Industrial Ontologies Group

University of JyväskyläUniversity of Jyväskylä

CONTEXT-POLICY-CONFIGURATION:CONTEXT-POLICY-CONFIGURATION:Paradigm of Intelligent Autonomous System CreationParadigm of Intelligent Autonomous System Creation

CONTEXT-POLICY-CONFIGURATION:CONTEXT-POLICY-CONFIGURATION:Paradigm of Intelligent Autonomous System CreationParadigm of Intelligent Autonomous System Creation

Oleksiy KhriyenkoOleksiy Khriyenko

June 8 – 12, 2010, Funchal, Madeira - PortugalJune 8 – 12, 2010, Funchal, Madeira - Portugal

University of Jyväskylä, FinlandUniversity of Jyväskylä, Finland

Vagan TerziyanVagan Terziyan

IOG, Agora Center, MIT IOG, Agora Center, MIT DepartmentDepartment

(presenter)(presenter)

1212thth International Conference on Enterprise Information Systems International Conference on Enterprise Information Systems

~ICEIS 2010~ ~ICEIS 2010~

1212thth International Conference on Enterprise Information Systems International Conference on Enterprise Information Systems

~ICEIS 2010~ ~ICEIS 2010~

Sergiy NikitinSergiy Nikitin

ContentContentContentContent

System evolution trendsSystem evolution trends UBIWARE platformUBIWARE platform Policy based system…Policy based system… Context-Policy-Configuration…Context-Policy-Configuration… Role-based Policy ControlRole-based Policy Control

Conclusions and future opportunitiesConclusions and future opportunities

CPC extensionCPC extension Example…Example…

AcknowledgementsAcknowledgements

System evolution trendsSystem evolution trendsSystem evolution trendsSystem evolution trends

Semantic Web:Semantic Web: semantic technologies are viewed today as a key technology to resolve the semantic technologies are viewed today as a key technology to resolve the problems of interoperability and integration within the heterogeneous world of ubiquitously problems of interoperability and integration within the heterogeneous world of ubiquitously interconnected objects and systemsinterconnected objects and systems;;

To achieve the vision of ubiquitous knowledge, the next generation of integration To achieve the vision of ubiquitous knowledge, the next generation of integration systems will utilize different methods and techniques:systems will utilize different methods and techniques:

Agent Technologies:Agent Technologies: a agent based approach to software engineering is considered to be gent based approach to software engineering is considered to be

facilitating the design of complex systems.facilitating the design of complex systems.

Context awareness:Context awareness: to be smart, system should be able to behave accordingly to a state of to be smart, system should be able to behave accordingly to a state of

environment and react on dynamic changes of it.environment and react on dynamic changes of it.

Policy:Policy: highly valuable approach towards creation automatically controllable system.highly valuable approach towards creation automatically controllable system.

UBIWARE platformUBIWARE platformUBIWARE platformUBIWARE platform

The The UBIWARE PlatformUBIWARE Platform is a development framework for creating multi-agent is a development framework for creating multi-agent systems. systems.

OntologyOntologyOntologyOntology

Rules Rules

Beliefs Beliefs

ActionsActionsActionsActions

new Beliefsnew Beliefsnew Beliefsnew Beliefs

OntologyOntologyOntologyOntology

Rules Rules

Beliefs Beliefs

OntologyOntologyOntologyOntology

Rules Rules

Beliefs Beliefs

OntologyOntologyOntologyOntology

Rules Rules

Beliefs Beliefs

OntologyOntologyOntologyOntology

Rules Rules

Beliefs Beliefs

Proactive Goal-driven Dynamic ResourceProactive Goal-driven Dynamic Resource as a main entity of any system… as a main entity of any system…

GUN GUN (Global Understanding Environment) concept: (Global Understanding Environment) concept: environment where all the resources of the virtual and environment where all the resources of the virtual and

the real world are connected and interoperate with the real world are connected and interoperate with each other…each other…

S-APL S-APL (Semantic Agent Programming Language): (Semantic Agent Programming Language): solves description of beliefs, rules and understanding solves description of beliefs, rules and understanding of their semantics, the meaning of predicates used in of their semantics, the meaning of predicates used in

those rules by all the parties involved while using those rules by all the parties involved while using first-order logic as the basis for an APL…first-order logic as the basis for an APL…

Policy based system…Policy based system…Policy based system…Policy based system…

System with two different levels of programming/administration. System with two different levels of programming/administration.

