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P3 3-fabio schreiber
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PERVASIVE DATA MANAGEMENT
IN FUTURE NETWORKED ENTERPRISES
Fabio A. Schreiber and Letizia Tanca Politecnico di Milano
The Networked Enterprise Background
Increasing international competition
Flexibility needs
Rapid evolution of the environments (market needs and available technologies)
Reduction of the time-to-market
Need of personalising the offer
A new organisational model not limited to the production supply chain but involving also the design and innovation processes : the networked enterprise
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Traditional model
providers purchase production distribution customers
Networked enterprise
Network based interdependent companies
Aimed at cooperation and coordination
Pervasive, Context-aware Systems
Networked enterprises need information gathered
from multiple heterogeneous sources
Information noise must be filtered by context in
order to provide only the right data to the right
person in the right situation
Pervasive languages can be effectively used to
design and implement complex, self-adapting
applications
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The Artdeco project vision
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To develop models, methods
and a platform to support
exchange of information
through various enterprises
part of a supply chain
• Sensors and RFIDs placed
everywhere allowing the system
to monitor the position of
products and their state in the
supply chain
• Mechanisms to autonomically
reconfigure a sensors network
based on environmental
conditions
• Context awareness allowing the
various actors of the enterprise
to access the right information at
the right time
Artdeco
middleware
Product X
arriving
tomorrow
Product X
on truck Y
on A1 highway
Context-aware information and service tailoring
• observables
• context schema
Context Modelling
• instantiation
• validation
• reasoning
Context Sensing
• context-aware data
• context-aware operations
Context-Aware
Behaviour
design-time run-time
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Case Study: The Wine LifeCycle
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Design Time Modeling
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risk
Context is hierarchically modelled in terms of observable parameters that have
a symbolic internal representation within the CDT context schema
The CD model is completely independent of the specific formalism adopted.
The Context Dimension Tree
Context-aware data tailoring
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Context-aware system architecture
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DATA VIEW FOR CONTEXT C
Some contextual views
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Sample contexts:
C1=< phase=harvesting, *, role=agronomist >
C2 =< phase=ageing, *, role=agronomist >
C3=< phase=harvesting, *, role=qlity manager >
C4 =< phase=transport, *, role=qlity manager >
Some contextual queries
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The agronomist during the harvesting phase
(context C1) wants to collect all the available
information coming from sensors:
SELECT m.date_time,m.value,s.s_id, s.meas_unit FROM C1.sensor s, C1.measure_data m
WHERE s.s_id=m.s_id;
S/he obtains only the information from sensors
placed in the vineyards (see Rel(C1))
Some contextual queries
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The quality manager during the harvesting phase
(context C3) wants to collect all the available
information about bottles of “Aglianico” wine:
SELECT *
FROM C3.bottle b
WHERE b.appellation="aglianico";
But the query is out of context, in the context C3
only information about vineyard and grapevine
are available for the qlity manager
The environment is modelled in terms of dimension, concept nodes and attributes
Intuitively a valid context is a particular subtree of the CDT (formally defined in IJWET09)
Agronomist
Overheat
Driver QtyMngr
Role
Disease
Growth Ageing Transport
Type
$Square_meters $ID
Affected
hectares
Risk Phase
A fragment of the CDT model
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Context management at runtime
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context
recognition
context
switch
querying
• Context activation
• Real-time C-A behaviour
sensing
sensors as tuple providers
A middleware and a
language to manage
pervasive systems hiding
the complexity of handling
different technologies
• Numerical observables
• Symbolic observables
Context-aware WSN
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Apply the sensor query
only to the sensors in
context:
phase = ‘growth'
AND
risk='overheat‘
AND
orientation=‘west
ward’
Example: Given the previous CDT
CREATE DIMENSION Role
CREATE CONCEPT Agronomist
WHEN get_user_role()=‘agronomist’
CREATE CONCEPT QtyMngr
WHEN get_user_role()=‘qtyMngr’
CREATE CONCEPT Driver
WHEN get_user_role()=‘driver’
CREATE DIMENSION Risk
CREATE CONCEPT Disease
WHEN get_interest_topic()=‘disease’
CREATE CONCEPT Overheat
WHEN temperature > 30 AND
brightness > 0.75;
…..
Agronomist
Overheat
Driver QtyMngr
Role
Disease
$ID $square_
meters
Type Affected
hectares
Risk
The context language (1/2)
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CREATE CONTEXT Growth_Monitoring
ACTIVE IF phase = ‘growth' AND role=‘agronomist’ AND Risk='overheat'
ON ENABLE(Growth_Monitoring):
SELECT temperature,humidity
SAMPLING EVERY 120 s
EXECUTE IF location = ‘vineyard'
SET PARAMETER 'alarm' = TRUE;
ON DISABLE(Growth_Monitoring):
SET PARAMETER 'alarm' = FALSE;
REFRESH EVERY 24 h;
Agronomist Growth
Risk
Overheat
Role Phase
The context Language (2/2)
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ID Temperature Brightness
1 28 0.60
3 31 0.71
4 33 0.80
OVERHEAT:
temperature > 30 AND brightness > 0.75
The context is active for all the
sensors for which the rule is true,
and the context-aware actions will
be performed only on them.
The CM associates to every dimension of the CDT a table that
contains the values of every numeric observable sampled from the
environment.
Agronomist Growth
Risk
Overheat
Role Phase
The context manager
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Concluding remarks
Pervasive systems are widely adopted to monitor many kinds
of physical phenomena and to seamlessly accommodate
information coming from all kinds of heterogeneous data
sources (e.g. social networks as sensors)
Context-awareness plays a fundamental role since it allows,
through the perception of the environment, to make the system
autonomic w.r.t. environmental situations and changes.
Further data personalization can be obtained considering the
user’s preferences
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Acknowledgements
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Giorgio
Orsi Cristiana
Bolchini
Letizia
Tanca
Fabio A.
Schreiber
Elisa
Quintarelli
Romolo
Camplani
Q & A
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Q & A (If you see this slide we’ve not run out of time)