University of Dublin Trinity College - School of Computer ... · This is where Autonomic Behaviour...
Transcript of University of Dublin Trinity College - School of Computer ... · This is where Autonomic Behaviour...
Autonomic Management and Ontologies © Declan O’Sullivan 3
Growing Complexity… Future network environment and system
Core Network
Satellite
Broadcast Networks
(DAB, DVB-T)
The Internet
ISP
CDMA, GSM, GPRS
IP-based micro-mobility
Wireless LANs
Signalling Gateway
WAP Accounting
Context-aware information Centre
Billing VHE SIP Proxy Server
WiBro, HSDPA
4G Bluetooth Zigbee
access operator
ISP
ASP
corporation
DMB
MP3
Camera
M-banking
Cam Navigation
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Growing Complexity… Service Oriented Environments
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Growing Complexity… Very large scales
• million of entities
Ad hoc (amorphous) structures/behaviors • p2p/hierarchical architecture
Dynamic • entities join, leave, move, change behavior
Heterogeneous • capability, connectivity, reliability, guarantees, QoS
Unreliable • components, communication
Lack of common/complete knowledge • number, type, location, availability, connectivity, protocols, semantics, etc.
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Coping with complexity… Our system programming paradigms, methods and management tools seem to be inadequate for handling the scale, complexity, dynamism and heterogeneity of emerging future network and systems Biological systems have evolved strategies to cope with dynamic, complex, highly uncertain constraints Recently, research applying biological system concepts to solve its unsolved problems
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Autonomic Computing Autonomic
• Pertaining to an on demand operating environment that responds automatically to problems, security threats, and system failures
• Cf) self-adaptive, self-governing, self-managing, … The term “autonomic” is derived from human biology – autonomic nervous system
• ANS monitors heartbeat, body temperature, … – Without any conscious effort on one’s part!
Nature has evolved to cope with scale, complexity, heterogeneity, dynamism and unpredictability, lack of guarantees
• self configuring, self optimizing, self healing, self protecting, highly decentralized, heterogeneous architectures that work !!!
The goal of autonomic computing is to use appropriate solutions based on current state/context/content based on specified policies
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Autonomic Computing Attributes
Self-managing systems that deliver Increased Responsiveness Adapt to dynamically changing environments
Business Resiliency Discover, diagnose,
and act to prevent disruptions
Operational Efficiency Tune resources and balance workloads to maximize use of IT resources
Secure Information and Resources
Anticipate, detect, identify, and
protect against attacks
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Key Aspects of an Autonomic System Model
Various
SOUPA
Policy models Ponder, XACML,
PCIM
Rei, Kaos,
DARPA XG SWRL
Resource models
MIBs, CIM, SID
OWL…
CORBA, RMI, WSDL
OWL-S, WSMO
Ontologies becoming lingua franca
This is where Autonomic Behaviour is defined
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Questions What is the potential role of Ontologies in the Engineering of Autonomic Systems? What are the benefits and costs of engineering with ontologies? Where do we go from here?