““advanced user” programming/administration:advanced user” programming/administration: implies building of the rules to reach implies building of the rules to reach different goals that cover particular domain. It is a definition of a certain domain by Ontology of different goals that cover particular domain. It is a definition of a certain domain by Ontology of Goals (set of possible abstract goals that can be reached by Resource, including sub-goal Goals (set of possible abstract goals that can be reached by Resource, including sub-goal hierarchy), and by set of abstract Behaviour Rules that can be used to achieve these goals (sub-hierarchy), and by set of abstract Behaviour Rules that can be used to achieve these goals (sub-goals);goals);

high-level system programming/administration:high-level system programming/administration: stage where user has to put the stage where user has to put the constraints on abstractions, he/she should specify/create concrete instance of goal/goals and constraints on abstractions, he/she should specify/create concrete instance of goal/goals and provide necessary initial states of the system;provide necessary initial states of the system;

Types of policies: Types of policies:

““D&R-type” policy:D&R-type” policy: user defines domains and ranges that can be considered as a policy user defines domains and ranges that can be considered as a policy for the system that should be followed during goal achievement process;for the system that should be followed during goal achievement process;

“ “ W-type ” policy:W-type ” policy: vector of weights of properties’ significance or vector of vector of weights of properties’ significance or vector of weights/preferences of any abstraction in general caseweights/preferences of any abstraction in general case;;

Context-Policy-Configuration…Context-Policy-Configuration…Context-Policy-Configuration…Context-Policy-Configuration…

Context-dependent Policy-based ControlContext-dependent Policy-based Control is an approach, able to leave is an approach, able to leave Resource flexible, dynamic and controlled at the same time. Resource flexible, dynamic and controlled at the same time.

CONTEXTCONTEXT POLICYPOLICY CONFIGURATIONCONFIGURATION(CONSTRAINTS)(CONSTRAINTS)

State of the EnvironmentState of the Environment(Resources with their properties)(Resources with their properties)

Context-based Policy Creation SystemContext-based Policy Creation System Resource Configuration EngineResource Configuration EngineModule builds a model of Policy based on Module builds a model of Policy based on available contextual information…available contextual information…

Module applies Policy and configures Resource Module applies Policy and configures Resource (its believes, capabilities, ontology, etc.)(its believes, capabilities, ontology, etc.)

Policy modelsPolicy models Resource believes, ontology, etc.Resource believes, ontology, etc.(Restricted subset of knowledge (Restricted subset of knowledge

and capabilities)and capabilities)(Filtering model, mask for perception)(Filtering model, mask for perception)

context

context

contextcontext

context

contextcontext

Configured knowledge and Configured knowledge and abilities to behave…abilities to behave…

context

OntologyOntologyOntologyOntology

OntologyOntologyOntologyOntology

(accordingly to policy model based on correspondent context)

0x

0x

0x

0x

)(xf

)(xf )(xf

)(xf

...),,,,(~...)))),(,(,(,()( 00000000 xxxxfxfxfxfxfxf

),...,,,( 113

12

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),...,,,( 223

22

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Role-based Policy ControlRole-based Policy ControlRole-based Policy ControlRole-based Policy ControlGenerally we deal with a system with big amount of entities (Resources) with own Generally we deal with a system with big amount of entities (Resources) with own behaviours and goals. To be able to control the system on general level, we have to put behaviours and goals. To be able to control the system on general level, we have to put constraints/policies on separate entities as well as on the system in whole.constraints/policies on separate entities as well as on the system in whole.

Role as a Context. Role as a Context. Any organization, union, company, society, group, individual and etc. Any organization, union, company, society, group, individual and etc. can be considered as a sub system that plays certain Role, which restricts it with can be considered as a sub system that plays certain Role, which restricts it with particular set of goals and knowledge/resources used for goal achievement. particular set of goals and knowledge/resources used for goal achievement.

