Applying Feedback Control to
QoS management
- an introduction -
Giovanna.Ferrari@ncl.ac.uk
Outline
Focus
Use of Feedback Control Theory in
computing systems for QoS management
Motivation To apply theory to govern component
execution in the scope of the TAPAS
project, addressing the goal of developing
Trusted and QoS-aware middleware services
for Application Hosting
• Control Theory
• Feedback Control
• Middleware for QoS Control
• Conclusions
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Dynamic Systems and Control Theory
Subject:
soft real-time applications
executing in open and
unpredictable environments
Application over Internet:
Dynamic System living in an
ever changing environment, it
evolves over the time and
nothing is known a priori
• Example: in an e-business server, neither the resource
requirements nor the arrival rate of service requests are known a
priori
• Problem: difficulty meeting performance guarantees, failure
may result in loss of customers and financial damage
• Solution: a well developed analytic foundation for performance
control in physical systems based on Control Theory
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Control Theory
Control Theory
The objective in a Control System is to
make some output behave in a desired
way by manipulating some input,
employing differential equations as a
fundamental modelling tool
• Success: due to its robustness in the face of modelling errors
•
and external disturbances, which reduces the need for accurate
system models
Recent results: Control Theory in Computing Systems
– Network flow controllers (TCP/IP), C. Hollot et al. (U.Mass)
– Lotus Notes admission control, N. Gandhi et al. (IBM)
– QoS in Caching, Y. Lu et al. (U.Virginia)
– Performance guarantees for Apache , T. Abdelzaher et al. 4
Control System
ENVIRONMENT
Control System
thermostat
Represented by a controlled
system in combination with a
controller, their interactions are
observations and manipulations
performed by the controller on
controlled system.
• Example: In a water heater, if
the temperature drops below a
set value, a constant heat source
is switched on, to be switched
off again when the temperature
rises above a set maximum
control
information
CONTROLLER
manipulation
input
cold water
observation
CONTROLLED
SYSTEM
water heater
CONTROL SYSTEM
BOILER
output
hot water
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Control System Strategies
 Feed forward control strategy manipulation through control
actions is determined based on observation of the input to the
controlled system
 A priori workload knowledge, a combination of preruntime analysis
and admission control algorithms ensure that the system is not
overloaded and that the desired performance is achieved
 Feedback control strategy
measurements of the output
delivered are compared with a desired behaviour (reference)
and the difference (error) is used to decide on the control
actions to be taken
 Applied for behaviour optimisation, it regulates control actions
according to continuous performance feedback
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Feedback Control System
The Controller compares the performance
reference with controlled variable to get the
current error, and it calls a control algorithm
to compute the control input, new value of the
manipulated variable based on the error
CONTROLLER
control
algorithm
The Actuator changes the manipulated
variable based on the newly computed
control input
ACTUATOR
control
input
manipulated
variable
SENSOR
sample
controlled
variable
error
+
-
reference
CONTROLLED
SYSTEM
FEEDBACK
CONTROL LOOP
The Sensor measures the controlled variable
and feeds the sample back to the Controller
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Feedback Control
Feedback Control
Continuous monitoring of the controlled
system, comparing the actual behaviour
result against a specification of the
expected behaviour and adjusting the
performances accordingly
Design challenges:
•
•
•
To develop a general methodology for converting specifications
of a computing system into feedback loops with known set
points and feedback control parameters.
To find a convenient interface between the service software and
the middleware control loops that manage its performance.
To design appropriate software performance sensors and
actuators.
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Feedback Control
Potential applications:
 Performance-assured services
(e-commerce, online trading)
 Services differentiation
 Contractual satisfaction guarantees
 Overload control
E-COMMERCE
PRICING
NETWORK QoS
CLIENT
HETEROGENEITY
SERVER OVERLOAD
MULTIMEDIA
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Feedback Control
Related works:
 AMIDST: architecture to support QoS-aware m/w, focusing
on the QoS-control system. An architectural framework, based
on models from Control Theory, observes and manipulates the
state of the m/w platform that supports distributed applications
 CONTROLWARE: m/w architecture for QoS guarantees in
distributed environments. It implements a new paradigm for
QoS control, suitable for system operating in highly uncertain
environments or when accurate system load and resource
models are not available
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Middleware for QoS Control
Diagram of a model
APPLICATIONS
agreed
QoS
difference
COMPARATOR
DECIDER
measurement
(QoS state)
control strategy
INTERPRETER
TRANSLATOR
observation
control action
SENSOR
probe
input
ACTUATOR
MIDDLEWARE PLATFORM
probe
COMPUTING & COMMUNICATION RESOURCES
output
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Middleware for QoS Control
Middleware for QoS Control monitors the output and
reconfigures itself to provide the application with a stable
execution environment
 Adaptation based middleware architecture demands
three principal stages of run time support:
• probing the performance of QoS parameters
• instantiating the initial middleware configuration
• adapting to on-the-fly variations
TAPAS Project: Trusted and QoS-aware middleware services
for Application Hosting
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Conclusions
Applying Feedback Control to QoS management
 Feedback Control Theory offers a valid solution to achieve
performance guarantees for soft real-time applications
 Successfully applied by the engineering community in
controlling a vast variety of physical systems
 Recent results prove that Control Theory can also be
efficiently applied to the control of software performance
 Theoretical basis for the design of a QoS aware middleware
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Selected bibliography
- MODERN CONTROL SYSTEMS, R.Dorf, R.Bishop, Prentice
Hall
- ControlWare: A Middleware Architecture for Feedback
Control of Software Performance, R. Zhang, C.Lu, Tarek F.
Abdelzaher, John A. Stankovic (Department of Computer Science
University of Virginia - 2002)
- SWiFT: A Feedback Control and Dynamic Reconfiguration
Toolkit A.Goel, D.Steere, C.Pu, J.Walpole,(Department of
Computer Science and Engineering Oregon Graduate Institute,
Portland - 1999)
- AMIDST: A QoS-Control Architecture for Object
Middleware, L.Bergmans, A.van Halteren, L.Ferreira Pires,
M.van Sinderen and M.Aksit, (CTIT University of Twente, The
Netherlands - 2000)
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