© David Lewis
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Key Aspects of an Autonomic System Model
Various
SOUPA
Policy models Ponder, XACML,
PCIM
Rei, Kaos,
DARPA XG SWRL
Resource models
MIBs, CIM, SID
OWL…
CORBA, RMI, WSDL
OWL-S, WSMO
Ontologies becoming lingua franca
This is where Autonomic Behaviour is defined
© David Lewis
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Adaptive Service Element A Reference Model to show how ontology based semantics can help integrate:
• service-oriented modelling • resource-modelling • policy-based management • context-modelling
Resource is logically managed / wrapped by a service Service Elements have well defined inputs and output and can be composed Service Element’s operation and adaptation is dependent on its preconditions and effects Adaptive behaviour can be:
• Context Driven • Constrained by Policy
Not an ‘Autonomic Service Element’
Adaptive behaviour
model Input Output
Preconditions Effects
Policy Management Interface
Resources Context
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Wireless Access
ISP Service
Sensor Network
Adaptive behaviour
model Input Output
Preconditions Effects
Policy Mgmt i/f
Resources Context
User User or Value
Governened Adaptive Service Element
Application Service
Network Service
Client Application
E2E service policies
Policy Refinement
Composite Autonomic System – combines:
• Service-oriented provision of value
• Policy-based governance
• Context-Awareness • Resource
management
E2E Service
Policy Refinement
S S C C C R R R
© David Lewis
namespace { _"http://www.dmtf.org/CIM_Device29/Printers#" } concept PrinterJob JobId ofType (1 1) _string JobSize ofType (1 1) _integer MimeTypes ofType MimeType RequiredPaperType ofType (1 1) PaperType Copies ofType (1 1) _integer DefaultNumberUp ofType (0 1) NumberUp HorizontalResolution ofType (0 1)_integer NumberUp ofType (0 1) NumberUp PrintJobstatus ofType (1 1) _string TimeComplete ofType (0 1) time RequiredJobSheets ofType (1 1) _integer OwningPrinterQueue ofType (1 1) PrintQueue PrinterServiceJob ofType (1 1) Printer
concept PrintQueue NumberOnQueue ofType (1 1) _integer MaxJobSize ofType (1 1) _integer OwnPrintJobs ofType PrinterJob PrinterServiceQueue ofType Printer
concept Printer subConceptOf LogicalDevice PrinterStatus ofType (1 1) _string DetectedErrorState ofType (0 1) _string ErrorInformation ofType (0 1) _string PaperSizesSupported ofType PaperSize PaperSizesAvailable ofType PaperSize DefaultPaperType ofType (0 1) PaperType CurrentPaperType ofType (0 1) PaperTpye MimeTypesSupported ofType MimeType CurrentMimeType ofType (0 1) MimeType DefaultMimeType ofType (0 1) MimeType JobCountSinceLastReset ofType (1 1) _integer TimeOfLastReset ofType (0 1) time MaxCopies ofType (0 1) _integer DefaultCopies ofType (0 1) _integer MaxNumberUp ofType (0 1) NumberUp DefaultNumberUp ofType (0 1) NumberUp HorizontalResolution ofType (0 1) _integer VerticalResolution ofType (0 1) _integer MaxSizeSupported ofType (0 1) _integer AvailableJobSheets ofType (0 1) _integer Capabilities ofType Capability DefaultCapabilities ofType (0 1) Capability CurrentCapability ofType (1 1) Capability
namespace { _"http://example.org/ont#", dc _"http://purl.org/dc/elements/1.1#", cimPr "http://www.dmtf.org/CIM_Device29/Printers", uPnPPr_"http://www.upnp.org/services/wsmo/
PrintBasicv1_01" } ontology uPnPPr#CreatePrintJob concept uPnPPr#CreatPrintJobReq uPnPPr#JobName ofType (0 1) _string uPnPPr#JobOriginatingUserName ofType (1 1) _
string uPnPPr#DocumentFormat ofType (1 1)
cimPr#MimeType uPnPPr#Copies ofType (0 1) _integer uPnPPr#Sides ofType (0 1) cimPr#SideTypes uPnPPr#NumberUp ofType (0 1)
cimPr#NumberUp uPnPPr#OrientationRequested ofType (0 1) uPnPPr#PaperOrientation uPnPPr#MediaSize ofType (0 1) cimPr#PaperSize uPnPPr#MediaType ofType (0 1) cimPr#PaperType uPnPPr#PrintQuality ofType (0 1) cimPr#Capability
interface CreatePrinterJobIntf choreography CreatePrinterJobChor stateSignature CreatePrinterJobSig importsOntology { "http://www.upnp.org/services/wsmo/PrintBasicv1_01”,
"http://www.dmtf.org/ont/CIM_Device29/Printers"}
in uPnPPr#CreatPrintJobReq out cimPr#PrinterJob
transitionRules PrinterPolicies forall (?request) with (?request memberOf uPnPPr#CreatePrintJobReq and ?request[uPnPPr#DocumentFormat hasValue ?format] and ?request[uPnPPr#Copies hasValue ?copies] and ?request[uPnPPr#NumberUp hasValue ?numup] and ?request[uPnPPr#MediaSize hasValue ?size] and ?request[uPnPPr#MediaType hasValue ?type]
and ?request[uPnPPr#PrintQualit hasValue ?qual] and ?queue[cimPr#PrinterServiceQueue hasValue ?printer] and ?printer[cimPr#MaxCopies hasValue ?maxcopies]
) do add(?job [ cimPr#MimeType hasValue ?
format, cimPr#RequiredPaperType hasValue ?type, cimPr#Copies hasValue ?copies, cimPr#NumberUp hasValue ?numup, cimPr#PRinterServiceJob hasValue ?printer, cimPr#OwningPrinterQueue hasValue ?queue
] memberOf cimPr#PrinterJob) | if ?copies > ?maxcopies then
update(?job[cimPr#Copies hasValue ?maxcopies]) | if ?copies > 100 then update(?job[cimPr#NumberUp hasValue 2]).
