1. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Event Management
Proposal for
Distribution Data
Service Standard
José-Luis Poza-Luján
Juan-Luis Posadas-Yagüe
José-Enrique Simó-Ten
University Institute of Control Systems and
Industrial Computing (ai2)
Universitat Politècnica de València (UPV).
···
Events
···
···
···
··
Conditio
Component
Operations
QoS Alarms
QoC Alarms
Message Filters
Event
-m_iState
-m_iType
-m_pCondition
+setState()
+getState()
+getType()
EventAlarm
-m_iAlarmType
-m_iAlarmValue
-m_iStartupAlarm
-m_iThersholdRising
-m_iThersholdFalling
EventComponent
-m_iEventComponentType

2. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
NCS, EBC and Middleware
• Event-Based Control (EBC) paradigm
(also called event-driven control) is
adopted to implement systems where…
– The periodic sampling is not possible.
– The periodic sampling is not recommended
• In networked control systems
(NCS), distributed control elements are
connected by a network.
– Control elements needs to know the
technology
– Problems with synchronization

3. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
NCS, EBC and Middleware
• A middleware enhances and offers to
control elements a set of services in order
to facilitate the access to the network.
– If EBC is used in NCS, the middleware will be an
essential component.
• Middleware architecture is based on
communications paradigms.
– Message passing
– Client-server
– Publish/Subscribe (P/S)
– Blackboard.

4. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
DDS Model
• Data Distribution Service for Real-Time
Systems (DDS) is an OMG standard
middleware based on the P/S paradigm.
– Offers time-controlled communications
between components using Quality of
Service (QoS) polices.
DomainParticipant
write read, takeon_data_available
Producer Consumer
Data
Writer
Data
Writer
Publisher
Data
Reader
Listener
Subscriber
Topic
Data
Writer
Data
Reader
Subscriber
Publisher
Data
Reader
Topic
Topic
DomainParticipant
DomainParticipant
read, take write
Consumer
Producer &
Consumer
Consumer
read, take

5. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
DDS Model
• DDS can be used to send any kind of
Data, including event data.
• DDS allows the application (control
component in NCS) to perform flexible
filtering of events.
Entity
StatusCondition
1
0..1
statuscondition
ConditionWaitSet
* *
GuardCondition ReadCondition

6. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
DDS Model
• DDS can be used to send any kind of
Data, including event data.
• DDS allows the application (control
component in NCS) to perform flexible
filtering of events.
• NCS needs certain event management,
But DDS does not define a built-in event
type and advanced event management.

7. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Event management proposal
• DDS offers adequate support to
coordinate communications between
nodes, but it does not provide a
mechanism to review the internal
characteristics.
• To extend the capacity of DDS, a new
component, called Action, is added.
• The role of Condition and Waitset
components has been increased.

8. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Event management proposal
• Main components are
“Events”, “Conditions” and “Actions”
···
Events
···
Actions
···
···
···
···
···
···
···
Conditions
Component
Operations
QoS Alarms
QoC Alarms
Message Filters
Component
Functions
QoS Configuration
QoC Configuration
Message Filtering

9. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Event management proposal
• In our proposal Condition is similar to
WaitSet DDS element, Event is similar to
Condition and Action is the new element
Entity
1
*
condList
Event
EventAlarm EventFilterEventComponent
Condition
eventList
*
Action
1 *
*
actList

10. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Implementation
• A distributed mobile robot navigation
environment has been used to test the
validity and usefulness of the proposed
model.
• The mobile robot is controlled by a set of
control algorithms.
– Reactive behaviours algorithms, are embedded
within the robot.
– The deliberative algorithms, are implemented
in distributed nodes
• In the experiment, all algorithms are
implemented in distributed nodes

11. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Implementation
• The algorithm used is the “obstacle
avoidance” based on Braitenberg
vehicles behaviours.
Mleft Mright
S0
S1
S2 S3
S4
S5
S6S7

12. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Implementation
• Obstacle avoidance algorithm
1. Sensor detects obstacle and sends the
distance to control node with a specified
period
2. Control node changes the robot speed and
path in function of the distance detected by all
sensors in the ring using the formula to each
motor

13. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Implementation
• Optimization with event management
– The DDS based middleware filters sensor
messages and only sends significant
messages. The time interval between
messages can change the robot speed by
means the formula

14. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Experiment and results
• Two scenarios have been tested
a) Robot in corridor
b) Wall in front of robot
• Event Management influence
1) Robot navigation without middleware event
detection
2) The same navigation with event detection
and one Action linked by means a Condition
Scenarios
(1) DDS
(2) DDS Event
Management
Sampling
Period
Distance
Average
Sampling
Period
Distance
Average
(a) Robot in corridor 10.0 2.1 62.6 2.1
(b) Wall in front of robot 10.0 1.1 9.4 0.6

15. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
a) Robot in corridor
– No significant
differences in
distance
– Message load
optimization
b) Wall in front of
robot
– Significant differences
in distance (speed
optimization)
– Message load
optimization
Experiment and results

16. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Contextualization
DDS Model
Event
management
proposal
Implementation
Experiment and
results
Conclusions and
future work
Conclusions and future work
• Proposal to increase the event
management system proposed in the DDS
standard
• The most significant contribution is the
inclusion of a new object called Action.
– Actions automatically make changes on the
middleware based on a combination of events.
• The Action object has been tested with a
simple mobile robot system.
• Future work
– Test the middleware with complex event
combinations to generate different actions.
– Use priorities in Conditions or in Actions.

17. 10th International Symposium on Distributed Computing and Artificial Intelligence
Salamanca, 22nd-24th May, 2013
Thanks for
your attention
···
Events
···
···
···
··
Conditio
Component
Operations
QoS Alarms
QoC Alarms
Message Filters
Event
-m_iState
-m_iType
-m_pCondition
+setState()
+getState()
+getType()
EventAlarm
-m_iAlarmType
-m_iAlarmValue
-m_iStartupAlarm
-m_iThersholdRising
-m_iThersholdFalling
EventComponent
-m_iEventComponentType
The study described in this
paper is a part of the
coordinated project COBAMI:
Mission-based Hierarchical
Control. Education and
Science Department, Spanish
Government. CICYT: MICINN:
DPI2011-28507-C02-01/02