New approach to agent based management in service ans smart spaces environment is being developed at OSLL (http://osll.ru)

1. The 5th conference on Internet of Things and Smart Spaces ruSMART 2012
Smart Space Applications Integration:
A Mediation Formalism and Design for
Smart-M3
Yury Korolev, St. Petersburg Electrotechnical University, Russia.
Dmitry Korzun, Petrozavodsk State University, Russia.
Ivan Galov Petrozavodsk State University, Russia.

2. Agenda
• Ways of agents communication in the smart spaces.
• Agents coordination mechanisms
(the exchange of management information).
• Applications integration mechanisms
(the exchange of computational information).
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3. IoT Architecture
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4. Smart-M3 Platform
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5. General Smart Space Platform
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6. Agents Communications Categories
Communication can be
• Point to Point
– An agent talks directly to another agent.
•
Broadcast
– An agent sends some information to a group of
agents.
• Mediated
– The communication between two agents is
mediated by a third party.
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7. Whiteboard-based communications
• Making use of upper ontologies.
• Agents interact indirectly through shared ontology.
• Agents use the publish/subscribe mechanisms.
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8. Communication via mediator
•Problem of integration of applications processing multiple
heterogeneous data sources.
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9. Integration of Smart Conference System
with blogging service
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10. Analogy with Qt signals and slots
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11. Analogy with Qt signals and slots 2
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12. The concept of mediation
S = ( n, I , ρ )
Meta Information.
(For example,
rules from an
ontology or agents
coordinations
rules)
• Mediator is a kind of the context interpretator.
• The interpretation is based on rules. 12

13. What information should be passed?
Information can be:
•
Managment Group control of the
– Events agents based on the
– Notifications interpretation of events.
•
Computational
– Knowledge Run time knowledge
exchange.
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14. Rules for management information
( E1 ,E 2 ,C ) - Association rule. Association rules can be constructed
automatically based on data mining techniques (Association rule learning).
E1 - Triggering event. – The owner left the house.
E 2 - Resulting event. – Turn off the lighting.
C - Context. – The house has no more people.
E 2 ← E 1, C have_state(lighting, turn_off) :-
left(?x, house),
is(number_of_people_in_the_house,0).
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15. Problems
1. How to exchange heterogeneous computational
information between the agents?
2. How to improve the performance of inference?
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16. Smart Space Applications Integration Definition
1. Smart space applications matching: process of establishing
logical correspondences between elements of the source and
target ontologies of integrated applications. As a result of this
process integration scenarios are formed.
2. Run time instance mapping: process of mapping the
instances, processed by integrated applications.
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17. Smart Space Applications matching
The expert must determine:
1. The events that initiate the process of integration;
(<application_ID>,<notification_name>,<data_id>);
2. Input data for integration;
SELECT *
WHERE {
?person foaf:name ?name .
?person foaf:mbox ?email .
}
3. Mapping rules to transform entities of the source smart
space to entities of target smart space.
'title'(postId, titleValue) :-
'Title'(presentationID, titleValue),
generateUID(postId).
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18. Run time instance mapping
Ss is a source smart space;
N is a data loading notification;
P is a set of graph queries to the source smart space;
T is a set of transformation mapping rules for the source and target smart spaces;
St is a target smart space.
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19. Mediator specification
µ = ( O1, O2 , N , P , Q, D, T )
O1 ,O2 - source and target ontologies.
N = { ni} - notifications.
P = { pi } - source queries (one per notification).
Q = { qi } - target queries (one per notification).
D = {d i } - source to target dependencies.
T = {t i } - a set of transformation rules (one per notification).
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20. Integration of hierarchical information
• Need to establish a logical correspondence between integrable entities.
• Or need to keep the history of integration. 20

21. Integration of hierarchical information 2
• Need to establish a logical correspondence between integrable entities.
• Or need to keep the history of integration. 21

22. Transformation mapping rules types for
computational information
• Production rules;
• UIDs (URIs) generation;
• Manipulations with
• numbers;
• strings;
•
date and time;
• Integration of hierarchical information.
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23. Manipulations with strings
text = create_string('Speaker is %s (email: %s; phone: %s;).
Presentation is available at: %s', is, email, phone, url); 23

24. Mediator Architecture
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25. Mediator Activity Diagram
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26. The mediator has a decentralized nature
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27. Thank you for your attention
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