OntologyOntologyOntologyOntology

Role mRole mRole kRole k

Role nRole n

Role nRole n11

Role nRole n22

Role mRole m11

Role mRole m22

Role kRole k11

CPC extensionCPC extensionCPC extensionCPC extension

To be compatible with widely used technology we extend To be compatible with widely used technology we extend RDF SchemaRDF Schema with with some classes and properties for policy description. some classes and properties for policy description.

Policy System Ontology

RestrictionContainer

D&R_RestrictionContainer W_RestrictionContainer

basisSystem_is

hasRestrictionhasConfiguredOntology

rdfs:domainrdfs:range

rdfs:domain rdfs:rangerdfs:domain

rdfs:range

rdfs:subClassOfrdfs:subClassOf

ContainerProperty Class Resource

rdfs:subClassOf

rdfs:type

rdfs:subClassOfrdfs:type

rdfs:Statement

rdfs:Statement…

rdfs:Statement

rdfs:Statement…

RDFSRDFS

CPC CPC extensionextension

applied tordfs:range

rdfs:domain

Figure shows us initial part of CPC-extension of RDFS.Figure shows us initial part of CPC-extension of RDFS. In the platform we utilize N3 representation in S-APL language. In the platform we utilize N3 representation in S-APL language.

Example…Example…Example…Example…

Statement #1subject objectpredicate

Policy #n

applied to

GreenFactory #m

inContext

ContextContainer #1

Statement #2subject objectpredicate

GreenFactory #m

hasRole

Role #k

Statement #3subject objectpredicate

Factory #k

hasConfiguredOntology

Ontology #i

rdfs:Statement

rdfs:range

property: useEnergy

Oil-energy

Wood-energy

Coal-energy

Nuclear -energy

Hydro-energy

Wind-energy

Sun-energy

basisSystem_is Factory #k

hasRestriction D&R_RestrictionContainer #1

hasRestriction W_RestrictionContainer #1

Policy #n

rdfs:Statement

rdfs:range

Nuclear -energy

Hydro-energy

Wind-energy

Sun-energy

property: useEnergy

rdfs:Statement

buyEnergyFrom

Supplier #jSystem

rdfs:Statement

hasRelevance0.7

Consider a System – Consider a System – “GreenFactory”“GreenFactory” as a subsystem of as a subsystem of “Factory” “Factory” System with only System with only difference that “GreenFactory” utilized only green kind of energy: Nuclear-, Hydro-, Wind-, difference that “GreenFactory” utilized only green kind of energy: Nuclear-, Hydro-, Wind-, Sun-energy, etc.Sun-energy, etc.

““GreenFactory”GreenFactory” join some industrial financial group and should follow a policy that join some industrial financial group and should follow a policy that demands at least 70% of energy to be bought from the energy supplier that belongs to the demands at least 70% of energy to be bought from the energy supplier that belongs to the same financial group even if it is more expensive then buy energy from other suppliers. same financial group even if it is more expensive then buy energy from other suppliers.

Conclusions and future opportunitiesConclusions and future opportunitiesConclusions and future opportunitiesConclusions and future opportunities

This research presents a policy-based approach for supporting the high-level This research presents a policy-based approach for supporting the high-level configuration of systems, integrated into the middleware platform. Policies are configuration of systems, integrated into the middleware platform. Policies are high-level, declarative statements governing choices in the behaviour of a high-level, declarative statements governing choices in the behaviour of a system. system.

With this approach we do not program system in a hardcoded way, but build With this approach we do not program system in a hardcoded way, but build it able to change internal functionality and behaviour on the fly when context is it able to change internal functionality and behaviour on the fly when context is changed.changed.

As a future steps we are planning to elaborate a machine learning module to As a future steps we are planning to elaborate a machine learning module to automate (provide a suggestion to the user) the process of policy creation automate (provide a suggestion to the user) the process of policy creation depending on correspondent context.depending on correspondent context.

AcknowledgementsAcknowledgements AcknowledgementsAcknowledgements

University of JyväskyläUniversity of Jyväskylä

www.cs.jyu.fi/ai/OntoGroupwww.cs.jyu.fi/ai/OntoGroup

www.cs.jyu.fi/ai/OntoGroup/UBIWARE_details.htmwww.cs.jyu.fi/ai/OntoGroup/UBIWARE_details.htm