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e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
An OWL Ontology for QoS
Glen Dobson(Russell Lock, Ian Sommerville)
Lancaster Universityg.dobson@lancs.ac.uk
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: 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? 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
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
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
OWL in the Semantic Web
OWL
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
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
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
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
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
QoS Sub-Systems
Service Discovery
Service negotiation
Service Mediation
Service Monitoring
Service Agreements
Service Payment
Service Operation
Banking systems
Service Differentiation
Law
Re-negotiation
QoSPrediction
WorkflowPlanning
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
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
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
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
QoSOnt High-Level Structure
Time
Performance Dependability Etc ….Attribute Layer
Low level concepts Base concepts
MetricsMetric Layer
Underlying OWL
Metric Instances
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
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
Overview of Metric Definition
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
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
SQRM Tool
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
Requirements Matching in SQRM
e-Science AHM, Nottingham. September 20th, 2005. Glen Dobson: g.dobson@lancs.ac.uk
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
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
Questions
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