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Benefits of Engineering with Ontologies
Integration of key modelling aspects Progressive modelling of elements
• Progressive conceptual understanding
Easier integration of separately sourced models • Good for multi-vendor systems and value chains • Integrating with models from completely different domains, e.g. GIS, genetics etc.
Logical consistency checks Exploit general purpose reasoners and tools (Jena, Protégé etc) Non Benefit:
• Does not help model adaptive behaviour – FSM is minimum, but can expect many non-deterministic models, e.g. bio-inspired
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ASE-Specific Benefits Services
• More accurate service discovery (provided service offerings are accurate) • Runtime interoperability
Resources • More complete model through axiom and rules? • Progressive, incremental models?
Policy • Determining applicable policies • Extensibility – primarily in semantics of condition and targets • Impact on refinement and conflict handling?
Context • Gathering context from unknown, heterogeneous sources
– Widespread in ubicomp research • Middleware emerging – KBN, Construct etc
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Costs
Classic Semantic Bootstrap problem • SemWeb: Someone has to bear the costs of providing semantic markup of
content For ASE, the equivalent is Grounding
• OWL-S/WSMO to WSDL • Resource models to MIBS/CIM/SID • Context and policies to native forms
Ontological form may not be best for • Transmission or storage • Runtime-matching or interoperability • Non-DL or rule-based reasoning, e.g. temporal reasoning, sub-reasoning
Must maintain groundings to versions of ‘normative’ models Must frequently invoke grounding mapping function
• May not be fully automated
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Cost-Benefit Analysis
Benefits win out where: • Grounding costs are minimised – especially where ontology used for
normative/canonical form • Service (re)composition and/or changes to policies and context are
frequent and preferably dynamic • Open market with lots of ASE offerings
Costs win out where: • Grounding cost are high: non-ontological languages used for core
engineering modelling • Frequency of change is low and resource/behaviour complexity is high • Intra-organisational integration more common than inter-organisation
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Likely Application Domains Favours communications domains where:
• Level of innovation in services and networks is high • Services and networks can be freely integrated • Complexity is compositional
Less appealing where: • Large body of legacy models • Resource control and commoditisation are priorities • Complexity is monolithic
Favours • Internet/mobile application services - Software as a Service • Lightly regulated wireless – MANETS, Mesh, Cognitive Radio • Pervasive Computing
Less suited: • Wired-backbones, expensive/static network elements, ISPs, 3G
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Next Steps
Mixed initiative engineering and governance tools providing help with: • Inconsistencies when integrating ontologies • Incompleteness when building models • Explaining reasons for policy conflicts • Suggesting policy refinement paths • Browsing/searching large populations of models • Developing grounding mappings – including natural language processing • Developing semantic interoperability mappings • Version control
Leave Protégé to the SemWeb researchers – need stronger, modular engineering platform, i.e. Eclipse
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Next Steps Tool design need a better understanding of tensions between optimal semantic forms (including non-ontological) for:
• Sharing and integration • Human comprehension • Automated reasoning
Need to understand when to move from general purpose ontological tools and reasoners and to optimised-but-constrained versions
• From innovation phase to production/provision phase
Semantics for Benchmarking (and benchmarking for semantics)
• Abstract user/traffic patterns, failure models, threat models
© David Lewis
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Ontology-based Engineering - Summary
May be necessary but certainly isn’t sufficient for modelling an autonomic system or its elements
• Good for monitoring, analysis and execution – not so much for planning
May not be necessary in all cases to providing cost-saving benefits of an autonomic system Definitely necessary to reap the value-adding benefits of autonomic systems
• Maintaining operational savings of self-management through business change
• Supporting innovation in creating business value
© David Lewis