Semantic Pervasive Computing: state-of-the-art approaches Computer Engineering Department, Sharif...

Semantic Pervasive Computing: state-of-the-art approaches

Computer Engineering Department, Sharif University of Technology.

Behrad Zari ([email protected])

Semantic Pervasive Computing, Distributed Systems Course, June 2006 1

mailto:[email protected]

Outline• Pervasive Computing

– Characteristics of Interest

• Pervasive Computing Paradigm– Pervasive Services– Semantics of Pervasive Services

• Semantic Web Technology– Introduction– Benefits

• Context Modeling Ontologies• Semantic Web Services

– Architecture– An Example

• Semantic Pervasive Spaces– Triple Space Computing

• Conclusion & Open Questions• References


Pervasive Computing Characteristics

• Discovery and Matchmaking

• Inter-operability between different entities

• Context-awareness


Discovery and Matchmaking• Discovery:

– Pervasive Computing Environments have one or more registries to keep a real time state of the system, i.e., the entities currently present and available.

– In the Discovery Service, standard schemas are needed to describe many kinds of entities, including people, places, and things.

• Matchmaking:– what sets or combinations meet

certain criteria, i.e., the requirements and preferences of the parties.


Smart Devices


Inter-operability– involve dozens, if not hundreds of

devices (sensors, external input and output devices, remotely controlled appliances, etc.)

– Multiple inhomogeneous networks• Short range: IrDA, Bluetooth,

Wireless LAN• Wide area: (HS)CSD, GPRS,

UMTS• Often also no network

– Interoperability Nightmare

– Proliferation of devices that need to be connected.


Inter-operability (cont’d)

• Accomplish discovery and configuration of new devices without “a human in the loop”.

• Automatic formation of device coalitions.

• Qualitatively stronger means of representing service semantics are required.

• Heterogeneity and Autonomy:– Machine process-able descriptions


Context-Awareness• Applications in pervasive and mobile

environments need to be context-aware so that they can adapt themselves to rapidly changing situations.

• Different kinds of contexts (such as location of people, activities of individuals or groups, weather information, etc.).

• The various types of contextual information that can be used in the environment must be well-defined so that different entities have a common understanding of context.


Ubiquitous Computing Paradigm

What’d be the magic?


Not A dream…

• The right service

• At the right place

• At the right time

• At the right cost


A Solution

• Wide range of services:– Carrier Service– Ticket Reservation Service– Transport Service– Information Service– Routing Service– …

• We need Pervasive Services.• But what is a Service?


Pervasive Services

• Independently developed and deployed

• Life-Cycle Management– Compare to Agent Systems

• Input/Output, Pre/Post-Conditions, Effects

• Profile for logic semantics of the service.

• Discovery– SLP, Jini, Bluetooth SDP, UDDI,

GSD, DNS-SD …


Semantics for Pervasive Services• Data/Information Semantics

– What: Formal definition of data in input and output messages of a service

– Why: for discovery and interoperability– How: by annotating input/output data of services using

ontologies

• Functional/Operational Semantics– Formally representing capabilities of service– for discovery and composition of Services– by annotating operations of Services as well as provide

preconditions and effects

• Execution Semantics– Formally representing the execution or flow of a

services in a process or operations in a service– for analysis (verification), validation (simulation) and

execution (exception handling) of the process models

• QoS Semantics– Formally describing operational metrics of a

service/process– To select the most suitable service to carry out an

activity in a process


Semantic Web Technology

How it relates to Pervasive Computing?


Introduction• “The Semantic Web will bring structure

to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users.” [Berners-Lee 1998]


Key Benefits• Serendipitous Interoperability: the

ability of software systems to discover and utilize services they have not seen before.

• With the Semantic Web approach it is possible for agents to “learn” new vocabularies and – via reasoning – make meaningful use of them.

• Automated service discovery, selection and composition.

• Has proof-of-application in Multi-Agent software systems.


Ontology Benefits• Enabling semantic discovery of entities.

• Allowing users to gain a better understanding of the environment and how different pieces relate to each other.

• Allowing both humans and automated agents to perform searches on different components easily.

• Allowing both humans and automated agents to interact with different entities easily.

• Allowing both humans and automated agents to specify rules for context-sensitive behavior of different entities easily.

• Enabling new entities (which follow different Ontologies) to interact with the system easily.


Context Modeling Ontologies

Some Proposed Ontologies


CoOL ASC Model


CoOL Ontology


GAIA Ontology• Converts physical spaces and the

devices they contain into a programmable computing system.

• Multiple Ontologies has used to augment various system services:– Configuration management– Discovery and matchmaking– Human Interfaces– Interoperation of components– Context Sensitive behavior

• Implemented on DAML+OIL and CORBA standards.


GAIA Ontology Infrastructure


CHIL Ontology• A general-purpose core vocabulary

for the various concepts within a multi-sensor smart space.


SOUPA


CoBrA Ontology


CoBrA Architecture


SOCAM Ontology


SOCAM Architecture


An Extensible Ontology• User

– Important properties include a user’s profile, but also his preferences, mood and current activity.

• Environment– the environment in which the

user interacts is an important aspect of the context specification. It consists of time and location information, and environmental conditions, such as temperature and lighting.


An Extensible Ontology (2)

• Service– provides specific functionality to

the user. Specifying semantic and syntactic information sustains easy service discovery and service interaction.

• Platform– hardware and software

description of a specific device.


