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Semantic web services discovery

ESOCC2013
by

Kobkaew Opasjumruskit

on 25 October 2013

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Transcript of Semantic web services discovery

Towards Leveraging Semantic Web Service Technology for Adaptive Sensors Discovery for IoT
PhD Symposium in ESOCC 11th Sept. 2013, Malaga, Spain
Kobkaew Opasjumruskit, University of Jena, Germany

Agenda
Problem & Motivation
Brief introduction to MERCURY
State of the art
Solution Outline
Research Plan

Service discovery Usages
Challenges
http://mercury-portals.org
Problem & Motivation
Brief introduction to MERCURY
State of the art
Solution Outline
Research Plan
Initial Assumption
Internet of Things
Physical things
becoming smart devices
Things can be programmed to make decisions
User adaptive
Remotely control
Things communicate with each other
Publish devices as web services
Limit set of web services, mostly social network applications
Require programming & hardware skill
Current approaches
Things?
Sensors
e.g. Temperator,
GPS location
Actuators
Web Services
e.g. Flight schedule
e.g. Alarm,
Ambulance
Integration of devices
Cope with heterogeneous devices
Complexity of usages
Tailored-made application with minimum technical effort
Scenario
Service Registration
Scenario Modelling
Scenario Execution
Standard Service Description
+Semantic Annotation
WSDL (Web Services Description Language)
OWL-S (Web Ontology Language for Web Services) : OWLS-MX
WSMO (Web Service Modelling Ontology) : WSMO-MX
SAWSDL (Semantic Annotations for WSDL) : SAWSDL-MX, SAWSDL-iMatcher
Tag-based Description
S3 (Semantic Service Selection)
Contest
How can we find desired services?
Compare service matchmakers performance
: WSCOLAB
Register rain sensor & calendar
Without specifying technical information
Update "Rain sensor" due to user's context
Automatically search for a nearby sensor and replace it
Create jogging scenario from rain sensor & alarm clock
Suggests relevant services
2012
Conclusion
Focus of this thesis
All devices are available as web services with WSDL descriptions.
Service Registration
Scenario Modelling
Scenario Execution
Q&A
Right balance between the service matchmaking computing time and the accuracy of results.
Implement the dynamic service discovery during the runtime.
The evaluation of service recommendation can be made following the guidelines in the S3 Contest.
Leverage the semantic web services technology to improve the automatic service discovery in the IoT
Aware of user context and personalized information
The service description contains at least a WSDL
The architecture of the service discovery
In the near future
Current challenge
Presented the core architecture and the prototype.
: The automatic service discovery in the registration process.
: The first prototype of automatic service discovery in the scenario modelling
: Complete the service discovery in this scenario modelling
2013
2014
: Complete the runtime service discovery
: Establish the user evaluation
: Improve the service discovery due to feedbacks from users
It is compulsory to specify the domain of discoverable services
ambiguous descriptions : ”apple” fruit or brand.
Optionally, OWL-S, SAWSDL or social-tagging, etc.
This thesis is not proposing a new service matchmaker
This work employs existing service matchmaking approaches
by defining the ontology repository
Automatically assign the ontology to a request from a user correctly
April
June
October
April
May
October
Challenges
Support various service description formalisms
Make these formalisms configurable without tampering with the code to support new description languages in the future
In the real-time processing
improve the matchmaking processing time
guarantee the reliability of the dynamic service discovery
Choose the suitable information to add to the service request
Existing
Matchmakers
x Weight
values
re-configurable
weight
City name
Weather
Screenshot Demo
Full transcript