. reliability, performance • A metric is e.g. Probability of Failure on Demand, Transactional Throughput • This becomes a (complex) directed graph once properties are considered • e.g. The Property hasMetric (and its inverse isMetricOf) is the basic link between the attribute and metric trees e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  13. Danger of Ontology Creep • Should we provide a model to represent: • Time • Currently we do – but we should instead use the OWL-Time ontology. • Ways of composing metrics, Mathematical constructs that don’t exist in OWL • This originally put us off and thus we have a separate XML language as well as the ontology. • Ways of composing services • We currently use a very shallow model – but perhaps this is all that is needed? e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  14. QoSOnt High-Level Structure Metric Instances Metric Layer Metrics Attribute Layer Performance Dependability Etc …. Low level concepts Base concepts Time Underlying OWL e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  15. IFIP 10.4 Dependability Taxonomy • Our example of an attribute layer ontology • Familiar Fault-Error-Failure model • Main point of linkage is DependabilityAttribute is a subclass of QoSAttribute • Shows how a detailed model of certain attributes can help • E.g. without the definition of Failure, Failure Domain it is impossible to be specific about what a Probability of Failure On Demand refers to e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  16. Overview of Metric Definition e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  17. Representing QoS Requirements • As OWL Classes using built-in OWL constructs • Datatype support is poor • No consistent way of using custom XML types • Reasoning support for quantification over datatypes (e.g. allValuesFrom 0-100) is poor. • Level of datatype support mandated by OWL spec is poor • Using QoSOnt defined Classes, Properties, Restrictions, etc. • As a separate (XML) language referencing the ontology e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  18. SQRM Tool e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  19. Requirements Matching in SQRM e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  20. Evaluation/Future (1) • An ontology is a good idea – but a large-scale standardisation effort is required • Need external input in order to evolve • Two interested parties are now involved • Requirements representation and matching using built-in OWL features would be nice • Need to wait for OWL to develop • Need to look at SWRL (Semantic Web Rules Language) • E.g. would provide a neater way to express unit conversions e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  21. Evaluation/Future (2) • Need to work on tools that make use of QoSOnt (and also enhance SQRM) • Difficult to evaluate otherwise since the purpose is machine-machine understanding • But are there really a lot of QoS “semantics” to model? • Service Composition/Workflow • Integrating existing work with ontology e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

  22. Questions For more information: http://digs.sourceforge.net e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk

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