Ontology Core Overview


User Ontology


Environment Ontology


Platform Ontology


Service Ontology


Semantic Web Services

A further step towards Pervasive Systems needs


Architecture


Name

Year

Date

Duration

City

Outputs

Interfaces

Inputs

Area

Coordinates

City Forrest

XML Schema Data type hierarchy

Temporal-Entity

TimeInterval

Time-Point

Date Time

TimeDomain

Event

Scientific-Event

Calendar-Date

{absolute_time}

{hour, minute, second}

{millisecond}

{year, month, day}

{dayOftheWeek, monthOftheYear}

= Time - Ontology

= Local ontology

{name}

{x, y}

Get ConferenceInformation

Ontologies

Web Service

QoS OntologyQoS Ontology

<xsd:complexType name=“Date"><xsd:sequence><xsd:element name=“year" type="xsd:integer" / ><xsd:element name=“month" type="xsd:integer" / ><xsd:element name=“day" type="xsd:byte" / >

</ xsd:sequence></ xsd:complexType>

<portType name=“ConferenceInformation"><operation name="getInformation"><input message="tns:Data" / ><output message="tns:ConferenceInformation" / >

</ operation>

Conference Information Functions

Information Function

Get Information Get Date

Data Semantics

FunctionalSemantics

WSDL

WSDL

QoSSemantics

Min

Quality


Task Computing Environment• Fujitsu Laboratories of America and

the MINDSWAP research group at the University of Maryland Implementation of a smart conference room.

• Expose the functionality in rich pervasive environments (device functionality or third-party functionality) as Semantic Web services, which in turn the user can discover and arbitrarily compose.

• STEER client.


Semantic Pervasive Spaces


Triple Space Computing• Proposed By Digital Enterprise

Research Institute (DERI) at W3C Workshop on the Ubiquitous Web, Tokyo, 2005.

• Provides a web that is optimized for machines, thus simplifying the sharing of data and the coordination of devices and services in dynamic and heterogeneous systems.

• Services will have to understand each other and exchange information over the Ubiquitous Web to allow human users access to the world's information spaces whenever and wherever they find themselves.


TSC Architecture


TSC Access Model• Write(URI ts, Graph triples):URI

– Write an RDF graph containing one or more triples to the Triple Space ts. returns: the URI that identifies the written graph.

• Read(URI ts, Template template):Graph – Read a set of triples matching the given

template. returns: the RDF triples that were matched by the template.

• Read(URI ts, URI graph):Graph – Read the RDF graph identified by the provided

URI. returns: the RDF graph that is identified by the URI.

• Take(URI ts, Template template):Graph – Take (read and remove) one RDF graph

matching the given template. returns: one of the graphs that have matching triples.

• Take(URI ts, URI graph):Graph – Take the RDF graph identified by the provided

URI. returns: the graph that is identified by the URI.


Open Questions• Triple Spaces provides us with

– A web of devices– Data and interaction heterogeneity,– Decreased communication overhead

(no Context gathering overhead)

• A service language– Like WSDL for Web Services

– DAML-S, OWL-S

• Triple spaces + OWL-S = Semantic Pervasive Spaces?


Conclusion• Semantic Web goals propose

potential cases of usages in pervasive computing domain.

• Semantic Web is not covered our lives as current Web does yet.

• We need a standardized solution– As CORBA, EJB or others did to

Distributed Computing years ago.– Some implementation should be

proven.– How many standards and

consortiums should be gathered?


References• M. Satyanarayanan. Pervasive Computing: Vision and Challenges. School

of Computer Science Carnegie Mellon University, IEEE Personal Communications, 2001.

• Ora Lassila, Applying Semantic Web in Mobile and Ubiquitous Computing: Will Policy-Awareness Help?, Nokia Research Center.

• Ryusuke Masuoka and Yannis Labrou, Fujitsu Laboratories of America, Bijan Parsia and Evren Sirin, MIND Lab, University of Maryland, Ontology-Enabled Pervasive Computing Applications, IEEE INTELLIGENT SYSTEMS, 2003.

• Jorge Cardoso, Amit Sheth, Semantic Web Processes, 4rd International Conference on Web Information Systems Engineering, WISE 2003.

• Heraklion, Crete, Ubiquitous Services Cluster - UbiServ, DERI Offsite, May 2005.

• Reto Krummenacher, Thomas Strang, Dieter Fensel. TRIPLE SPACES FOR AN UBIQUITOUS WEB OF SERVICES, Position Paper: W3C Workshop on the Ubiquitous Web, Tokyo, Japan, March 9-10, 2005.

• Ippokratis Pandis, et.al. An Ontology-based Framework for Dynamic Resource Management in Ubiquitous Computing Environments, 2005.

• Sheila A. McIlraith, Tran Cao Son, and Honglei Zeng, Semantic Web Services, Stanford University.

• Ovidiu Chira, The Semantic Web, IDIMS Report, February 2003.


References (2)• Davy Preuveneers, et.al. Towards an extensible context ontology for

Ambient Intelligence, 2004.

• Tao Gu, et.al. An Ontology-based Context Model in Intelligent Environments, 2004.

• Harry Chen, et.al. SOUPA: Standard Ontology for Ubiquitous and Pervasive Applications.

• Harry Chen, et. al. Using OWL in a Pervasive Computing Broker

• Harry Chen, et.al. An Ontology for Context Aware Pervasive Computing Environments.


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